CN109143274A - A kind of receiver positioning completeness monitoring method based on raw satellite navigation signal - Google Patents

A kind of receiver positioning completeness monitoring method based on raw satellite navigation signal Download PDF

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CN109143274A
CN109143274A CN201810852542.XA CN201810852542A CN109143274A CN 109143274 A CN109143274 A CN 109143274A CN 201810852542 A CN201810852542 A CN 201810852542A CN 109143274 A CN109143274 A CN 109143274A
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signal
satellite navigation
covariance matrix
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pvt
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CN109143274B (en
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王尔申
杨迪
佟刚
曲萍萍
刘艳伟
王传云
庞涛
蓝晓宇
黄煜峰
徐嵩
邵清亮
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Shenyang Aerospace University
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13Receivers
    • G01S19/20Integrity monitoring, fault detection or fault isolation of space segment
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13Receivers
    • G01S19/23Testing, monitoring, correcting or calibrating of receiver elements

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Security & Cryptography (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

The invention discloses a kind of, and the receiver based on raw satellite navigation signal positions completeness monitoring method, wherein current signal shows first with raw satellite navigation signal;Then the Gaussian Profile centered on true delays is obeyed in the estimation delay of satellite navigation signals on each channel, and current signal is combined with filter bandwidht, constructs the asymptotic covariance matrix of the distribution;Then PVT (position, velocity, time, PVT) covariance matrix is derived, new test statistics is obtained;Finally carry out the detection and identification of satellite failure.This method can carry out satellite navigation receiver and position integrity monitoring under using raw satellite navigation signal, provide a kind of new method to promote receiver positioning integrity monitoring performance.

Description

Receiver positioning integrity monitoring method based on original satellite navigation signals
Technical Field
The invention relates to a method for monitoring the positioning integrity of a satellite navigation receiver of a signal, in particular to a method for monitoring the positioning integrity of the receiver based on an original satellite navigation signal.
Background
With the rapid development of GNSS (Global Navigation Satellite System), the problem of integrity monitoring of Satellite Navigation becomes more and more prominent, and the RAIM research on Satellite Navigation will continue to become a research hotspot in the field of autonomous flight Navigation. Aiming at the characteristics and new development and application directions of autonomous integrity monitoring of a user side, RAIM research of satellite navigation is further developed deeply, conversion of research results to actual application is promoted, and a scientific theoretical basis and a powerful technical support means are provided for aviation flight safety management and application.
Receiver Autonomous Integrity Monitoring (RAIM) is a technique for integrity monitoring at a satellite navigation receiver, particularly in aeronautical applications. In open and broad environments, the RAIM detects and eliminates pseudo-range errors, guarantees are provided for the safety of satellite navigation, and nearly optimal performance is achieved. To date, specific integrity monitoring methods have been substantially implemented, such as: (1) solution Separation Method (SSM), (2) Least Squares Residual (LSR) or Weighted Least Squares Residual (WLSR) methods: detection is carried out by utilizing residual sum of squares definition, (3) a parity vector method and (4) a distance comparison method, which are the most commonly used techniques in civil aviation. But these methods are based on pseudo-range redundancy observations. The existing RAIM does not consider the received original satellite navigation signals before the relevant processing steps, and is carried out based on pseudo-range observed quantity, and the original satellite navigation signals contain rich information which is not approximately processed, so that the method can be introduced into a satellite navigation receiver positioning integrity monitoring method, a method different from the existing receiver autonomous integrity monitoring technology based on pseudo-range observed quantity is established, the receiver positioning integrity monitoring performance is improved, and meanwhile, the method can be used as a supplement method of the traditional RAIM technology.
Disclosure of Invention
The technical task of the invention is to provide a receiver positioning integrity monitoring method based on original satellite navigation signals, aiming at the defects of the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows:
step one, calculating the current signal-to-noise ratio of the ith channel by using an original satellite navigation signal;
secondly, the estimated delay of the satellite navigation signal on each channel follows Gaussian distribution with real delay as the center, and the current signal-to-noise ratio is combined with the bandwidth of a filter to construct an asymptotic covariance matrix of the distribution;
thirdly, deriving to obtain a PVT covariance matrix, and further obtaining new test statistics by diagonal elements of the PVT covariance matrix;
and fourthly, detecting and identifying the satellite fault.
Further improvement: in the first step, the current signal-to-noise ratio of the ith channel is represented by using the original satellite navigation signal, and the specific process is as follows:
the satellite navigation baseband signal model is as follows:
wherein, αiRepresenting the complex amplitude of the ith satellite navigation signal, ai(theta) represents the transmitted uniform signal vector, N is zero-mean additive white Gaussian noise, and the obeyed distribution is N-N (0, delta)2)。
Wherein, ciRepresenting the i-th navigation signal transmitted by Pseudo-random noise (PRN), the PRN code mainly includes fine ranging code (P code) and coarse ranging code (C/a code), which implement Pseudo-code spreading of the navigation message, so as to further modulate to the L1 carrier frequency or the L2 carrier frequency by BPSK modulation, thereby forming the L1 signal or the L2 signal. The delay τ is calculated from the estimated PVTi(theta) and polyParameter f of Pulleri(θ),[t1,...,tN]A vector of time samples;
the signal-to-noise ratio SNR is the ratio between the desired signal power and the noise power:
the signal power of the ith channel can be represented according to a signal model:
Psig,i=E[(Aiαi)H(Aiαi)]=αi HAi HAiαi
the ith amplitude is an unknown parameter, and the linear signal model can be estimated using the least squares method:
thus, the signal power expression is:
Psig,i=xHAi(Ai HAi)-1Ai Hx=xHPix
noise power estimation is based on the same principle, using noise signal amplitude estimation:
Pnoise,i=||x-Aiαi||2
further, the noise power:
Pnoise,i=xHx-xHAi(Ai HAi)-1Ai Hx=xHQix
finally, the SNR expression can be expressed from the received signal as:
wherein,
where x represents the original navigation baseband signal,a vector representing the transmitted unified signal. Thus, the signal-to-noise ratio of the current channel can be obtained.
Further improvement: the estimated delay of the satellite navigation signal on each channel in the second step obeys Gaussian distribution with real delay as the center, the current signal-to-noise ratio is combined with the bandwidth of a filter, and the specific process of constructing the asymptotic covariance matrix of the distribution is as follows:
estimated delay of satellite navigation signal on ith channelObey the following distribution:
in the formula, B represents a filter bandwidth. Thus, the progressive covariance matrix of the delays can be expressed with the original satellite navigation signal as follows:
and the noise power at the ith channel is as follows:
each desired satellite navigation signal is buried in noise, and thus, the signal energy xHx>>Projection of the original signal onto the ith signal subspace, i.e.Therefore, the first and second electrodes are formed on the substrate,
thus, the progressive covariance matrix can be expressed as:
further improvement: and the third step deduces a PVT covariance matrix to obtain new test statistics, and the specific process is as follows:
when the delayed asymptotic covariance matrix is obtained, the PVT covariance matrix of a receiver positioning integrity monitoring method based on the original satellite navigation signals can be derived as follows:
wherein, CP=cCrAnd c denotes the speed of light, in which method only the diagonal elements of the PVT covariance matrix characterizing the three-dimensional position of the receiver are considered. Tong (Chinese character of 'tong')Often, the fourth dimension of the PVT covariance matrix, i.e., clock bias, is not considered. Therefore, three parameters are selected
The PVT standard deviation obtained by the method is as follows:
and new test statistics are constructed therefrom. Unlike the test statistic in the weighted least squares residual method, the test statistic of the weighted least squares residual method is obtained by the weighted sum of squared residuals (WSSE), i.e., composed of an error vector and a noise covariance matrix, and is expressed as:
where E represents an error vector (K × 1) following a gaussian distribution N (0, Σ); Σ denotes a noise covariance matrix (K × K), in which,
further improvement: detecting and identifying the fourth step satellite fault;
the threshold value is then determined by combining the expected false alarm probability with the new test statistic. When the threshold value is larger than the test statistic, no satellite fault is indicated; and when the threshold value is smaller than the test statistic, indicating that the satellite has a fault, and identifying the satellite fault.
The invention has the advantages that: 1. the existing receiver autonomous integrity monitoring method is realized based on pseudo-range measurement, the influence of an original navigation signal received by a receiver on integrity monitoring performance is not considered, and the method can utilize the original satellite navigation signal to realize the positioning integrity monitoring of the satellite navigation receiver; 2. under the condition of noise (such as weak multipath), the signal-to-noise ratio of the method changes, and then the change can be reflected in the PVT covariance and statistic, so that the method can detect the noise and even the fault which have small influence on the PVT, thereby sending alarm information to a user in time and improving the sensitivity of the integrity monitoring method.
Drawings
Fig. 1 is a schematic structural view of the present invention.
Detailed Description
The invention is described in detail below with reference to the drawings.
As shown in fig. 1, the following concepts and definitions are introduced first:
1. integrity: when the positioning result is unavailable, the system can send an alarm service to the user in time, so that the positioning error or navigation danger brought to the user by the wrong positioning result is avoided.
2. Detection of Failure (FD): judging the existence of the fault of the monitored system;
3. fault Isolation (FI): the method is used for identifying and eliminating the satellite faults.
The invention provides a method for monitoring the positioning integrity of a receiver based on an original satellite navigation signal, which comprises the following specific steps:
the method comprises the steps that firstly, the current signal-to-noise ratio of the ith channel is expressed by using an original satellite navigation signal;
the satellite navigation baseband signal model is as follows:
wherein, αiRepresenting the complex amplitude of the ith satellite navigation signal, ai(theta) represents the transmitted uniform signal vector, N is zero-mean additive white Gaussian noise, and the obeyed distribution is N-N (0, delta)2)。
Wherein, ciRepresenting the i-th navigation signal transmitted by Pseudo-random noise (PRN), the PRN code mainly includes fine ranging code (P code) and coarse ranging code (C/a code), which implement Pseudo-code spreading of the navigation message, so as to further modulate to the L1 carrier frequency or the L2 carrier frequency by BPSK modulation, thereby forming the L1 signal or the L2 signal. The delay τ is calculated from the estimated PVTi(theta) and Doppler parameter fi(θ),[t1,...,tN]A vector of time samples;
the signal-to-noise ratio SNR is the ratio between the desired signal power and the noise power:
the signal power of the ith channel can be represented according to a signal model:
Psig,i=E[(Aiαi)H(Aiαi)]=αi HAi HAiαi
the ith amplitude is an unknown parameter, and the linear signal model can be estimated using the least squares method:
thus, the signal power expression can be expressed as:
Psig,i=xHAi(Ai HAi)-1Ai Hx=xHPix
noise power estimation is based on the same principle, using noise signal amplitude estimation:
Pnoise,i=||x-Aiαi||2
further, the noise power:
Pnoise,i=xHx-xHAi(Ai HAi)-1Ai Hx=xHQix
finally, the SNR expression can be expressed from the received signal as:
wherein
Where x represents the original baseband signal and represents the vector of the transmitted unified signal.
Secondly, the estimated delay of the satellite navigation signal on each channel follows Gaussian distribution with real delay as the center, and the current signal-to-noise ratio is combined with the bandwidth of a filter to construct an asymptotic covariance matrix of the distribution;
the signal is at the ith signalEstimated delay on trackObey the following distribution:
in the formula, B represents a filter bandwidth. Thus, the progressive covariance matrix of the delays can be expressed with the original satellite navigation signal as follows:
and the noise power at the ith channel is as follows:
each desired satellite navigation signal is buried in noise, and thus, the signal energy xHx>>Projection of the original signal onto the ith signal subspace, i.e.Therefore, the first and second electrodes are formed on the substrate,
thus, the progressive covariance matrix can be expressed as:
thirdly, deducing a PVT covariance matrix to obtain new test statistics;
when the delayed asymptotic covariance matrix is obtained, the prior method PVT covariance matrix can be derived therefrom as:
wherein, CP=cCrAnd c denotes the speed of light, in which method only the diagonal elements of the PVT covariance matrix characterizing the three-dimensional position of the receiver are considered. Typically, the fourth dimension of the PVT covariance matrix, i.e., the clock bias, is not considered. Therefore, three parameters are selected
The PVT standard deviation obtained by the method is as follows:
and new test statistics are constructed therefrom. The test statistic for the weighted least squares residual method, which is different from the test statistic in the weighted least squares residual method, is obtained from the weighted sum squared residual (WSSE), i.e., composed of an error vector and a noise covariance matrix, and is represented as:
where E represents an error vector (K × 1) following a gaussian distribution N (0, Σ); Σ denotes a noise covariance matrix (K × K), in which,
and fourthly, detecting and identifying the satellite fault.
The threshold value is then determined by combining the expected false alarm probability with the new test statistic. When the threshold value is larger than the test statistic, no satellite fault is indicated; and when the threshold value is smaller than the test statistic, indicating that the satellite has a fault, and identifying the satellite fault.
The detailed algorithm flow chart is shown in fig. 1:
① calculates the current Signal-to-noise ratio (SNR) of the ith channel using the original satellite navigation Signal x.
② the estimated delay of satellite navigation signal on each channel is subject to Gaussian distribution with real delay as center, current SNR is combined with filter bandwidth B to construct asymptotic covariance matrix C of the distributionr
③ is formed by an asymptotic covariance matrix CrA PVT covariance matrix is derived.
④ then obtain new test statistics.
⑤ combined with expected false alarm probability value PfaCalculating a threshold value Tth
⑥ detect and identify satellite failures.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (5)

1. A receiver positioning integrity monitoring method based on original satellite navigation signals is characterized in that: comprises the following steps;
step one, calculating the current signal-to-noise ratio of the ith channel by using an original satellite navigation signal;
secondly, the estimated delay of the satellite navigation signal on each channel follows Gaussian distribution with real delay as the center, and the current signal-to-noise ratio is combined with the bandwidth of a filter to construct an asymptotic covariance matrix of the distribution;
thirdly, deducing a PVT covariance matrix, and further obtaining new test statistics by diagonal elements of the PVT covariance matrix;
and fourthly, detecting and identifying the satellite fault.
2. The method of claim 1, wherein the method further comprises the step of: in the first step, the current signal-to-noise ratio of the ith channel is calculated by using the original satellite navigation signal, and the specific process is as follows:
the satellite navigation baseband signal model is as follows:
wherein, αiRepresenting the complex amplitude of the ith satellite navigation signal, ai(theta) represents the transmitted uniform signal vector, N is zero-mean additive white Gaussian noise, and the obeyed distribution is N-N (0, delta)2);
Wherein, ciRepresenting the i-th navigation signal transmitted by Pseudo-random noise (PRN), the PRN code mainly includes fine ranging code (P code) and coarse ranging code (C/a code), which implement Pseudo-code spreading of the navigation message, so that the navigation message can be further modulated onto the L1 carrier frequency or the L2 carrier frequency by BPSK modulation, thereby forming the L1 signal or the L2 signal. The delay τ is calculated from the estimated PVTi(theta) and Doppler parameter fi(θ),[t1,...,tN]A vector of time samples;
the signal-to-noise ratio SNR is the ratio between the desired signal power and the noise power:
the signal power of the ith channel can be represented according to a signal model:
Psig,i=E[(Aiαi)H(Aiαi)]=αi HAi HAiαi
the ith amplitude is an unknown parameter, and the linear signal model can be estimated using the least squares method:
thus, the signal power expression can be expressed as:
Psig,i=xHAi(Ai HAi)-1Ai Hx=xHPix
noise power estimation is based on the same principle, using noise signal amplitude estimation:
Pnoise,i=||x-Aiαi||2
further, the noise power:
Pnoise,i=xHx-xHAi(Ai HAi)-1Ai Hx=xHQix
finally, the SNR expression can be expressed from the received signal as:
wherein,
where x represents the original navigation baseband signal,a vector representing the transmitted unified navigation signal, from which the signal-to-noise ratio of the current channel can be obtained.
3. The method of claim 1, wherein the method further comprises the step of: the estimated delay of the satellite navigation signal on each channel in the second step obeys Gaussian distribution with real delay as the center asymptotically, the current signal-to-noise ratio is combined with the bandwidth of a filter, and the specific process of constructing the asymptotic covariance matrix of the distribution comprises the following steps:
estimated delay of satellite navigation signal on ith channelObey the following distribution:
where B represents the filter bandwidth, and therefore the progressive covariance matrix of the delays can be represented by the original satellite navigation signal, as follows:
and the noise power at the ith channel is as follows:
each desired satellite navigation signal is buried in noise, and thus, the signal energy xHx>>Projection of the original satellite navigation signal onto the ith signal subspace, i.e.Therefore, the first and second electrodes are formed on the substrate,
thus, the progressive covariance matrix can be expressed as:
4. the method of claim 1, wherein the method further comprises the step of: and the third step of deducing a PVT covariance matrix to obtain new test statistics, wherein the specific process comprises the following steps:
when the delayed asymptotic covariance matrix is obtained, the PVT covariance matrix of a receiver positioning integrity monitoring method based on the original satellite navigation signals can be derived as follows:
wherein, CP=cCrAnd c denotes the speed of light, in which method only the diagonal elements of the PVT covariance matrix characterizing the three-dimensional position of the receiver are considered. Typically, the fourth dimension of the PVT covariance matrix, i.e., the clock bias, is not considered. Therefore, three parameters are selected
The PVT standard deviation obtained by the method is as follows:
and new test statistics are constructed therefrom. Unlike the test statistic in the weighted least squares residual method, the test statistic of the weighted least squares residual method is obtained by the weighted sum of squared residuals (WSSE), i.e., composed of an error vector and a noise covariance matrix, and is expressed as:
where E represents an error vector (K × 1) following a gaussian distribution N (0, Σ); Σ denotes a noise covariance matrix (K × K), in which,
5. the method of claim 1, wherein the method further comprises the step of: detection and identification of the fourth step satellite fault:
combining the false alarm probability required by the satellite navigation application with new test statistic to obtain a threshold value, and when the threshold value is greater than the test statistic, indicating that no satellite fault exists; and when the threshold value is smaller than the test statistic, indicating that the satellite fault exists, and identifying the satellite fault.
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