CN1329741C - Apparatus for obtaining environmental data and method for realizing same - Google Patents
Apparatus for obtaining environmental data and method for realizing same Download PDFInfo
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- CN1329741C CN1329741C CNB021551669A CN02155166A CN1329741C CN 1329741 C CN1329741 C CN 1329741C CN B021551669 A CNB021551669 A CN B021551669A CN 02155166 A CN02155166 A CN 02155166A CN 1329741 C CN1329741 C CN 1329741C
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Abstract
The present invention discloses a device which is suitable for honeycomb mobile station positioning systems and GPS and A-GPS systems to acquire environment data and a method. The environment data acquiring device comprises a power time delay distribution acquisition unit which is connected with a honeycomb mobile station receiver and a GPS receiver, a power time delay distribution pretreatment unit, an environment data extraction unit and a managing unit. The environment data acquiring method of the present invention comprises determining input data type, acquiring power time delay distribution, power time delay distribution pretreatment, environment data extraction and environment data comprehension. The environment data acquiring device and the method of the present invention can effectively suppress influence to the system positioning precision of the honeycomb mobile station positioning systems and the GPS and A-GPS (network auxiliary GPS) systems caused by NLOS errors.
Description
Technical field
The invention belongs to wireless communication and radiolocation field, relate in particular to a kind of device of environmental data and method of realization thereof obtained.
Background technology
The existence of NLOS (Non-Line-Of-Sight) error (a kind of that introduced by non-visual travel path, with respect to the line-of-sight propagation extra time delay in the path delay of time) has significantly reduced based on the mobile station locating system of honeycomb and the bearing accuracy of A-GPS (GPS of network assistance) system.At present, in based on the mobile station locating system of honeycomb, still there is not the simple and practical environmental data collecting method that the NLOS error suppresses that is used for; In the A-GPS system, in order to improve the bearing accuracy of A-GPS receiver under the NLOS environment, U.S. Pat 6313786B1 has proposed the method for environmental data collecting.
For A-GPS (or GPS) receiver environment of living in being discerned and the NLOS error size being estimated, the environment that U.S. Pat 6313786B1 may be in A-GPS (or GPS) receiver is divided into indoor, outdoor two big classes, outdoor environment is divided into subclasses such as suburb, urban district, unscreened open area again, and the urban district further is subdivided into some groups according to the height and the dense degree of building again; For the environmental form of GPS (or A-GPS) receiver present position is discerned, U.S. Pat 6313786B1 determined one group of satellite-signal characteristic parameter as the environmental data of A-GPS (as, the signal to noise ratio (S/N ratio) of the satellite-signal that receives, the first footpath time delay that receives, the peak signal width of correlator output, the Doppler shift of signal, the reception elevation angle of satellite-signal, position angle etc.), such as, all be higher than certain particular value if the signal to noise ratio (S/N ratio) of several satellite-signals that receive is compared with empirical data, just think that the A-GPS receiver is in unscreened open area; All be lower than certain particular value if the signal to noise ratio (S/N ratio) of several satellite-signals that receive is compared with empirical data, it is indoor just to think that A-GPS is in.Patent US6313786B1 estimates that the method for NLOS error size is, at first determine the residing geographical environment kind of A-GPS according to priori data, the empirical data of NLOS error and signal characteristic at that time under according to different geographical environments then, as the elevation angle of the variance of correlator peaks, the satellite-signal that receives, estimate the size of NLOS error.The method that this patent utilization ambient signal improves the GPS bearing accuracy is: the 1) environmental data that reports according to the GPS receiver of asking the location, in conjunction with the data in the experience database, judge the residing geographical environment type of A-GPS receiver and satellite-signal is selected; 2) in the process that the satellite-signal that receives is selected, reject the poor satellite-signal of those signal qualitys, such as those lower satellite-signals of the signal elevation angle, in remaining satellite-signal, again according to the characteristic parameter value of satellite-signal, as the variance of correlator peaks, estimate the size of correction; 3) determine the weighted value of different satellite-signals according to the signal environment parameter,, in carrying out location estimation, determine suitable weight matrix according to the difference of weights.
Above-mentioned U.S. Pat 6313786B1 is by the estimation to the NLOS error size that comprises in the pseudo range measurement under the careful classification of environment and the varying environment, can produce certain effect to suppressing the NLOS error, but, this environmental data collecting method also has following shortcoming: the size that 1) need set in advance the NLOS error according to different geographical environments and priori data, this is a loaded down with trivial details storehouse process of building, and its accuracy is difficult to guarantee; 2) do not provide the method for estimation of NLOS error in TDOA (Time-Differnce-Of-Arrival) measuring system, therefore existing NLOS error estimation only is applicable to the inhibition of NLOS error in the gps system that adopts pseudo range measurement, is not suitable for the inhibition of NLOS error in the TDOA positioning system; 3) though between geographical environment and the NLOS error close contact is arranged, but the thinking that patent US 6313786B1 utilizes the geographical environment feature that positioning error is estimated can not embody the assurance to NLOS error statistics essence, therefore can't realize the optimization in theory of location estimation performance.
Summary of the invention
The present invention is in order to overcome the existing defective that receiver environment of living in is discerned and the NLOS error size is estimated, and a kind of inhibition that both had been applicable to NLOS error in TOA (Time-Of-Arrival) positioning system (as A-GPS) that provides, also be applicable to the environmental data collecting method of the inhibition of NLOS error in TDOA (Time-Difference-Of-Arrival) positioning system, and, this method need not be known the actual position of transfer table, can finish the collection that suppresses the needed environmental parameter of NLOS error in the mobile position estimation process in real time.
The concrete technical scheme that realizes the object of the invention is:
A kind of device that obtains environmental data, be characterized in, with transfer table, base station or mobile position estimation center are used, comprise: with the cellular mobile station receiver, the power time delay distribution collection unit that the baseband signal of base station or the output of mobile position estimation center is connected, the power time delay distribution pretreatment unit that is connected with the output of power time delay distribution collection unit, the environmental data extraction unit that is connected with the output of power time delay distribution pretreatment unit, and the administrative unit that is connected with the output of environmental data extraction unit, this administrative unit output control information is to power time delay distribution collection unit;
Wherein:
The control information that receiving management unit, power time delay distribution collection unit is sent, according to these control informations, power time delay distribution collection unit is from the baseband signal that is received, gather one group of environmental data extraction unit desired power time delay distribution data, this group power time delay distributed data is delivered to the environmental data extraction unit after the pre-service of power time delay distribution pretreatment unit; The environmental data extraction unit is delivered to administrative unit with this environmental data after extracting environmental data; Administrative unit is carried out overall treatment to environmental data, simultaneously power time delay distribution collection unit is controlled.
In the above-mentioned device that obtains environmental data, described power time delay distribution collection unit is made of correlator bank or matched filter banks.
In the above-mentioned device that obtains environmental data, described power time delay distribution pretreatment unit is made up of ground unrest extraction unit, footpath detection threshold determining unit and footpath decision unit.
In the above-mentioned device that obtains environmental data, described environmental data extraction unit is made up of difference power estimation unit and estimation of distribution parameters unit between Motion Recognition parameter estimation unit, sample coefficient of dispersion estimation unit, footpath; Difference power estimation unit and estimation of distribution parameters unit receive respectively from position, amplitude or the power data in the last footpath of power time delay distribution that power time delay distribution pretreatment unit is sent here between Motion Recognition parameter estimation unit, sample coefficient of dispersion estimation unit, footpath; The estimation of distribution parameters unit also receives power time delay distributed data and the detection threshold of sending here from the power time delay distribution pretreatment unit footpath or scatterer simultaneously, and each estimation unit outputs to administrative unit to difference power and distribution parameter between the Motion Recognition parameter of estimating to obtain, sample coefficient of dispersion, footpath.
In the above-mentioned device that obtains environmental data, described administrative unit is made up of NLOS estimation of error unit, NLOS recognition unit under NLOS estimation of error unit, the TDOA pattern under environmental data collecting control module, the TOA pattern; The location mode signal that described environmental data collecting control module issues according to the mobile position estimation center, location estimation mode signal and service quality signal output control information be to power time delay distribution collection unit, exports control information NLOS estimation of error unit under NLOS estimation of error unit or the TDOA pattern under the TOA pattern simultaneously; Under the described TOA pattern under NLOS estimation of error unit or the TDOA pattern NLOS estimation of error unit also receive distribution parameter simultaneously by environmental data extraction unit output, and obtain the average and the variance of NLOS error under the average of NLOS error under the TOA pattern and variance or the TDOA pattern; NLOS recognition unit in this administrative unit receives from difference power and sample coefficient of dispersion between the Motion Recognition parameter of environmental data extraction unit output, footpath respectively and carries out overall treatment, obtains the NLOS recognition result.
A kind of method of environmental data collecting is characterized in, may further comprise the steps:
A, according to the station-keeping mode that mobile position estimation adopts, determine the signal kinds that environmental data collecting need be imported;
B, from the baseband signal of cellular mobile station receiver output, perhaps from the baseband signal of GPS receiver output, perhaps simultaneously from these two kinds of baseband signals, gather one group of power time delay distributed data according to control information;
C, the described power time delay distributed data of step b carried out ground unrest extracts, the footpath detection threshold is determined and the footpath judgement, finish environmental data and extract needed pre-service;
D, utilize the result who obtains in the described preprocessing process of step c, from the power time delay distributed data, extract environmental data according to station-keeping mode and location estimation pattern;
E, environmental data that steps d is extracted is carried out overall treatment.
In the said method, the station-keeping mode that described mobile position estimation adopts comprises: 1) based on the station-keeping mode of cellular network; 2) based on the station-keeping mode of A-GPS; 3) comprehensive utilization cellular network signals and gps signal carry out the station-keeping mode that time delay is estimated.
In the said method, the described station-keeping mode that adopts according to mobile position estimation is determined the signal kinds of environmental data collecting needs input, is meant: if based on the location of cellular network, then only the pilot signal of Cellular Networks is carried out the Multipath searching acquisition process; If the location that comprehensive utilization cellular network signals and gps signal carry out the time delay estimation, then need simultaneously the pilot signal and the gps signal of Cellular Networks are carried out acquisition process.
In the said method,, adopt and carry out location estimation based on the TDOA pattern for station-keeping mode based on cellular network; For station-keeping mode, then adopt based on the TOA pattern and carry out location estimation based on A-GPS; Station-keeping mode for comprehensive utilization cellular network signals and gps signal then adopts simultaneously based on TOA pattern and TDOA pattern and carries out location estimation.
In the said method, step b comprises that also alignment quality as requested determines corresponding control information, and this control information comprises: the frequency acquisition that need gather number that the number of the pseudo-random code that its power time delay distributes, same a kind of power time delay that needs are gathered distribute simultaneously, various power time delay is distributed and coherent length and the noncoherent accumulation number of times of gathering power time delay employing when distributing.
In the said method, the described power time delay distribution that step b is obtained is carried out pre-service and is comprised three sub-steps:
C1, extraction ground unrest NP;
The detection threshold THR in c2, definite footpath;
C3, determine the amplitude or the power of first path position, first footpath amplitude or power, most powerful path position, most powerful path power or amplitude, local most powerful path position, local most powerful path.
In the said method, the described extraction environmental data of steps d comprises that Motion Recognition calculation of parameter substep, sample coefficient of dispersion calculate difference power calculating substep and estimation of distribution parameters substep between substep, footpath; Wherein:
The method of d1, Motion Recognition calculation of parameter is:
The first step, position, amplitude or the power information in the footpath that N power time delay of certain pseudo-random code correspondence of obtaining according to power time delay distribution preprocessing process distributes are selected a footpath that is used for Motion Recognition in certain interval after the head footpath;
In second step, calculate the amplitude or the power sample coefficient of dispersion in N the NLOS footpath of from N power time delay distributes, picking out;
The 3rd step compared the second sample coefficient of dispersion that obtain of step with the decision threshold THR-MOVE that obtains from empirical data, move if the sample coefficient of dispersion, just is judged to transfer table greater than THR-MOVE, otherwise it is static to be judged to transfer table;
D2, sample coefficient of dispersion computing method are, position, amplitude or the power information in the footpath that N power time delay of certain pseudo-random code correspondence of obtaining according to power time delay distribution preprocessing process distributes, from N power time delay distributes, pick out N the amplitude or the performance number in footpath unexpectedly the strongest, the amplitude or the performance number in this N footpath unexpectedly the strongest are calculated the sample coefficient of dispersion;
The computing method that difference power calculates between d3, footpath are, position, amplitude or the power information in the footpath of N power time delay distribution of certain pseudo-random code correspondence of obtaining according to power time delay distribution preprocessing process are done following processing:
1) each during N power time delay distributed is selected the amplitude or the power of the strongest footpath unexpectedly and local most powerful path, ratio calculated;
2) each during N power time delay distributed is calculated the difference of the time of arrival of time of arrival in first footpath and most powerful path;
D4, NLOS error profile parameter estimation are divided into the estimation of the distribution parameter of the estimation of distribution parameter of discrete form and conitnuous forms.
In the said method, the described location estimation pattern of steps d adopts carries out location estimation at the mobile position estimation center, then extracts the estimation that environmental data comprises NLOS error profile parameter.
In the said method, the overall treatment of the environmental data of described step e comprises the estimator step e12 and the NLOS recognin step e13 of NLOS error mean and variance under the estimator step e11, TDOA pattern of NLOS error mean and variance under the TOA pattern:
Wherein:
E11, the probability density function that utilizes NLOS error under the TOA pattern and distribution parameter carry out the estimation of NLOS error mean and variance;
E12, the probability density function that utilizes NLOS error under the TDOA pattern and distribution parameter carry out the estimation of NLOS error mean and variance;
Difference power carries out comprehensively obtaining the NLOS recognition result between e13, the Motion Recognition parameter by steps d is obtained, sample coefficient of dispersion, footpath.
In the said method, the concrete grammar that carries out NLOS identification is: judge that at first whether the Motion Recognition parameter is greater than certain thresholding, if the Motion Recognition parameter is greater than certain thresholding, just show that cellular mobile station or A-GPS are in the motion, under the situation of this transfer table motion, determine according to the sample coefficient of dispersion whether the channel of corresponding pseudo-random code correspondence is the NLOS channel again, greater than certain thresholding, be exactly the NLOS channel, otherwise, be exactly the LOS channel; If cellular mobile station or A-GPS remain static, just adopt that difference power judges whether the channel into NLOS between sample footpath.
In the said method, adopt difference power between the sample footpath to judge whether for NLOS channel concrete grammar to be: whether the ratio K of 1) judging most powerful path in the power time delay distribution and local most powerful path is greater than certain thresholding; 2) whether the time delay spacing T of first footpath and most powerful path is less than certain thresholding;
If above-mentioned two conditions are set up simultaneously, just be judged to LOS, otherwise, be judged to NLOS.
In the said method, described local most powerful path is meant that certain position after most powerful path begins until the most powerful path that searches out in such interval, search window end.
In the said method, whether the time delay spacing T of described first footpath and most powerful path is meant that less than certain thresholding whether T is less than a chip width.
Environmental data collecting apparatus and method of the present invention, can obtain in real time, exactly and suppress the needed environmental data of NLOS error, utilization to these environmental datas, can suppress the NLOS error effectively to influence, improve bearing accuracy based on the mobile station locating system and A-GPS (GPS of the network assistance) system accuracy of honeycomb.
Description of drawings
Concrete feature of the present invention, performance and advantage can further be found out from the description of following embodiment and accompanying drawing.
Fig. 1 is the structure that cellular mobile station of the present invention and A-GPS gather the device of environmental data
Fig. 2 is the structure of environmental data extraction unit among Fig. 1
Fig. 3 is the structure of administrative unit among Fig. 1
Fig. 4 be among Fig. 1 NLOS error profile parameter and the footpath between difference power statistical method synoptic diagram
Fig. 5 is an environmental data collecting method schematic flow sheet of the present invention.
Embodiment
Environmental data of the present invention is meant difference power R between the kinematic parameter M, the sample coefficient of dispersion σ/μ that are used for the NLOS channel identification, footpath and is used to estimate the distribution parameter P of NLOS error
iThe structure of environmental data collecting device of the present invention, principle of work and environmental data collecting method are as follows.
See also Fig. 1, a kind of device that obtains environmental data of the present invention comprises: the power time delay distribution collection unit 105, power time delay distribution pretreatment unit 106, environmental data extraction unit 107 and the administrative unit 108 that link to each other with the base band output of cellular mobile station and A-GPS; Wherein:
The control information that receiving management unit, power time delay distribution collection unit is sent, according to these control informations, power time delay distribution collection unit is by the interface between the baseband signal of this unit and the output of cellular mobile station receiver, perhaps this unit by and the baseband signal of GPS receiver output between interface, this unit is respectively or simultaneously from these two kinds of baseband signals, gather one group of environmental data extraction unit desired power time delay distribution data, this group power time delay distributed data is delivered to the environmental data extraction unit after the pre-service of power time delay distribution pretreatment unit; The environmental data extraction unit is delivered to administrative unit with this environmental data after extracting environmental data; This administrative unit output control information is to power time delay distribution collection unit; Comprehensive unit carries out overall treatment to environmental data, simultaneously power time delay distribution collection unit is controlled.
Power time delay distribution collection unit 105 is made of correlator bank (or matched filter banks), this correlator bank has multiple implementation method: can be the design separately of environmental data collecting device, also can be to use the correlator bank in the Multipath searching unit in the cellular mobile station or the correlator bank of using in the A-GPS receiver realizes.The control information that 105 receiving management unit 108, power time delay distribution collection unit are sent, as, the number (corresponding a kind of power time delay of each pseudo-random code distributes) of the pseudo-random code that its power time delay distributes need be gathered simultaneously; The number that needs same a kind of power time delay distribution (corresponding same pseudo-random code) of collection; Frequency acquisition to various power time delay distributions; Gather the coherent length and the noncoherent accumulation number of times that adopt when power time delay distributes, according to these control informations, power time delay distribution collection unit 105 is from cellular mobile station receiver radio frequency front end baseband signals 101 outputs, through 103 quantifications of one of A/D converter, perhaps from 2 104 baseband signals that quantize 102 outputs of GPS receiver radio frequency front end, through A/D converter, perhaps simultaneously from these two kinds of baseband signals, gather one group of environmental data extraction unit, 107 desired power time delay distribution data.This power time delay distributed data is delivered to environmental data extraction unit 107 after 106 pre-service of power time delay distribution pretreatment unit; After environmental data extraction unit 107 extracts environmental data, this environmental data is delivered to administrative unit 108; 108 pairs of environmental datas of comprehensive unit carry out overall treatment, simultaneously power time delay distribution collection unit 105 are controlled.
Power time delay distribution pretreatment unit 106 is made up of ground unrest extraction unit, footpath detection threshold determining unit and footpath decision unit.Wherein, the distribution parameter of the needed ground unrest of ground unrest extraction unit extraction footpath detection threshold determining unit (as, average and standard deviation), the ground unrest extraction unit divides two steps to extract ground unrest: the first step, the rough extraction, can realize the rough extraction of ground unrest by the method for in power time delay distributes, rejecting several most powerful paths, also can be by using idle pseudo-random code (idle pseudo-random code can be the scrambler that near the base station of cellular mobile station does not have use, also can be the positioning signal sign indicating number of extrapolating in the gps satellite ephemeris that is in the following satellites transmits in local horizon); Second step, accurately extract, rough extract ground unrest after, the ground unrest NC of rough extraction is carried out parameter estimation, as, estimate rough average and standard deviation, (approximately think x according to the distribution form of the average that estimates, standard deviation, ground unrest
2Distribute or normal distribution) and specific detection probability, determine a rough footpath detection threshold THR_C, utilize THR_C from corresponding power time delay distributes, to detect a first footpath PATH1_C, on this power time delay distributes, begin to open in beginning such interval, position from several chips before the PATH1_C, extract accurate ground unrest NP to search window.The accurate ground unrest NP that footpath detection threshold determining unit provides according to the ground unrest extraction unit carries out the parameter estimation of ground unrest, obtains average and the standard deviation of NP, then according to the distribution form (x of the average that estimates, standard deviation, ground unrest NP
2Distribute or normal distribution) and specific detection probability, determine final footpath detection threshold THR.When ground unrest NP is normal distribution, THR=Mu+k*Sigma, wherein, Mu represents the average of ground unrest, and Sigma represents the standard deviation of ground unrest, and k is a weighting coefficient, and the value of k is detected the false alarm rate decision that requires by the footpath.For using a plurality of power time delay of obtaining with a kind of pseudo-random code to distribute, a plurality of THR are arranged.The footpath decision unit is according to each power time delay corresponding footpath detection threshold THR that distributes, and the method by detection peak point on corresponding power time delay distributes realizes the footpath judgement, and the power time delay position of going up every peak point greater than THR that distributes is exactly position directly.The footpath decision unit is on the basis of carrying out the footpath judgement, further finish the 107 needed pre-service of environmental data extraction unit, as, the directly amplitude (or power) of amplitude (or power), most powerful path position, most powerful path power (or amplitude), local most powerful path (local most powerful path is meant that certain position after most powerful path begins until the most powerful path that searches out in such interval, search window end) position, local most powerful path of path position, head of determining to inform against.There is not effective diameter if determine certain power time delay on distributing, just the extraction of environmental data do not carried out in this power time delay distribution according to (or scatterer) detection threshold in footpath.
Environmental data extraction unit 107 extracts environmental data from the power time delay distributed data that power time delay distribution pretreatment unit 106 is sent here.This unit is according to 106 supplementarys of sending here, as, the distribute amplitude (or power) of (or scatterer) detection threshold that goes up the footpath, first path position, first footpath amplitude (or power), most powerful path position, most powerful path power (or amplitude), local most powerful path position, local most powerful path of different types of power time delay, the various power time delay environmental data information of carrying that distributes is extracted, obtained difference power R between the Motion Recognition parameter M, the sample coefficient of dispersion σ/μ that are used for the NLOS channel identification, footpath and be used to estimate the distribution parameter P of NLOS error
i
See also Fig. 2.The environmental data extraction unit forms 207 by difference power estimation unit 206 and estimation of distribution parameters unit between Motion Recognition parameter estimation unit 204, sample coefficient of dispersion estimation unit 205, footpath.201 are meant the power time delay distributed data of sending here from 106; 202 are meant (or scatterer) detection threshold from 106 footpaths of sending here, and different power time delay distributes and has different detection threshold.203 are meant from 106 power time delay sent here the distribute position of going up the footpath, amplitude (or power) data (as the distribute amplitude (or power) of (or scatterer) detection threshold that goes up the footpath, first path position, first footpath amplitude (or power), most powerful path position, most powerful path power (or amplitude), local most powerful path position, local most powerful path of, different types of power time delay).
Wherein, Motion Recognition parameter M computing unit 204 is made up of three steps: the first step, certain pseudo-random code according to 106 outputs of power time delay distribution pretreatment unit, (this pseudo-random code can be the scrambler that the pilot tone of Serving cell adopts, also can be the scrambler that adjacent district pilots adopts) corresponding N power time delay distribution is (usually, the span of N is 4～20) the position and amplitude (or power) information in footpath, select a footpath that is used for Motion Recognition (this footpath must be NLOS directly) in certain interval after the head footpath; In second step, calculate amplitude (or power) the sample coefficient of dispersion in N the NLOS footpath of from N power time delay distributes, picking out; In the 3rd step, sample coefficient of dispersion that obtains and the decision threshold THR-MOVE that obtains from empirical data compare in second step, and THR-MOVE gets about 0.1 usually, if the sample coefficient of dispersion is greater than THR-MOVE, just be judged to transfer table motion, otherwise it is static to be judged to transfer table;
Sample coefficient of dispersion σ/μ (the expression standard deviation is divided by average) computing unit 205 (can be the scrambler of the pilot tone employing of Serving cell according to certain pseudo-random code of power time delay distribution pretreatment unit 106 outputs, also can be the scrambler that adjacent district pilots adopts) corresponding N power time delay distribution is (usually, the span of N is 4～20) the position in footpath, and amplitude (or power) information, from N power time delay distributes, pick out N amplitude (or power) value in footpath unexpectedly the strongest, amplitude (or power) value in this N footpath unexpectedly the strongest is calculated sample coefficient of dispersion σ/μ;
Difference power estimation unit 206 (can be the scrambler of the pilot tone employing of Serving cell according to certain pseudo-random code of power time delay distribution pretreatment unit 106 outputs between the footpath, it also can be the scrambler that adjacent district pilots adopts, also can be the P sign indicating number (smart sign indicating number) of gps satellite emission) corresponding N power time delay distribution is (usually, the span of N is 4～20) the position in footpath, and amplitude (or power) information, do following processing: each in 1) N power time delay being distributed is selected the strongest footpath (as 404 among Fig. 4) Max_Path unexpectedly and local most powerful path Local_Max_Path (as 409 among Fig. 4, among Fig. 4 408 and 410 is starting point and terminal points of local most powerful path search window, starting point 408 is positioned at several chip places, back of most powerful path) amplitude (or power), ratio calculated Max_Path/Local_Max_Path; 2) each during N power time delay distributed calculate first footpath time of arrival Time_Of_First_Path_Arrival and most powerful path Max_Path time of arrival Time_Of_Max_Path_Arrival difference;
Estimation of distribution parameters unit 207 carries out NLOS error profile parameter P
iThe essence of estimation be to transfer table, or A-GPS receiver, near the estimation of scatterer density, this estimation are to realize that by the processing that the power time delay that power time delay distribution collection unit 105 (being the Multipath searching unit) obtained distributes Fig. 4 is to NLOS error profile parameter P
iCarry out the estimation principles synoptic diagram.The power time delay of 406 certain pseudo-random code of sending here for power time delay distribution collection unit 105 among Fig. 4 distributes, 405 is footpath decision threshold THR, 401 is directly first for what rule out according to footpath decision threshold THR, 402 is the reference position of scatterer statistic window, 403 is the end position of scatterer statistic window, the width of reference position 402 several (as 1) chips of interval of first path position 401 and scatterer statistic window is (under the NLOS channel, the scatterer statistic window also can comprise first footpath), interval (being the width of scatterer statistic window) is several chips between the reference position 402 of scatterer statistic window and the end position 403 of scatterer statistic window, as 1～10 chip.404 is a detected footpath in the scatterer statistic window, the corresponding spatially distinguishable scatterer in this footpath.Dnlos407 is (with respect to the LOS travel path) error in relative time delay that the NLOS travel path is introduced, i.e. NLOS error, and the NLOS error has non-negative characteristic.The ratio of the number by calculating the footpath that surpasses footpath decision threshold THR in the scatterer statistic window and the width of scatterer statistic window just can obtain NLOS error profile parameter P
iMaximum likelihood estimator.During specific implementation, both can adopt formula (1), and also can adopt formula (2) to finish NLOS error profile parameter P
iEstimation.
In the formula: P
iBe NLOS error profile parameter; m
kBe k (k=1,2 ... n) number in detected footpath in the individual scatterer statistic window (from k power time delay distribution intercepting); W is the width of scatterer statistic window, and unit is a chip, and usually, the value of W is between 1～10 chip; N is for obtaining a P
iThe number that distributes of the power time delay that estimated value adopted, usually, the value of N is between 1～10, used N power time delay distribution is to carry out N Multipath searching to obtain in the regular hour interval; α is the sampling number that carries out in the chip, and usually, α is value between 1～32, and the α value is exactly a number of samples that the footpath comprises.
In the formula: P
1Be NLOS error profile parameter; s
kBe k (k=1,2 ... N) the detected number that surpasses the sampling point of detection threshold in the individual scatterer statistic window (from k power time delay distribution intercepting); W is the width of scatterer statistic window, and unit is a sampling point, and usually, the value of W is within 40 sampling points, and representative value is 20 sampling points; N is for obtaining a P
iThe number that distributes of the power time delay that estimated value adopted, usually, the value of N is between 1～10, used N power time delay distribution is to carry out N Multipath searching to obtain in the regular hour interval.
According to formula (3), can be by ρ
iObtain δ
iDistribution parameter θ
i
In the formula, T is systematic sampling sampling point interval time, and unit is a microsecond.
Utilize formula (1) or formula (2) to obtain i, the distribution parameter ρ between j radiation source
iAnd ρ
jAfterwards, just obtained NLOS error delta in the TDOA system of discrete form
(s) ijDistribution parameter;
Utilize distribution parameter P
i, P
jAnd formula (3), just obtained NLOS error delta in the TDOA system of conitnuous forms
IjDistribution parameter θ
iAnd θ
j
The environmental data that environmental data extraction unit 107 extracts, as, be used for difference power R between Motion Recognition parameter M, sample coefficient of dispersion σ/μ, the footpath of NLOS channel identification and be used to estimate the distribution parameter P of NLOS error
i, deliver to administrative unit and do overall treatment.
See also Fig. 3, administrative unit 108 is made up of NLOS estimation of error unit 303, NLOS recognition unit 304 under NLOS estimation of error unit 302, the TDOA pattern under environmental data collecting control module 301, the TOA pattern.Administrative unit 108 is finished two major functions, the one, power time delay distribution collection unit 105 is controlled, send control information to power time delay distribution collection unit 105 by environmental data collecting control module 301 shown in Figure 3, as, the power time delay that needs to gather those pseudo-random codes distributes, need gather the distribution of what power time delay to a pseudo-random code; The 2nd, the environmental data that environmental data extraction unit 107 is extracted carries out comprehensively, obtains to be used for the data that the NLOS error is corrected.
The location mode signal that described environmental data collecting control module issues according to the mobile position estimation center, location estimation mode signal and service quality (QOS:quality of service) signal output control information is to power time delay distribution collection unit, exports control information NLOS estimation of error unit under NLOS estimation of error unit or the TDOA pattern under the TOA pattern simultaneously; Under the TOA pattern under NLOS estimation of error unit or the TDOA pattern NLOS estimation of error unit also receive distribution parameter simultaneously by environmental data extraction unit output, and obtain the average and the variance of NLOS error under the average of NLOS error under the TOA pattern and variance or the TDOA pattern; NLOS recognition unit in this administrative unit receives from difference power and sample coefficient of dispersion between the Motion Recognition parameter of environmental data extraction unit output, footpath respectively and carries out overall treatment, obtains the NLOS recognition result.
Wherein, NLOS estimation of error unit 302 is used for obtaining the average and the variance of the NLOS error that TOA (or pseudorange) measures under the TOA pattern.As, for the NLOS error delta in TOA (or pseudorange) measurement of obtaining continuous distribution
iAverage and variance, at first utilize formula (3), from the distribute distribution parameter P of NLOS error of extraction of one group of power time delay of i pseudo-random code correspondence
i, the distribution parameter θ of the NLOS error during the TOA (or pseudorange) that obtains continuous distribution measures
iUtilize formula (4), (5) just can calculate the average and the variance of the NLOS error in TOA (or pseudorange) measurement again;
E[δ
i]＝θ
i (4)
In the formula, δ
iIt is the NLOS error in TOA (or pseudorange) propagation delay of i pseudo-random code of continuous distribution;
NLOS estimation of error unit 303 calculates the average and the variance of the NLOS error in the TDOA measuring system under the TDOA pattern.As, in order to obtain the average and the variance δ of the NLOS error of TDOA between i and j the pseudo-random code, continuous distribution in measuring
Ij, at first utilize formula (3) and from the distribution parameter P of the NLOS error extracted respectively on one group of power time delay of i and j pseudo-random code correspondence distributes
i, P
j, the distribution parameter θ of the NLOS error during the TOA (or pseudorange) that obtains continuous distribution measures
iAnd θ
j, calculate δ according to formula (6) then
IjAverage, utilize formula (7) to calculate δ
IjVariance.
E[δ
ij]＝θ
j-θ
i (6)
NLOS recognition unit 304 is gone up the Motion Recognition parameter M that extracts to one group of power time delay distribution of certain pseudo-random code correspondence, difference power R carries out comprehensively between sample coefficient of dispersion σ/μ and footpath, whether the channel of determining this pseudo-random code correspondence is the NLOS channel, concrete grammar is: judge that at first whether Motion Recognition parameter M is greater than certain thresholding, as, whether greater than 0.2, if Motion Recognition parameter M is greater than certain thresholding, just show that cellular mobile station or A-GPS are in the motion, under the situation of this transfer table motion, determine according to sample coefficient of dispersion σ/μ whether the channel of corresponding pseudo-random code correspondence is the NLOS channel again, σ/μ is greater than certain thresholding, as 0.1, be exactly the NLOS channel, otherwise, be exactly LOS (Line-Of-Sight) channel; If cellular mobile station or A-GPS remain static, just adopt that difference power R judges whether the channel into NLOS between sample footpath, concrete grammar is whether set up simultaneously judgment formula (8), (9).
R＝Max_Path/Local_Max_Pat＞K (8)
Time_Of_First_Path_Arrival-Time_Of_Max_Path_Arrival＜T (9)
If set up simultaneously, just be judged to LOS, otherwise, be judged to NLOS.The K value choose the compromise that need consider discrimination and False Rate, the value of general K is chosen between 2～8; The span of T is approximately the width of a chip.
Administrative unit 108 by to comprehensively obtaining of environmental data after the average and variance of NLOS recognition result, NLOS error, mobile station locating system just can be realized the inhibition to the NLOS error as follows: the average of 1) using the NLOS error is corrected stochastic variable as zero-mean to non-negative NLOS error; 2) weighting matrix during the variance of use NLOS recognition result and NLOS error structure weighted least-squares is estimated tentatively suppresses NLOS error (average has been zero) to the position estimation effect; 3) according to the zero mean characteristic of the NLOS error after correcting,, further suppress the NLOS error by multiple averaging to the position estimated result.
Environmental data collecting device of the present invention both can adopt software to realize, also can adopt hardware to realize; Both can in portable terminal, realize, also can realize at the mobile position estimation center.When realizing environmental data collecting device of the present invention at mobile station side, if location estimation is to finish at mobile station side, administration module is just the location estimation unit that sends to through comprehensive environmental data in the transfer table; If location estimation is finished at the mobile position estimation center, the environmental data that administrative unit 108 is just extracted environmental data extraction unit 107 sends the mobile position estimation center of network side to by air interface; When realizing device of the present invention at the mobile position estimation center, the baseband signal that transfer table (cellular mobile station or the A-GPS) collection that need at first be located by needs receives, it can be the baseband signal of the pilot signal of the base station that receives of transfer table, also can be the baseband signal of the satellite positioning signal that receives of A-GPS terminal, by wireless network the baseband signal that collects be sent to the mobile position estimation center then.At first these baseband signals are carried out certain pre-service at the mobile position estimation center, as offset part interference to improve the signal interference ratio of desired signal, and then these are passed through pretreated baseband signal deliver to power time delay distribution collection unit 105, through 105 and the processing of follow-up unit after, just can obtain the environmental data that suppresses the NLOS error.
See also Fig. 5.The method of the invention environmental data collecting method comprises the steps:
A, according to the station-keeping mode that mobile position estimation adopts, determine the signal kinds that environmental data collecting need be imported;
B, from the baseband signal of cellular mobile station receiver output, perhaps from the baseband signal of GPS receiver output, perhaps simultaneously from these two kinds of baseband signals, gather one group of power time delay distributed data according to control information;
C, the described power time delay distributed data of step b carried out ground unrest extracts, the footpath detection threshold is determined and the footpath judgement, finish environmental data and extract needed pre-service;
D, utilize the result who obtains in the described preprocessing process of step c, from the power time delay distributed data, extract environmental data according to station-keeping mode and location estimation pattern;
E, environmental data that steps d is extracted is carried out overall treatment.
Concrete grammar is:
Step a, the kind 501 of definite input data.Station-keeping mode according to mobile position estimation adopts has three kinds of basic fixed position patterns: 1) based on the location of cellular network; 2) based on the location of A-GPS; 3) comprehensive utilization cellular network signals and gps signal carry out the location that time delay is estimated.Step a is according to the concrete station-keeping mode that adopts, determine that environmental data collecting unit 105 needs the signal classification of input, if based on the location of cellular network, environmental data collecting unit 105 just only carries out acquisition process (promptly carrying out Multipath searching) to the pilot signal of Cellular Networks; If comprehensive utilization cellular network signals and gps signal carry out the location that time delay is estimated, environmental data collecting unit 105 carries out acquisition process to the pilot signal and the gps signal of Cellular Networks simultaneously with regard to needs.In addition, step a also as requested alignment quality (as precision, response time) determines corresponding control information, as, need gather the number (a corresponding a kind of power time delay of pseudo-random code distributes) of the pseudo-random code that its power time delay distributes simultaneously; The number that needs same a kind of power time delay distribution (corresponding same pseudo-random code) of collection; Frequency acquisition to various power time delay distributions; Gather the coherent length and the noncoherent accumulation number of times that adopt when power time delay distributes;
Step b gathers power time delay and distributes 502.Environmental data collecting kind and control parameter that step b determines according to step a, as, the number (a corresponding a kind of power time delay of pseudo-random code distributes) of the pseudo-random code that its power time delay distributes need be gathered simultaneously; The number that needs same a kind of power time delay distribution (corresponding same pseudo-random code) of collection; Frequency acquisition to various power time delay distributions; Gather the coherent length and the noncoherent accumulation number of times that adopt when power time delay distributes, the power time delay of obtaining the specific pilot signal of cellular network by Multipath searching (being realized by one group of correlator or matched filter) distributes or the power time delay of satellite positioning signal distributes;
Step c, power time delay distribution pre-service 503.The power time delay that this step is obtained step b distributes and carries out pre-service, purpose is to obtain environmental data and extracts more needed parameters, as, the amplitude (or power) of footpath detection threshold THR, first path position, first footpath amplitude (or power), most powerful path position, most powerful path power (or amplitude), local most powerful path (local most powerful path is meant that certain position after most powerful path begins until the most powerful path that searches out in such interval, search window end) position, local most powerful path.This step is made up of three sub-steps:
Substep c1 extracts ground unrest NP, and its principle is identical with the corresponding part in Unit 106;
The detection threshold THR in substep c2, definite footpath, its principle is identical with the corresponding part in Unit 106;
Substep c3, determine the amplitude (or power) of first path position, first footpath amplitude (or power), most powerful path position, most powerful path power (or amplitude), local most powerful path (local most powerful path is meant that certain position from most powerful path after begins the most powerful path that searches out in such interval, search window end) position, local most powerful path, its principle is identical with the corresponding part in Unit 106;
Steps d is extracted environmental data 504.Utilize the result who obtains in the described preprocessing process of step c, from the power time delay distributed data, extract environmental data according to station-keeping mode and location estimation pattern; Described location estimation pattern adopts carries out location estimation at the mobile position estimation center, and then the environmental data collecting unit directly reports NLOS error profile parameter.This step is finished difference power calculating and estimation of distribution parameters between Motion Recognition calculation of parameter, the calculating of sample coefficient of dispersion, footpath.
The method of Motion Recognition calculation of parameter is, the first step, certain pseudo-random code of obtaining according to power time delay distribution preprocessing process (can be the scrambler of the pilot tone employing of Serving cell, also can be the scrambler that adjacent district pilots adopts) corresponding N power time delay distribution is (usually, the span of N is 4～20) the position and amplitude (or power) information in footpath, select a footpath that is used for Motion Recognition (this footpath must be NLOS directly) in certain interval after the head footpath; In second step, calculate amplitude (or power) the sample coefficient of dispersion σ/μ in N the NLOS footpath of from N power time delay distributes, picking out; In the 3rd step, sample coefficient of dispersion that obtains and the decision threshold THR-MOVE that obtains from empirical data compare in second step, and THR-MOVE gets about 0.1 usually, if sample coefficient of dispersion σ/μ is greater than THR-MOVE, just be judged to transfer table motion, otherwise it is static to be judged to transfer table;
The sample coefficient of dispersion (is that standard deviation is divided by average σ/μ, σ represents standard deviation, μ represents average) computing method are, certain pseudo-random code of obtaining according to power time delay distribution preprocessing process (can be the scrambler of the pilot tone employing of Serving cell, also can be the scrambler that adjacent district pilots adopts) corresponding N power time delay distribution is (usually, the span of N is 4～20) the position in footpath, and amplitude (or power) information, from distributing, N power time delay pick out N amplitude (or power) value in footpath unexpectedly the strongest, amplitude (or power) value to this N footpath unexpectedly the strongest is calculated sample coefficient of dispersion σ/μ, represents that promptly standard deviation is divided by average);
The computing method that difference power calculates between the footpath are, certain pseudo-random code of obtaining according to power time delay distribution preprocessing process (can be the scrambler of the pilot tone employing of Serving cell, it also can be the scrambler that adjacent district pilots adopts, N the corresponding power time delay of P sign indicating number (smart sign indicating number or thick sign indicating number) that also can be the gps satellite emission distributes (usually, the span of N is 4～20) the position in footpath, and amplitude (or power) information, do following processing: each in 1) N power time delay being distributed is selected the strongest footpath (as 404 among Fig. 4) Max_Path unexpectedly and local most powerful path Local_Max_Path (as 409 among Fig. 4, among Fig. 4 408 and 410 is starting point and terminal points of local most powerful path search window, starting point 408 is positioned at several chip places, back of most powerful path) amplitude (or power), ratio calculated Max_Path/Local_Max_Path; 2) each during N power time delay distributed calculate first footpath time of arrival Time_Of_First_Path_Arrival and most powerful path Max_Path time of arrival Time_Of_Max_Path_Arrival difference;
NLOS error profile parameter estimation is divided into the distribution parameter P of discrete form
iEstimation and the distribution parameter θ of conitnuous forms
iEstimation, P
iCan adopt formula (1) or formula (2) to obtain θ
iCan pass through P
iAnd formula (3) obtains.
Step e, comprehensive 505 of environmental data.This step is discerned three sub-steps by estimation, the NLOS of NLOS error mean and variance under the estimation of NLOS error mean and variance under the TOA pattern, the TDOA pattern and is formed:
Substep e1, the estimation of NLOS error mean and variance under the TOA pattern.Can utilize the probability density function of NLOS error, be geometric distributions as the NLOS error of discrete form under the TOA pattern, and having obtained distribution parameter by step 4 again is P
iThe NLOS error of conitnuous forms is monolateral exponential distribution under the TOA pattern, has obtained distribution parameter θ by step 4 again
i, so just can calculate average and standard deviation according to the definition of average and standard deviation.For easy, also can directly use existing conclusion, as, utilize formula (4), (5) just can calculate the average and the variance of the NLOS error in TOA (or pseudorange) measurement;
Substep e2, the estimation of NLOS error mean and variance under the TDOA pattern.Can utilize the probability density function of NLOS error, be bilateral geometric distributions as the NLOS error of discrete form under the TDOA pattern, and having obtained distribution parameter by step 4 again is P
i, P
jThe NLOS error of conitnuous forms is bilateral exponential distribution under the TDOA pattern, has obtained distribution parameter θ by step 4 again
i, θ
j, so just can calculate average and standard deviation according to the definition of average and standard deviation.For easy, also can directly use existing conclusion, as, utilize formula (6), (7) just can calculate the average and the variance of the NLOS error in the TDOA measurement;
Substep e3 carries out NLOS identification, and promptly difference power carries out comprehensively obtaining reliable NLOS recognition result between the Motion Recognition parameter that step 504 is obtained, sample coefficient of dispersion, footpath.Concrete grammar is: judge that at first whether Motion Recognition parameter M is greater than certain thresholding, as, whether greater than 0.2, if Motion Recognition parameter M is greater than certain thresholding, just show that cellular mobile station or A-GPS are in the motion, under the situation of this transfer table motion, determine according to sample coefficient of dispersion σ/μ whether the channel of corresponding pseudo-random code correspondence is the NLOS channel, and σ/μ is greater than certain thresholding again, as 0.1, be exactly the NLOS channel, otherwise, be exactly LOS (Line-Of-Sight) channel; If cellular mobile station or A-GPS remain static, just adopt that difference power R judges whether the channel into NLOS between sample footpath, concrete grammar is whether set up simultaneously judgment formula (8), (9).
If set up simultaneously, just be judged to LOS, otherwise, be judged to NLOS.The K value choose the compromise that need consider discrimination and False Rate, the value of general K is chosen between 2～8; The span of T is approximately the width of a chip.
Environmental data collecting apparatus and method of the present invention are equally applicable to other wireless systems, as in the WLAN (wireless local area network) to the inhibition of NLOS error.
Claims (18)
1, a kind of device that obtains environmental data, it is characterized in that, with transfer table, base station or mobile position estimation center are used, comprise: with the cellular mobile station receiver, the power time delay distribution collection unit that the baseband signal of base station or the output of mobile position estimation center is connected, the power time delay distribution pretreatment unit that is connected with the output of power time delay distribution collection unit, the environmental data extraction unit that is connected with the output of power time delay distribution pretreatment unit, and the administrative unit that is connected with the output of environmental data extraction unit, this administrative unit output control information is to power time delay distribution collection unit;
Wherein:
The control information that receiving management unit, power time delay distribution collection unit is sent, according to these control informations, power time delay distribution collection unit is from the baseband signal that is received, gather one group of environmental data extraction unit desired power time delay distribution data, this group power time delay distributed data is delivered to the environmental data extraction unit after the pre-service of power time delay distribution pretreatment unit; The environmental data extraction unit is delivered to administrative unit with this environmental data after extracting environmental data; Administrative unit is carried out overall treatment to environmental data, simultaneously power time delay distribution collection unit is controlled.
2, the device that obtains environmental data according to claim 1 is characterized in that, described power time delay distribution collection unit is made of correlator bank or matched filter banks.
3, the device that obtains environmental data according to claim 1 is characterized in that, described power time delay distribution pretreatment unit is made up of ground unrest extraction unit, footpath detection threshold determining unit and footpath decision unit.
4, the device that obtains environmental data according to claim 1, it is characterized in that described environmental data extraction unit is made up of difference power estimation unit and estimation of distribution parameters unit between Motion Recognition parameter estimation unit, sample coefficient of dispersion estimation unit, footpath; Difference power estimation unit and estimation of distribution parameters unit receive respectively from position, amplitude or the power data in the last footpath of power time delay distribution that power time delay distribution pretreatment unit is sent here between Motion Recognition parameter estimation unit, sample coefficient of dispersion estimation unit, footpath; The estimation of distribution parameters unit also receives power time delay distributed data and the detection threshold of sending here from the power time delay distribution pretreatment unit footpath or scatterer simultaneously, and each estimation unit outputs to administrative unit to difference power and distribution parameter between the Motion Recognition parameter of estimating to obtain, sample coefficient of dispersion, footpath.
5, the device that obtains environmental data according to claim 1, it is characterized in that described administrative unit is made up of NLOS estimation of error unit, NLOS recognition unit under NLOS estimation of error unit, the TDOA pattern under environmental data collecting control module, the TOA pattern; The location mode signal that described environmental data collecting control module issues according to the mobile position estimation center, location estimation mode signal and service quality signal output control information be to power time delay distribution collection unit, exports control information NLOS estimation of error unit under NLOS estimation of error unit or the TDOA pattern under the TOA pattern simultaneously; Under the described TOA pattern under NLOS estimation of error unit or the TDOA pattern NLOS estimation of error unit also receive distribution parameter simultaneously by environmental data extraction unit output, and obtain the average and the variance of NLOS error under the average of NLOS error under the TOA pattern and variance or the TDOA pattern; NLOS recognition unit in this administrative unit receives from difference power and sample coefficient of dispersion between the Motion Recognition parameter of environmental data extraction unit output, footpath respectively and carries out overall treatment, obtains the NLOS recognition result.
6, a kind of method of environmental data collecting is characterized in that, may further comprise the steps:
A, according to the station-keeping mode that mobile position estimation adopts, determine the signal kinds that environmental data collecting need be imported;
B, from the baseband signal of cellular mobile station receiver output, perhaps from the baseband signal of GPS receiver output, perhaps simultaneously from these two kinds of baseband signals, gather one group of power time delay distributed data according to control information;
C, the described power time delay distributed data of step b carried out ground unrest extracts, the footpath detection threshold is determined and the footpath judgement, finish environmental data and extract needed pre-service;
D, utilize the result who obtains in the described preprocessing process of step c, from the power time delay distributed data, extract environmental data according to station-keeping mode and location estimation pattern;
E, environmental data that steps d is extracted is carried out overall treatment.
7, method according to claim 6 is characterized in that, the station-keeping mode that described mobile position estimation adopts comprises: 1) based on the station-keeping mode of cellular network; 2) based on the station-keeping mode of A-GPS; 3) comprehensive utilization cellular network signals and gps signal carry out the station-keeping mode that time delay is estimated.
8, according to claim 6 or 7 described methods, it is characterized in that, the described station-keeping mode that adopts according to mobile position estimation is determined the signal kinds of environmental data collecting needs input, be meant:, then only the pilot signal of Cellular Networks is carried out the Multipath searching acquisition process if based on the location of cellular network; If the location that comprehensive utilization cellular network signals and gps signal carry out the time delay estimation, then need simultaneously the pilot signal and the gps signal of Cellular Networks are carried out acquisition process.
9, method according to claim 7 is characterized in that, for the station-keeping mode based on cellular network, adopts and carries out location estimation based on the TDOA pattern; For station-keeping mode, then adopt based on the TOA pattern and carry out location estimation based on A-GPS; Station-keeping mode for comprehensive utilization cellular network signals and gps signal then adopts simultaneously based on TOA pattern and TDOA pattern and carries out location estimation.
10, method according to claim 6, it is characterized in that, step b comprises that also alignment quality as requested determines corresponding control information, and this control information comprises: the frequency acquisition that need gather number that the number of the pseudo-random code that its power time delay distributes, same a kind of power time delay that needs are gathered distribute simultaneously, various power time delay is distributed and coherent length and the noncoherent accumulation number of times of gathering power time delay employing when distributing.
11, method according to claim 6 is characterized in that, the described power time delay distribution that step b is obtained is carried out pre-service and comprised three sub-steps:
C1, extraction ground unrest NP;
The detection threshold THR in c2, definite footpath;
C3, determine the amplitude or the power of first path position, first footpath amplitude or power, most powerful path position, most powerful path power or amplitude, local most powerful path position, local most powerful path.
12, method according to claim 6 is characterized in that, the described extraction environmental data of steps d comprises that Motion Recognition calculation of parameter substep, sample coefficient of dispersion calculate difference power calculating substep and estimation of distribution parameters substep between substep, footpath; Wherein:
The method of d1, Motion Recognition calculation of parameter is:
The first step, position, amplitude or the power information in the footpath that N power time delay of certain pseudo-random code correspondence of obtaining according to power time delay distribution preprocessing process distributes are selected a footpath that is used for Motion Recognition in certain interval after the head footpath;
In second step, calculate the amplitude or the power sample coefficient of dispersion in N the NLOS footpath of from N power time delay distributes, picking out;
The 3rd step compared the second sample coefficient of dispersion that obtain of step with the decision threshold THR-MOVE that obtains from empirical data, move if the sample coefficient of dispersion, just is judged to transfer table greater than THR-MOVE, otherwise it is static to be judged to transfer table;
D2, sample coefficient of dispersion computing method are, position, amplitude or the power information in the footpath that N power time delay of certain pseudo-random code correspondence of obtaining according to power time delay distribution preprocessing process distributes, from N power time delay distributes, pick out N the amplitude or the performance number in footpath unexpectedly the strongest, the amplitude or the performance number in this N footpath unexpectedly the strongest are calculated the sample coefficient of dispersion;
The computing method that difference power calculates between d3, footpath are, position, amplitude or the power information in the footpath of N power time delay distribution of certain pseudo-random code correspondence of obtaining according to power time delay distribution preprocessing process are done following processing:
1) each during N power time delay distributed is selected the amplitude or the power of the strongest footpath unexpectedly and local most powerful path, ratio calculated;
2) each during N power time delay distributed is calculated the difference of the time of arrival of time of arrival in first footpath and most powerful path;
D4, NLOS error profile parameter estimation are divided into the estimation of the distribution parameter of the estimation of distribution parameter of discrete form and conitnuous forms.
13, method according to claim 6 is characterized in that, the described location estimation pattern of steps d adopts carries out location estimation at the mobile position estimation center, then extracts the estimation that environmental data comprises NLOS error profile parameter.
14, method according to claim 9, it is characterized in that the overall treatment of the environmental data of described step e comprises the estimator step e12 and the NLOS recognin step e13 of NLOS error mean and variance under the estimator step e11, TDOA pattern of NLOS error mean and variance under the TOA pattern:
Wherein:
E11, the probability density function that utilizes NLOS error under the TOA pattern and distribution parameter carry out the estimation of NLOS error mean and variance;
E12, the probability density function that utilizes NLOS error under the TDOA pattern and distribution parameter carry out the estimation of NLOS error mean and variance;
Difference power carries out comprehensively obtaining the NLOS recognition result between e13, the Motion Recognition parameter by steps d is obtained, sample coefficient of dispersion, footpath.
15, method according to claim 14, it is characterized in that, the concrete grammar that carries out NLOS identification is: whether at first judge the Motion Recognition parameter greater than certain thresholding, if the Motion Recognition parameter, just shows that cellular mobile station or A-GPS are in the motion greater than certain thresholding, under the situation of this transfer table motion, determine according to the sample coefficient of dispersion whether the channel of corresponding pseudo-random code correspondence is the NLOS channel, greater than certain thresholding, is exactly the NLOS channel again, otherwise, be exactly the LOS channel; If cellular mobile station or A-GPS remain static, just adopt that difference power judges whether the channel into NLOS between sample footpath.
16, method according to claim 14 is characterized in that, adopts difference power between the sample footpath to judge whether for NLOS channel concrete grammar to be: whether the ratio K of 1) judging most powerful path in the power time delay distribution and local most powerful path is greater than certain thresholding; 2) whether the time delay spacing T of first footpath and most powerful path is less than certain thresholding;
If above-mentioned two conditions are set up simultaneously, just be judged to LOS, otherwise, be judged to NLOS.
According to claim 11 or 16 described methods, it is characterized in that 17, described local most powerful path is meant that certain position after most powerful path begins until the most powerful path that searches out in such interval, search window end.
18, method according to claim 17 is characterized in that, whether the time delay spacing T of described first footpath and most powerful path is meant that less than certain thresholding whether T is less than a chip width.
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