CN111856526A - Method, system and medium for identifying non-direct path satellite navigation signal - Google Patents

Method, system and medium for identifying non-direct path satellite navigation signal Download PDF

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CN111856526A
CN111856526A CN202010724432.2A CN202010724432A CN111856526A CN 111856526 A CN111856526 A CN 111856526A CN 202010724432 A CN202010724432 A CN 202010724432A CN 111856526 A CN111856526 A CN 111856526A
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nlos
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CN111856526B (en
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戴振东
王玉泽
文飞
刘佩林
应忍冬
刘强
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Shanghai Jiaotong University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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Abstract

The invention provides a method, a system and a medium for identifying a non-direct path satellite navigation signal, which comprise the following steps: step S1: the sample data processing unit (111) receives the acquired sample data, records the sample data as acquired signal data, judges LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value, and acquires a multipath category judgment result; step S2: at each epoch time, the initialization unit (112) is responsible for receiving the satellite navigation signals to be detected, and obtaining input signal parameters of the initialization unit (112), including pseudo-range, integral Doppler and carrier-to-noise ratio parameter information of each satellite signal, which can be measured in a signal tracking loop. The method identifies the non-direct path satellite navigation signals based on the signal characteristic parameters, and avoids additional equipment cost by taking the signal intensity attenuation, the pseudo-range carrier difference change rate and the posterior probability distribution of the pseudo-range residual error as characteristics.

Description

Method, system and medium for identifying non-direct path satellite navigation signal
Technical Field
The invention relates to the field of satellite navigation, in particular to a method, a system and a medium for identifying a non-direct path satellite navigation signal. And more particularly to non-direct path satellite navigation signal identification algorithms based on signal characteristic parameters.
Background
The satellite navigation positioning technology is used as the current most cost-effective outdoor position information acquisition means and widely applied to the application fields of vehicle navigation, mobile phone positioning, land surveying and mapping, unmanned aerial vehicle flight and the like. In some fields with the most extensive audiences, such as a vehicle-mounted navigation system and a smartphone positioning system, the system is often applied to urban complex environments, so that navigation signals are easily influenced by various buildings, vegetation and the like in the surrounding environment, signal interference such as shielding, blocking, multipath and the like is generated, and the quality of received signals is reduced. In an urban canyon application scene, the influence of multipath interference on satellite navigation positioning accuracy is the most serious, and the multipath interference can cause distortion of a related waveform in a pseudo-random code tracking loop, so that the measurement accuracy of pseudo range is reduced.
Most multipath mitigation algorithms are mainly applicable to the situation that the antenna can receive direct path signals and multipath signals at the same time. Since a direct path signal is easily blocked and energy of a multipath signal is strong in an urban canyon scene, a situation that a positioning terminal can only receive and lock the multipath signal may occur, and such a situation is called as non-direct path signal interference. If the indirect path signal data is used in the algorithm, the positioning accuracy is reduced by dozens or even hundreds of meters, so that the indirect path signal identification algorithm can be used for improving the positioning accuracy in the urban environment.
In addition, the current high-precision non-direct path detection usually needs to rely on additional hardware equipment and additional equipment cost, and the non-direct path satellite navigation signal identification algorithm based on signal characteristic parameters is used for detecting the non-direct path through posterior probability distribution of the characteristic parameters such as signal intensity attenuation, pseudo-range carrier difference change rate, pseudo-range residual error and the like, and the algorithm process only depends on navigation signal characteristics. The method only needs to utilize standard signal observation quantity data, so that the method can be quickly applied to most navigation terminals.
In summary, the invention provides a non-direct path satellite navigation signal identification algorithm based on signal characteristic parameters, which has practical value.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method, a system and a medium for identifying a non-direct path satellite navigation signal.
The method for identifying the non-direct path satellite navigation signal provided by the invention comprises the following steps:
step S1: the sample data processing unit (111) receives the acquired sample data, records the sample data as acquired signal data, judges LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value, and acquires a multipath category judgment result;
step S2: at each epoch moment, the initialization unit (112) is responsible for receiving the navigation signal of the satellite to be detected, and obtaining the input signal parameters of the initialization unit (112), including the pseudo-range, integral Doppler and carrier-to-noise ratio parameter information of each satellite signal, which can be measured in the tracking loop of the signal;
step S3: the rough detection unit (113) preliminarily detects an LOS signal with higher reliability according to the input signal parameters of the initialization unit (112);
step S4: the distinguished LOS signal is input into a position resolving unit (114), Kalman filtering positioning resolving is realized by using the LOS signal, and a positioning result is output;
step S5: the fine detection unit (115) can calculate the pseudo-range residual value of each satellite by using the positioning result output by the position resolving unit (114), calculate the prior probability of the LOS signal and the NLOS signal and fit the probability density distribution of the pseudo-range residual of the LOS signal and the NLOS signal by using the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111), define a decision factor and judge the LOS signal and the NLOS signal;
step S6: if the LOS signal is selected from the result of the fine detection unit (115), the signal input position calculation unit (114) carries out positioning calculation again, the process is iterated until the LOS signal cannot be selected, and the currently obtained signal classification result and the positioning result are output as final results.
Preferably, the step S1:
the collected sample data:
the method comprises the steps that long-time satellite signal data are acquired under various direct path and non-direct path scenes through satellite signal receiving equipment;
and judging LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value:
according to the positioning result (x)r,tr,zr) Satellite position (x)s,ys,zs) And calculating a pseudo-range residual error delta rho by the pseudo-range Pr, wherein the method comprises the following steps:
Figure BDA0002601155270000021
whereinpMeasuring errors for each detectable pseudorange;
by actual measurement of Doppler fdSubtracting the nominal value
Figure BDA0002601155270000031
Obtaining the Doppler frequency error Δ fdThe calculation is as follows:
Figure BDA0002601155270000032
whereinpVarious common errors and local clock drift;
Figure BDA0002601155270000033
the calculation method of (2) is as follows:
Figure BDA0002601155270000034
wherein (v)x,vy,vz) In order to calibrate the speed values obtained by the apparatus,
Figure BDA0002601155270000035
as satellite velocity value, (I)x,Iy,Iz) Is the unit directional vector of the receiving antenna pointing at the satellite.
The method for judging LOS and NLOS signals in sample data comprises the following steps:
(1) the pseudo-range residual error value is more than 15 meters;
(2) the pseudorange residual value is between 10 and 15 meters, and the absolute value of the Doppler frequency error is greater than 10 Hz;
(3) the pseudorange residual value is between 5 and 10 meters, and the absolute value of the Doppler frequency error is greater than 20 Hz;
and if any one of the three judgment conditions is met, judging the current signal to be an NLOS signal, and otherwise, judging the current signal to be an LOS signal.
Preferably, the step S3:
calculating a corresponding threshold value according to the sample input signal;
and selecting a signal with signal carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate smaller than a threshold value as an LOS signal with higher reliability.
Preferably, the step 3:
firstly, the signal intensity attenuation and the pseudo-range carrier difference change rate are calculated according to the signal parameter information, and then the signal intensity attenuation threshold Att is determined according to the distribution probability of NLOS in the marked sample value input by the sample data processing unit (111)thresAnd pseudorange carrier difference rate of change threshold
Figure BDA0002601155270000036
The calculation method is as follows:
Figure BDA0002601155270000037
Figure BDA0002601155270000038
wherein, AttNLOSAnd
Figure BDA0002601155270000039
is a sample set of all carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate of NLOS signal, P (| AttNLOs≤AttthresI is AttNLOSThe attenuation of the carrier-to-noise ratio of the NLOS signal in the sample set is less than the threshold AttthresThe probability of (a) of (b) being,
Figure BDA00026011552700000310
is composed of
Figure BDA00026011552700000311
The pseudo-range carrier-difference change rate of the NLOS signal in the sample set is less than the threshold value
Figure BDA00026011552700000312
Probability of (P)thresIs a preset proportional probability value;
the discrimination method of the LOS signal with high reliability is as follows:
Figure BDA00026011552700000313
wherein, Att is the carrier-to-noise ratio attenuation of the signal to be distinguished,
Figure BDA00026011552700000314
the pseudo-range carrier difference change rate of the signal to be distinguished is obtained.
Preferably, the step 5:
the probability density distribution of the pseudo-range residual error of the LOS signal and the NLOS signal is fitted through the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111) of the sample data processing unit (111), wherein the LOS signal meets zero-mean Gaussian distribution and the NLOS signal meets a class of specific distribution which are respectively expressed as
Figure BDA0002601155270000041
Figure BDA0002601155270000042
Wherein
Figure BDA0002601155270000043
Calculating the proportion P of NLOS signal and LOS signal in total sample through the output of the sample data processing unit (111)NAnd PLProbability P of conversion from LOS signal to NLOS signalL,NProbability P of conversion from NLOS signal to LOS signalN,LAnd probability P of NLOS and LOS signal state invarianceN,NAnd PL,L. The prior probability can be expressed as follows:
Figure BDA0002601155270000044
calculating a pseudo-range residual error according to a positioning result output by the position calculating unit (114), wherein the method for calculating the pseudo-range residual error is consistent with that in the sample data processing unit (111);
calculating a decision factor according to the probability density and the prior probability of the pseudo-range residual error, wherein the decision factor is expressed as
Figure BDA0002601155270000045
The discrimination of LOS and NLOS signals is as follows:
Figure BDA0002601155270000046
the invention provides a non-direct path satellite navigation signal identification system, which comprises:
module S1: the sample data processing unit (111) receives the acquired sample data, records the sample data as acquired signal data, judges LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value, and acquires a multipath category judgment result;
module S2: at each epoch moment, the initialization unit (112) is responsible for receiving the navigation signal of the satellite to be detected, and obtaining the input signal parameters of the initialization unit (112), including the pseudo-range, integral Doppler and carrier-to-noise ratio parameter information of each satellite signal, which can be measured in the tracking loop of the signal;
module S3: the rough detection unit (113) preliminarily detects an LOS signal with higher reliability according to the input signal parameters of the initialization unit (112);
module S4: the distinguished LOS signal is input into a position resolving unit (114), Kalman filtering positioning resolving is realized by using the LOS signal, and a positioning result is output;
module S5: the fine detection unit (115) can calculate the pseudo-range residual value of each satellite by using the positioning result output by the position resolving unit (114), calculate the prior probability of the LOS signal and the NLOS signal and fit the probability density distribution of the pseudo-range residual of the LOS signal and the NLOS signal by using the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111), define a decision factor and judge the LOS signal and the NLOS signal;
module S6: if the LOS signal is selected from the result of the fine detection unit (115), the signal input position calculation unit (114) carries out positioning calculation again, the process is iterated until the LOS signal cannot be selected, and the currently obtained signal classification result and the positioning result are output as final results.
Preferably, the module S1:
the collected sample data:
the method comprises the steps that long-time satellite signal data are acquired under various direct path and non-direct path scenes through satellite signal receiving equipment;
and judging LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value:
according to the positioning result (x)r,yr,zr) Satellite position (x)s,ys,zs) And calculating a pseudo-range residual error delta rho by the pseudo-range Pr, wherein the method comprises the following steps:
Figure BDA0002601155270000051
whereinpMeasuring errors for each detectable pseudorange;
by actual measurement of Doppler fdSubtracting the nominal value
Figure BDA0002601155270000052
Obtaining the Doppler frequency error Δ fdThe calculation is as follows:
Figure BDA0002601155270000053
whereinpVarious common errors and local clock drift;
Figure BDA0002601155270000054
the calculation method of (2) is as follows:
Figure BDA0002601155270000055
wherein (v)x,vy,vz) In order to calibrate the speed values obtained by the apparatus,
Figure BDA0002601155270000056
as satellite velocity value, (I)x,Iy,Iz) Is the unit directional vector of the receiving antenna pointing at the satellite.
The method for judging LOS and NLOS signals in sample data comprises the following steps:
(1) the pseudo-range residual error value is more than 15 meters;
(2) the pseudorange residual value is between 10 and 15 meters, and the absolute value of the Doppler frequency error is greater than 10 Hz;
(3) the pseudorange residual value is between 5 and 10 meters, and the absolute value of the Doppler frequency error is greater than 20 Hz;
and if any one of the three judgment conditions is met, judging the current signal to be an NLOS signal, and otherwise, judging the current signal to be an LOS signal.
Preferably, the module S3:
calculating a corresponding threshold value according to the sample input signal;
selecting a signal with signal carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate both smaller than a threshold value as an LOS signal with higher reliability;
the module 3 is:
firstly, the signal intensity attenuation and the pseudo-range carrier difference change rate are calculated according to the signal parameter information, and then the signal intensity attenuation threshold Att is determined according to the distribution probability of NLOS in the marked sample value input by the sample data processing unit (111)thresAnd pseudorange carrier difference rate of change threshold
Figure BDA0002601155270000061
The calculation method is as follows:
Figure BDA0002601155270000062
Figure BDA0002601155270000063
wherein, AttNLOSAnd
Figure BDA0002601155270000064
is a sample set of all carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate of NLOS signal, P (| AttNLOS≤AttthresI is AttNLOSThe attenuation of the carrier-to-noise ratio of the NLOS signal in the sample set is less than the threshold AttthresThe probability of (a) of (b) being,
Figure BDA0002601155270000065
is composed of
Figure BDA0002601155270000066
The pseudo-range carrier-difference change rate of the NLOS signal in the sample set is less than the threshold value
Figure BDA0002601155270000067
Probability of (P)thresIs a preset proportional probability value;
the discrimination method of the LOS signal with high reliability is as follows:
Figure BDA0002601155270000068
wherein, Att is the carrier-to-noise ratio attenuation of the signal to be distinguished,
Figure BDA0002601155270000069
the pseudo-range carrier difference change rate of the signal to be distinguished is obtained.
Preferably, the module 5:
the probability density distribution of the pseudo-range residual error of the LOS signal and the NLOS signal is fitted through the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111) of the sample data processing unit (111), wherein the LOS signal meets zero-mean Gaussian distribution and the NLOS signal meets a class of specific distribution which are respectively expressed as
Figure BDA00026011552700000610
Figure BDA00026011552700000611
Wherein
Figure BDA00026011552700000612
Calculating the proportion P of NLOS signal and LOS signal in total sample through the output of the sample data processing unit (111)NAnd PLProbability P of conversion from LOS signal to NLOS signalL,NProbability P of conversion from NLOS signal to LOS signalN,LAnd probability P of NLOS and LOS signal state invarianceN,NAnd PL,L. The prior probability can be expressed as follows:
Figure BDA0002601155270000071
calculating a pseudo-range residual error according to a positioning result output by the position calculating unit (114), wherein the method for calculating the pseudo-range residual error is consistent with that in the sample data processing unit (111);
calculating a decision factor according to the probability density and the prior probability of the pseudo-range residual error, wherein the decision factor is expressed as
Figure BDA0002601155270000072
The discrimination of LOS and NLOS signals is as follows:
Figure BDA0002601155270000073
according to the present invention, there is provided a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the non-direct path satellite navigation signal identification method described in any one of the above.
Compared with the prior art, the invention has the following beneficial effects:
the method identifies the non-direct path satellite navigation signals based on the signal characteristic parameters, and avoids additional equipment cost by taking the signal intensity attenuation, the pseudo-range carrier difference change rate and the posterior probability distribution of the pseudo-range residual error as characteristics. In addition, because the statistical characteristics of the real collected data are utilized to construct the signal type judgment factor, the indirect path in the signal is gradually detected through multiple iterations, the higher precision can be achieved, and the problem of insufficient precision of the traditional method for identifying by utilizing the navigation signal parameters is solved.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a system block diagram of a non-direct path satellite navigation signal identification algorithm based on signal feature parameters in an alternative embodiment;
FIG. 2 is a functional block diagram of a sample data processing unit in an alternative embodiment;
FIG. 3 is a functional block diagram of a coarse detection unit in an alternative embodiment;
FIG. 4 is a functional block diagram of a fine detection unit in an alternative embodiment;
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
The method for identifying the non-direct path satellite navigation signal provided by the invention comprises the following steps:
step S1: the sample data processing unit (111) receives the acquired sample data, records the sample data as acquired signal data, judges LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value, and acquires a multipath category judgment result;
step S2: at each epoch moment, the initialization unit (112) is responsible for receiving the navigation signal of the satellite to be detected, and obtaining the input signal parameters of the initialization unit (112), including the pseudo-range, integral Doppler and carrier-to-noise ratio parameter information of each satellite signal, which can be measured in the tracking loop of the signal;
step S3: the rough detection unit (113) preliminarily detects an LOS signal with higher reliability according to the input signal parameters of the initialization unit (112);
step S4: the distinguished LOS signal is input into a position resolving unit (114), Kalman filtering positioning resolving is realized by using the LOS signal, and a positioning result is output;
step S5: the fine detection unit (115) can calculate the pseudo-range residual value of each satellite by using the positioning result output by the position resolving unit (114), calculate the prior probability of the LOS signal and the NLOS signal and fit the probability density distribution of the pseudo-range residual of the LOS signal and the NLOS signal by using the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111), define a decision factor and judge the LOS signal and the NLOS signal;
step S6: if the LOS signal is selected from the result of the fine detection unit (115), the signal input position calculation unit (114) carries out positioning calculation again, the process is iterated until the LOS signal cannot be selected, and the currently obtained signal classification result and the positioning result are output as final results.
Specifically, the step S1:
the collected sample data:
the method comprises the steps that long-time satellite signal data are acquired under various direct path and non-direct path scenes through satellite signal receiving equipment;
and judging LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value:
according to the positioning result (x)r,yr,zr) Satellite position (x)s,ys,zs) And calculating a pseudo-range residual error delta rho by the pseudo-range Pr, wherein the method comprises the following steps:
Figure BDA0002601155270000091
whereinpMeasuring errors for each detectable pseudorange;
by actual measurement of Doppler fdSubtracting the nominal value
Figure BDA0002601155270000092
Obtaining the Doppler frequency error Δ fdThe calculation is as follows:
Figure BDA0002601155270000093
whereinpVarious common errors and local clock drift;
Figure BDA0002601155270000094
is calculated byThe following were used:
Figure BDA0002601155270000095
wherein (v)x,vy,vz) In order to calibrate the speed values obtained by the apparatus,
Figure BDA0002601155270000096
as satellite velocity value, (I)x,Iy,Iz) Is the unit directional vector of the receiving antenna pointing at the satellite.
The method for judging LOS and NLOS signals in sample data comprises the following steps:
(1) the pseudo-range residual error value is more than 15 meters;
(2) the pseudorange residual value is between 10 and 15 meters, and the absolute value of the Doppler frequency error is greater than 10 Hz;
(3) the pseudorange residual value is between 5 and 10 meters, and the absolute value of the Doppler frequency error is greater than 20 Hz;
and if any one of the three judgment conditions is met, judging the current signal to be an NLOS signal, and otherwise, judging the current signal to be an LOS signal.
Specifically, the step S3:
calculating a corresponding threshold value according to the sample input signal;
and selecting a signal with signal carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate smaller than a threshold value as an LOS signal with higher reliability.
Specifically, the step 3:
firstly, the signal intensity attenuation and the pseudo-range carrier difference change rate are calculated according to the signal parameter information, and then the signal intensity attenuation threshold Att is determined according to the distribution probability of NLOS in the marked sample value input by the sample data processing unit (111)thresAnd pseudorange carrier difference rate of change threshold
Figure BDA0002601155270000097
The calculation method is as follows:
Figure BDA0002601155270000098
Figure BDA0002601155270000099
wherein, AttNLOSAnd
Figure BDA00026011552700000910
is a sample set of all carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate of NLOS signal, P (| AttNLOS≤AttthresI is AttNLOSThe attenuation of the carrier-to-noise ratio of the NLOS signal in the sample set is less than the threshold AttthresThe probability of (a) of (b) being,
Figure BDA00026011552700000911
is composed of
Figure BDA00026011552700000912
The pseudo-range carrier-difference change rate of the NLOS signal in the sample set is less than the threshold value
Figure BDA00026011552700000913
Probability of (P)thresIs a preset proportional probability value;
the discrimination method of the LOS signal with high reliability is as follows:
Figure BDA00026011552700000914
wherein, Att is the carrier-to-noise ratio attenuation of the signal to be distinguished,
Figure BDA00026011552700000915
the pseudo-range carrier difference change rate of the signal to be distinguished is obtained.
Specifically, the step 5:
the probability density distribution of the pseudo-range residual error of the LOS signal and the NLOS signal is fitted through the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111) of the sample data processing unit (111), wherein the LOS signal meets zero-mean Gaussian distribution and the NLOS signal meets a class of specific distribution which are respectively expressed as
Figure BDA0002601155270000101
Figure BDA0002601155270000102
Wherein
Figure BDA0002601155270000103
Calculating the proportion P of NLOS signal and LOS signal in total sample through the output of the sample data processing unit (111)NAnd PLProbability P of conversion from LOS signal to NLOS signalL,NProbability P of conversion from NLOS signal to LOS signalN,LAnd probability P of NLOS and LOS signal state invarianceN,NAnd PL,L. The prior probability can be expressed as follows:
Figure BDA0002601155270000104
calculating a pseudo-range residual error according to a positioning result output by the position calculating unit (114), wherein the method for calculating the pseudo-range residual error is consistent with that in the sample data processing unit (111);
calculating a decision factor according to the probability density and the prior probability of the pseudo-range residual error, wherein the decision factor is expressed as
Figure BDA0002601155270000105
The discrimination of LOS and NLOS signals is as follows:
Figure BDA0002601155270000106
the invention provides a non-direct path satellite navigation signal identification system, which comprises:
module S1: the sample data processing unit (111) receives the acquired sample data, records the sample data as acquired signal data, judges LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value, and acquires a multipath category judgment result;
module S2: at each epoch moment, the initialization unit (112) is responsible for receiving the navigation signal of the satellite to be detected, and obtaining the input signal parameters of the initialization unit (112), including the pseudo-range, integral Doppler and carrier-to-noise ratio parameter information of each satellite signal, which can be measured in the tracking loop of the signal;
module S3: the rough detection unit (113) preliminarily detects an LOS signal with higher reliability according to the input signal parameters of the initialization unit (112);
module S4: the distinguished LOS signal is input into a position resolving unit (114), Kalman filtering positioning resolving is realized by using the LOS signal, and a positioning result is output;
module S5: the fine detection unit (115) can calculate the pseudo-range residual value of each satellite by using the positioning result output by the position resolving unit (114), calculate the prior probability of the LOS signal and the NLOS signal and fit the probability density distribution of the pseudo-range residual of the LOS signal and the NLOS signal by using the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111), define a decision factor and judge the LOS signal and the NLOS signal;
module S6: if the LOS signal is selected from the result of the fine detection unit (115), the signal input position calculation unit (114) carries out positioning calculation again, the process is iterated until the LOS signal cannot be selected, and the currently obtained signal classification result and the positioning result are output as final results.
Specifically, the module S1:
the collected sample data:
the method comprises the steps that long-time satellite signal data are acquired under various direct path and non-direct path scenes through satellite signal receiving equipment;
and judging LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value:
according to the positioning result (x)r,yr,zr) Satellite position (x)s,ys,zs) And calculating a pseudo-range residual error delta rho by the pseudo-range Pr, wherein the method comprises the following steps:
Figure BDA0002601155270000111
whereinpMeasuring errors for each detectable pseudorange;
by actual measurement of Doppler fdSubtracting the nominal value
Figure BDA0002601155270000112
Obtaining the Doppler frequency error Δ fdThe calculation is as follows:
Figure BDA0002601155270000113
whereinpVarious common errors and local clock drift;
Figure BDA0002601155270000114
the calculation method of (2) is as follows:
Figure BDA0002601155270000115
wherein (v)x,vy,vz) In order to calibrate the speed values obtained by the apparatus,
Figure BDA0002601155270000116
as satellite velocity value, (I)x,Iy,Iz) Is the unit directional vector of the receiving antenna pointing at the satellite.
The method for judging LOS and NLOS signals in sample data comprises the following steps:
(1) the pseudo-range residual error value is more than 15 meters;
(2) the pseudorange residual value is between 10 and 15 meters, and the absolute value of the Doppler frequency error is greater than 10 Hz;
(3) the pseudorange residual value is between 5 and 10 meters, and the absolute value of the Doppler frequency error is greater than 20 Hz;
and if any one of the three judgment conditions is met, judging the current signal to be an NLOS signal, and otherwise, judging the current signal to be an LOS signal.
Specifically, the module S3:
calculating a corresponding threshold value according to the sample input signal;
selecting a signal with signal carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate both smaller than a threshold value as an LOS signal with higher reliability;
the module 3 is:
firstly, the signal intensity attenuation and the pseudo-range carrier difference change rate are calculated according to the signal parameter information, and then the signal intensity attenuation threshold Att is determined according to the distribution probability of NLOS in the marked sample value input by the sample data processing unit (111)thresAnd pseudorange carrier difference rate of change threshold
Figure BDA0002601155270000121
The calculation method is as follows:
Figure BDA0002601155270000122
Figure BDA0002601155270000123
wherein, AttNLOsAnd
Figure BDA0002601155270000124
is a sample set of all carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate of NLOS signal, P (| AttNLoS≤AttthresI is AttNLOSThe attenuation of the carrier-to-noise ratio of the NLOS signal in the sample set is less than the threshold AttthresThe probability of (a) of (b) being,
Figure BDA0002601155270000125
is composed of
Figure BDA0002601155270000126
The pseudo-range carrier-difference change rate of the NLOS signal in the sample set is less than the threshold value
Figure BDA0002601155270000127
Probability of (P)thresIs a preset proportional probability value;
the discrimination method of the LOS signal with high reliability is as follows:
Figure BDA0002601155270000128
wherein, Att is the carrier-to-noise ratio attenuation of the signal to be distinguished,
Figure BDA0002601155270000129
the pseudo-range carrier difference change rate of the signal to be distinguished is obtained.
Specifically, the module 5:
the probability density distribution of the pseudo-range residual error of the LOS signal and the NLOS signal is fitted through the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111) of the sample data processing unit (111), wherein the LOS signal meets zero-mean Gaussian distribution and the NLOS signal meets a class of specific distribution which are respectively expressed as
Figure BDA00026011552700001210
Figure BDA00026011552700001211
Wherein
Figure BDA00026011552700001212
Calculating the proportion P of NLOS signal and LOS signal in total sample through the output of the sample data processing unit (111)NAnd PLProbability P of conversion from LOS signal to NLOS signalL,NConversion from NLOS signal toProbability of LOS signal PN,LAnd probability P of NLOS and LOS signal state invarianceN,NAnd PL,L. The prior probability can be expressed as follows:
Figure BDA0002601155270000131
calculating a pseudo-range residual error according to a positioning result output by the position calculating unit (114), wherein the method for calculating the pseudo-range residual error is consistent with that in the sample data processing unit (111);
calculating a decision factor according to the probability density and the prior probability of the pseudo-range residual error, wherein the decision factor is expressed as
Figure BDA0002601155270000132
The discrimination of LOS and NLOS signals is as follows:
Figure BDA0002601155270000133
according to the present invention, there is provided a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the non-direct path satellite navigation signal identification method described in any one of the above.
The present invention will be described more specifically below with reference to preferred examples.
Preferred example 1:
the invention aims to provide a non-direct path satellite navigation signal identification algorithm based on signal characteristic parameters. Aiming at the problem that extra cost is needed for high-precision indirect path identification at present, a non-direct path detection algorithm based on navigation signal characteristics is innovatively adopted, the method is divided into a coarse detection process and a fine detection process, and a signal type decision factor is constructed through LOS and NLOS signal statistical characteristics of real acquired data, so that the non-direct path in a received signal is gradually detected through multiple iterations, and the problem of positioning precision in an urban canyon environment is solved.
The invention provides a non-direct path satellite navigation signal identification algorithm based on signal characteristic parameters, which is characterized by comprising the following steps:
s1: the sample data processing unit (111) is responsible for receiving the acquired sample data and judging LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value.
S2: at each epoch moment, the initialization unit (112) is responsible for receiving the satellite navigation signals to be detected, and obtaining parameter information such as pseudo-range, integral Doppler and carrier-to-noise ratio of each satellite signal, which can be measured in a signal tracking loop.
The satellite navigation signal to be detected is a signal at a certain moment acquired by the satellite receiver in real time in the actual positioning process, and the input sample signal in S1 is a large amount of signal data collected in various scenes in advance and in a long time. The main objective of the present patent is to extract corresponding characteristic features from the large amount of signal data (i.e. the fitting probability distribution in step S5, calculating decision factors), so as to determine whether the real-time input signals are direct path signals (i.e. mainly embodied as the determination mode in step S5)
S3: a coarse detection unit (113) preliminarily detects an LOS signal with high reliability according to the input signal parameters of the initialization unit (112). Firstly, the signal intensity attenuation and the pseudo-range carrier difference change rate are calculated according to the signal parameter information, and then the signal intensity attenuation threshold Att is determined according to the distribution probability of NLOS in the marked sample value input by the sample data processing unit (111)thresAnd pseudorange carrier difference rate of change threshold
Figure BDA0002601155270000141
The calculation method is as follows
Figure BDA0002601155270000142
Figure BDA0002601155270000143
Wherein AttNLOSAnd
Figure BDA0002601155270000144
is a sample set of all carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate of NLOS signal, P (| AttNLOS≤AttthresI is AttNLOSThe attenuation of the carrier-to-noise ratio of the NLOS signal in the sample set is less than the threshold AttthresThe probability of (a) of (b) being,
Figure BDA0002601155270000145
is composed of
Figure BDA0002601155270000146
The pseudo-range carrier-difference change rate of the NLOS signal in the sample set is less than the threshold value
Figure BDA0002601155270000147
Probability of (P)thresThe predetermined proportional probability value is generally about 0.1. The discrimination method of the LOS signal with high reliability is as follows
Figure BDA0002601155270000148
Wherein, Att is the carrier-to-noise ratio attenuation of the signal to be distinguished,
Figure BDA0002601155270000149
rate of change of pseudo-range carrier difference for signal to be discriminated
S4: and inputting the distinguished LOS signal into a position resolving unit (114), and realizing Kalman filtering positioning resolution by using the LOS signal to output a positioning result.
S5: the fine detection unit (115) can calculate the pseudo-range residual value of each satellite by using the positioning result output by the position calculation unit (114), and can calculate the prior probability of the LOS signal and the NLOS signal and fit the probability density distribution of the pseudo-range residual value of the LOS signal and the NLOS signal by using the acquired signal data output by the sample data processing unit (111) and the multi-path type judgment result thereof. Defining a decision factor
Figure BDA00026011552700001410
Where f (Δ ρ | NLOS) and f (Δ ρ | LOS) are probability density distributions P of pseudorange residuals for NLOS and LOSNLOSAnd PLOSIs the prior probability of NLOS and LOS. The LOS and NLOS signals are distinguished by
Figure BDA00026011552700001411
Wherein class is the discrimination class
S6: if the LOS signal is selected from the result of the fine detection unit (115), the signal input position calculation unit (114) carries out positioning calculation again, the process is iterated until the LOS signal cannot be selected, and the currently obtained signal classification result and the positioning result are output as final results.
Fig. 1 shows an overall block diagram of the present invention, which mainly includes four parts: the device comprises a sample data processing unit (111), an initialization unit (112), a coarse detection unit (113), a position calculation unit (114) and a fine detection unit (115). The data input comes from the sample data processing unit and the initialization unit, each unit carries out certain processing on the data, and the fine detection unit comprises data output.
Fig. 2 shows details of the sample data processing unit (111) and its output. Wherein the pseudo-range residual calculation module calculates the pseudo-range residual according to the positioning result (x)r,yr,zr) Satellite position
Figure BDA0002601155270000151
And calculating a pseudo-range residual error delta rho from the pseudo-range Pr by the following method
Figure BDA0002601155270000152
WhereinpThe error is measured for each detectable pseudorange.
By actual Doppler measurement f in a "Doppler frequency error calculation" moduledSubtracting the nominal value
Figure BDA0002601155270000153
Obtaining the Doppler frequency error Δ fdIs calculated as follows
Figure BDA0002601155270000154
WhereinpThe method is characterized by comprising the steps of detecting various common errors and local clock drift.
Figure BDA0002601155270000157
Is calculated as follows
Figure BDA0002601155270000155
Wherein (v)x,vy,vz) In order to calibrate the speed values obtained by the apparatus,
Figure BDA0002601155270000156
as satellite velocity value, (I)x,Iy,Iz) Is the unit directional vector of the receiving antenna pointing at the satellite.
In the 'signal type discrimination' module, the signal type is discriminated by using the pseudo-range residual error and the doppler frequency error output by the 'pseudo-range residual error calculation' module and the 'doppler frequency error calculation' module as input, and the method is as follows:
(1) the pseudo-range residual error value is more than 15 meters;
(2) the pseudorange residual value is between 10 and 15 meters, and the absolute value of the Doppler frequency error is greater than 10 Hz;
(3) the pseudorange residual value is between 5 and 10 meters, and the absolute value of the Doppler frequency error is greater than 20 Hz;
and if any one of the three judgment conditions is met, judging the current signal to be an NLOS signal, and otherwise, judging the current signal to be an LOS signal.
The final output of the sample data processing unit (111) comprises the discrimination result of the signal and the characteristic information of the signal.
Fig. 3 shows the real-time details and output of the coarse detection unit (113). The threshold calculation module calculates corresponding threshold values according to the sample input signals. In the 'rough detection discrimination' module, a signal of which the signal carrier-to-noise ratio attenuation and the pseudo-range carrier difference change rate are both smaller than a threshold value is selected as an LOS signal with higher reliability.
Fig. 4 shows specific real-time details and outputs of the fine detection unit (115). The probability density function fitting module respectively fits probability density distribution of LOS signal and NLOS signal pseudo-range residual error through output signal characteristics and classification results of the sample data processing unit (111), wherein the LOS signal meets zero-mean Gaussian distribution, the NLOS signal meets a class of specific distribution, and the LOS signal and the NLOS signal are respectively expressed as
Figure BDA0002601155270000161
Figure BDA0002601155270000162
Wherein
Figure BDA0002601155270000163
The prior probability calculation module calculates the proportion P of NLOS signals and LOS signals in total samples through the output of the sample data processing unit (111)NAnd PLProbability P of conversion from LOS signal to NLOS signalL,NProbability P of conversion from NLOS signal to LOS signalN,LAnd probability P of NLOS and LOS signal state invarianceN,NAnd PL,L。
The prior probability can be expressed as follows
Figure BDA0002601155270000164
A pseudo-range residual calculation module calculates a pseudo-range residual according to the positioning result output by the position calculation unit (114), and the method is consistent with that in the sample data processing unit (111).
The decision factor calculation module calculates a decision factor according to the probability density and the prior probability of the pseudo-range residual error, and the decision factor is expressed as
Figure BDA0002601155270000165
And in the 'fine detection discrimination' module according to the following decision mode
Figure BDA0002601155270000166
And (6) judging.
Preferred example 2:
s1: the sample data processing unit (111) is responsible for receiving the acquired sample data and judging LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value.
S2: at each epoch moment, the initialization unit (112) is responsible for receiving the satellite navigation signals to be detected, and obtaining parameter information such as pseudo-range, integral Doppler and carrier-to-noise ratio of each satellite signal, which can be measured in a signal tracking loop.
S3: a coarse detection unit (113) preliminarily detects an LOS signal with high reliability according to the input signal parameters of the initialization unit (112). Firstly, the signal intensity attenuation and the pseudo-range carrier difference change rate are calculated according to the signal parameter information, and then the signal intensity attenuation threshold Att is determined according to the distribution probability of NLOS in the marked sample value input by the sample data processing unit (111)thresAnd pseudorange carrier difference rate of change threshold
Figure BDA0002601155270000167
The calculation method is as follows
Figure BDA0002601155270000168
Figure BDA0002601155270000169
Wherein AttNLOSAnd
Figure BDA0002601155270000171
all carrier-to-noise ratio attenuation and pseudorange-to-carrier difference rate sample sets, P, for NLOS signalsthresThe predetermined proportional probability value is generally about 0.1. The discrimination method of the LOS signal with high reliability is as follows
Figure BDA0002601155270000172
S4: and inputting the distinguished LOS signal into a position calculating unit (114), and realizing Kalman filtering positioning calculation by using the LOS signal.
S5: the fine detection unit (115) can calculate the pseudo-range residual value of each satellite by using the positioning result output by the position calculation unit (114), and can calculate the prior probability of the LOS signal and the NLOS signal and fit the probability density distribution of the pseudo-range residual value of the LOS signal and the NLOS signal by using the acquired signal data output by the sample data processing unit (111) and the multi-path type judgment result thereof. Defining a decision factor
Figure BDA0002601155270000173
Where f (Δ ρ | NLOS) and f (Δ ρ | LOS) are probability density distributions P of pseudorange residuals for NLOS and LOSNLOSAnd PLOSIs the prior probability of NLOS and LOS. The LOS and NLOS signals are distinguished by
Figure BDA0002601155270000174
Wherein class is the discrimination class
S6: if the LOS signal is selected from the result of the fine detection unit (115), the signal input position calculation unit (114) carries out positioning calculation again, the process is iterated until the LOS signal cannot be selected, and the currently obtained signal classification result and the positioning result are output as final results.
In the description of the present application, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience in describing the present application and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present application.
Those skilled in the art will appreciate that, in addition to implementing the systems, apparatus, and various modules thereof provided by the present invention in purely computer readable program code, the same procedures can be implemented entirely by logically programming method steps such that the systems, apparatus, and various modules thereof are provided in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system, the device and the modules thereof provided by the present invention can be considered as a hardware component, and the modules included in the system, the device and the modules thereof for implementing various programs can also be considered as structures in the hardware component; modules for performing various functions may also be considered to be both software programs for performing the methods and structures within hardware components.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.

Claims (10)

1. A method for identifying a non-direct path satellite navigation signal, comprising:
step S1: the sample data processing unit (111) receives the acquired sample data, records the sample data as acquired signal data, judges LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value, and acquires a multipath category judgment result;
step S2: at each epoch moment, the initialization unit (112) is responsible for receiving the navigation signal of the satellite to be detected, and obtaining the input signal parameters of the initialization unit (112), including the pseudo-range, integral Doppler and carrier-to-noise ratio parameter information of each satellite signal, which can be measured in the tracking loop of the signal;
step S3: the rough detection unit (113) preliminarily detects an LOS signal with higher reliability according to the input signal parameters of the initialization unit (112);
step S4: the distinguished LOS signal is input into a position resolving unit (114), Kalman filtering positioning resolving is realized by using the LOS signal, and a positioning result is output;
step S5: the fine detection unit (115) can calculate the pseudo-range residual value of each satellite by using the positioning result output by the position resolving unit (114), calculate the prior probability of the LOS signal and the NLOS signal and fit the probability density distribution of the pseudo-range residual of the LOS signal and the NLOS signal by using the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111), define a decision factor and judge the LOS signal and the NLOS signal;
step S6: if the LOS signal is selected from the result of the fine detection unit (115), the signal input position calculation unit (114) carries out positioning calculation again, the process is iterated until the LOS signal cannot be selected, and the currently obtained signal classification result and the positioning result are output as final results.
2. The method for identifying non-direct path satellite navigation signals according to claim 1, wherein the step S1:
the collected sample data:
the method comprises the steps that long-time satellite signal data are acquired under various direct path and non-direct path scenes through satellite signal receiving equipment;
and judging LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value:
according to the positioning result (x)r，yr，zr) Satellite position (x)s，ys，zs) And calculating pseudorange residual Δ from pseudorange PrρThe method comprises the following steps:
Figure FDA0002601155260000021
whereinpMeasuring errors for each detectable pseudorange;
by actual measurement of Doppler fdSubtracting the nominal value
Figure FDA0002601155260000022
Obtaining the Doppler frequency error Δ fdThe calculation is as follows:
Figure FDA0002601155260000023
whereinpVarious common errors and local clock drift;
Figure FDA0002601155260000024
the calculation method of (2) is as follows:
Figure FDA0002601155260000025
wherein (v)x，vy，vz) In order to calibrate the speed values obtained by the apparatus,
Figure FDA0002601155260000026
as satellite velocity value, (I)x，Iy，Iz) Is the unit directional vector of the receiving antenna pointing at the satellite.
The method for judging LOS and NLOS signals in sample data comprises the following steps:
(1) the pseudo-range residual error value is more than 15 meters;
(2) the pseudorange residual value is between 10 and 15 meters, and the absolute value of the Doppler frequency error is greater than 10 Hz;
(3) the pseudorange residual value is between 5 and 10 meters, and the absolute value of the Doppler frequency error is greater than 20 Hz;
and if any one of the three judgment conditions is met, judging the current signal to be an NLOS signal, and otherwise, judging the current signal to be an LOS signal.
3. The method for identifying non-direct path satellite navigation signals according to claim 1, wherein the step S3:
calculating a corresponding threshold value according to the sample input signal;
and selecting a signal with signal carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate smaller than a threshold value as an LOS signal with higher reliability.
4. The method for identifying non-direct path satellite navigation signals according to claim 1, wherein the step 3:
firstly, the signal intensity attenuation and the pseudo-range carrier difference change rate are calculated according to the signal parameter information, and then the signal intensity attenuation threshold Att is determined according to the distribution probability of NLOS in the marked sample value input by the sample data processing unit (111)thresAnd pseudorange carrier difference rate of change threshold
Figure FDA0002601155260000027
The calculation method is as follows:
Attthres～P(|AttNLOS≤Attthres|)＝Pthres
Figure FDA0002601155260000028
wherein, AttNLOSAnd
Figure FDA0002601155260000029
is a sample set of all carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate of NLOS signal, P (| AttNLOS≤AttthresI) is AttNLOSCarrier-to-noise ratio attenuation of NLOS signal in sample setAt threshold value AttthresThe probability of (a) of (b) being,
Figure FDA00026011552600000210
is composed of
Figure FDA00026011552600000211
The pseudo-range carrier-difference change rate of the NLOS signal in the sample set is less than the threshold value
Figure FDA00026011552600000212
Probability of (P)thresIs a preset proportional probability value;
the discrimination method of the LOS signal with high reliability is as follows:
Figure FDA0002601155260000031
wherein, Att is the carrier-to-noise ratio attenuation of the signal to be distinguished,
Figure FDA0002601155260000038
the pseudo-range carrier difference change rate of the signal to be distinguished is obtained.
5. The method for non-direct path satellite navigation signal identification according to claim 1, wherein the step 5:
the probability density distribution of the pseudo-range residual error of the LOS signal and the NLOS signal is fitted through the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111) of the sample data processing unit (111), wherein the LOS signal meets zero-mean Gaussian distribution and the NLOS signal meets a class of specific distribution which are respectively expressed as
Figure FDA0002601155260000032
Figure FDA0002601155260000033
Wherein
Figure FDA0002601155260000034
Calculating the proportion P of NLOS signal and LOS signal in total sample through the output of the sample data processing unit (111)NAnd PLProbability P of conversion from LOS signal to NLOS signalL，NProbability P of conversion from NLOS signal to LOS signalN，LAnd probability P of NLOS and LOS signal state invarianceN，NAnd PL，L. The prior probability can be expressed as follows:
Figure FDA0002601155260000035
calculating a pseudo-range residual error according to a positioning result output by the position calculating unit (114), wherein the method for calculating the pseudo-range residual error is consistent with that in the sample data processing unit (111);
calculating a decision factor according to the probability density and the prior probability of the pseudo-range residual error, wherein the decision factor is expressed as
Figure FDA0002601155260000036
The discrimination of LOS and NLOS signals is as follows:
Figure FDA0002601155260000037
。
6. a system for identifying non-direct path satellite navigation signals, comprising:
module S1: the sample data processing unit (111) receives the acquired sample data, records the sample data as acquired signal data, judges LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value, and acquires a multipath category judgment result;
module S2: at each epoch moment, the initialization unit (112) is responsible for receiving the navigation signal of the satellite to be detected, and obtaining the input signal parameters of the initialization unit (112), including the pseudo-range, integral Doppler and carrier-to-noise ratio parameter information of each satellite signal, which can be measured in the tracking loop of the signal;
module S3: the rough detection unit (113) preliminarily detects an LOS signal with higher reliability according to the input signal parameters of the initialization unit (112);
module S4: the distinguished LOS signal is input into a position resolving unit (114), Kalman filtering positioning resolving is realized by using the LOS signal, and a positioning result is output;
module S5: the fine detection unit (115) can calculate the pseudo-range residual value of each satellite by using the positioning result output by the position resolving unit (114), calculate the prior probability of the LOS signal and the NLOS signal and fit the probability density distribution of the pseudo-range residual of the LOS signal and the NLOS signal by using the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111), define a decision factor and judge the LOS signal and the NLOS signal;
module S6: if the LOS signal is selected from the result of the fine detection unit (115), the signal input position calculation unit (114) carries out positioning calculation again, the process is iterated until the LOS signal cannot be selected, and the currently obtained signal classification result and the positioning result are output as final results.
7. The non-direct path satellite navigation signal identification system of claim 6, wherein the module S1:
the collected sample data:
the method comprises the steps that long-time satellite signal data are acquired under various direct path and non-direct path scenes through satellite signal receiving equipment;
and judging LOS and NLOS signals in the sample data according to the pseudo-range residual value and the Doppler error absolute value:
according to the positioning result (x)r，yr，zr) Satellite position (x)s，ys，zs) To be provided withAnd calculating pseudo-range residual error delta from pseudo-range PrρThe method comprises the following steps:
Figure FDA0002601155260000041
whereinpMeasuring errors for each detectable pseudorange;
by actual measurement of Doppler fdSubtracting the nominal value
Figure FDA0002601155260000042
Obtaining the Doppler frequency error Δ fdThe calculation is as follows:
Figure FDA0002601155260000043
whereinpVarious common errors and local clock drift;
Figure FDA0002601155260000044
the calculation method of (2) is as follows:
Figure FDA0002601155260000045
wherein (v)x，vy，vz) In order to calibrate the speed values obtained by the apparatus,
Figure FDA0002601155260000046
as satellite velocity value, (I)x，Iy，Iz) Is the unit directional vector of the receiving antenna pointing at the satellite.
The method for judging LOS and NLOS signals in sample data comprises the following steps:
(1) the pseudo-range residual error value is more than 15 meters;
(2) the pseudorange residual value is between 10 and 15 meters, and the absolute value of the Doppler frequency error is greater than 10 Hz;
(3) the pseudorange residual value is between 5 and 10 meters, and the absolute value of the Doppler frequency error is greater than 20 Hz;
and if any one of the three judgment conditions is met, judging the current signal to be an NLOS signal, and otherwise, judging the current signal to be an LOS signal.
8. The non-direct path satellite navigation signal identification system of claim 6, wherein the module S3:
calculating a corresponding threshold value according to the sample input signal;
selecting a signal with signal carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate both smaller than a threshold value as an LOS signal with higher reliability;
the module 3 is:
firstly, the signal intensity attenuation and the pseudo-range carrier difference change rate are calculated according to the signal parameter information, and then the signal intensity attenuation threshold Att is determined according to the distribution probability of NLOS in the marked sample value input by the sample data processing unit (111)thresAnd pseudorange carrier difference rate of change threshold
Figure FDA0002601155260000051
The calculation method is as follows:
Attthres～P(|AttNLOS≤Attthres|)＝Pthres
Figure FDA0002601155260000052
wherein, AttNLOSAnd
Figure FDA0002601155260000053
is a sample set of all carrier-to-noise ratio attenuation and pseudo-range carrier difference change rate of NLOS signal, P (| AttNLOS≤AttthresI) is AttNLOSThe attenuation of the carrier-to-noise ratio of the NLOS signal in the sample set is less than the threshold AttthresThe probability of (a) of (b) being,
Figure FDA0002601155260000054
is composed of
Figure FDA0002601155260000055
The pseudo-range carrier-difference change rate of the NLOS signal in the sample set is less than the threshold value
Figure FDA0002601155260000056
Probability of (P)thresIs a preset proportional probability value;
the discrimination method of the LOS signal with high reliability is as follows:
Figure FDA0002601155260000057
wherein, Att is the carrier-to-noise ratio attenuation of the signal to be distinguished,
Figure FDA0002601155260000058
the pseudo-range carrier difference change rate of the signal to be distinguished is obtained.
9. The non-direct path satellite navigation signal identification system of claim 6, wherein the module 5:
the probability density distribution of the pseudo-range residual error of the LOS signal and the NLOS signal is fitted through the acquired signal data and the multi-path type judgment result output by the sample data processing unit (111) of the sample data processing unit (111), wherein the LOS signal meets zero-mean Gaussian distribution and the NLOS signal meets a class of specific distribution which are respectively expressed as
Figure FDA0002601155260000061
Figure FDA0002601155260000062
Wherein
Figure FDA0002601155260000063
Calculating the proportion P of NLOS signal and LOS signal in total sample through the output of the sample data processing unit (111)NAnd PLProbability P of conversion from LOS signal to NLOS signalL，NProbability P of conversion from NLOS signal to LOS signalN，LAnd probability P of NLOS and LOS signal state invarianceN，NAnd PL，L. The prior probability can be expressed as follows:
Figure FDA0002601155260000064
calculating a pseudo-range residual error according to a positioning result output by the position calculating unit (114), wherein the method for calculating the pseudo-range residual error is consistent with that in the sample data processing unit (111);
calculating a decision factor according to the probability density and the prior probability of the pseudo-range residual error, wherein the decision factor is expressed as
Figure FDA0002601155260000065
The discrimination of LOS and NLOS signals is as follows:
Figure FDA0002601155260000066
。
10. a computer readable storage medium storing a computer program, wherein the computer program, when executed by a processor, performs the steps of the method for non-direct path satellite navigation signal identification of any one of claims 1 to 5.
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