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

Abstract

The invention discloses a receiver positioning integrity monitoring method based on the original satellite navigation signal, wherein the original satellite navigation signal is used to first express the current signal-to-noise ratio; then the estimated delay of the satellite navigation signal on each channel obeys the real The delay-centered Gaussian distribution combines the current signal-to-noise ratio with the filter bandwidth to construct the asymptotic covariance matrix of the distribution; then derive the PVT (position, velocity, time, PVT) covariance matrix to obtain new test statistics Finally, the detection and identification of satellite faults are carried out. The method can monitor the positioning integrity of the satellite navigation receiver by using the original satellite navigation signal, and provides a new method for improving the monitoring performance of the receiver positioning integrity.

Description

A method for monitoring receiver positioning integrity based on raw satellite navigation signals

technical field

The invention relates to a signal-based satellite navigation receiver positioning integrity monitoring method, in particular to a receiver positioning integrity monitoring method based on an original satellite navigation signal.

Background technique

With the rapid development of GNSS (Global Navigation Satellite System, GNSS), the integrity monitoring of satellite navigation has become more and more prominent, and the research on satellite navigation RAIM will continue to be a research hotspot in the field of autonomous flight navigation. Aiming at the characteristics, new development and application direction of user-side autonomous integrity monitoring, further in-depth research on satellite navigation RAIM will be carried out to promote the transformation of research results into practical applications, and will provide a scientific theoretical basis and strong support for aviation flight safety management and application. technical support means.

Receiver Autonomous Integrity Monitoring (RAIM) is a technique for integrity monitoring at the receiver side of satellite navigation, especially in aviation applications. In an open and open environment, RAIM detects and eliminates pseudorange errors, guarantees the safety of satellite navigation, and achieves near-optimal performance. So far, specific integrity monitoring methods have been basically implemented, such as: (1) Solution separation method (SSM), (2) Least square residual (LSR) or weighted least squares Residual (Weighted Least Square Residue, WLSR) method: use the residual squared definition for detection, (3) parity vector method, (4) distance comparison method, which are the most commonly used techniques in civil aviation. But these methods are all based on pseudorange redundant observations. The existing RAIM does not consider the received original satellite navigation signals before the relevant processing steps, and is all based on pseudo-range observations, and the original satellite navigation signals contain rich information that has not been approximated. It can be introduced into the satellite navigation receiver positioning integrity monitoring method, and a method different from the existing receiver autonomous integrity monitoring technology based on pseudo-range observations can be established to improve the receiver positioning integrity monitoring performance. A complementary approach to traditional RAIM techniques.

SUMMARY OF THE INVENTION

The technical task of the present invention is to aim at the above deficiencies of the prior art, and further provide a method for monitoring the positioning integrity of a receiver based on an original satellite navigation signal.

The technical scheme adopted by the present invention to solve its technical problems is:

The first step is to use the original satellite navigation signal to calculate the current signal-to-noise ratio of the i-th channel;

In the second step, the estimated delay of the satellite navigation signal on each channel obeys a Gaussian distribution centered on the real delay, and the current signal-to-noise ratio is combined with the filter bandwidth to construct an asymptotic covariance matrix of the distribution;

The third step is to derive the PVT covariance matrix, and then obtain a new test statistic from its diagonal elements;

The fourth step is to detect and identify satellite faults.

Further improvement: the first step uses the original satellite navigation signal to express the current signal-to-noise ratio of the i-th channel, and the specific process is as follows:

The satellite navigation baseband signal model is:

Among them, α _i represents the complex amplitude of the ith satellite navigation signal, a _i (θ) represents the transmitted uniform signal vector, n is the additive white Gaussian noise with zero mean, and the distribution obeyed is n～N(0,δ ² ).

Among them, c _i represents the ith navigation signal transmitted by pseudo-random noise (Pseudo-random noise, PRN), and the PRN code mainly includes fine ranging code (P code) and coarse ranging code (C/A code), They realize the pseudo-code spread spectrum of the navigation message, so that it can be further modulated to the L1 carrier frequency or the L2 carrier frequency through the BPSK modulation method, thereby forming the L1 signal or the L2 signal. The delay τ _i (θ) and the Doppler parameter f _i (θ) can be calculated from the estimated PVT, and [t ₁ ,...,t _N ] is the vector of time samples;

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 expressed according to the signal model:

P _sig,i =E[(A _i α _i ) ^H (A _i α _i )]=α _i ^H A _i ^H A _i α _i

The ith magnitude is an unknown parameter, and the linear signal model can be estimated using the least squares method:

Therefore, the signal power expression is:

P _sig,i =x ^H A _i (A _i ^H A _i ) ^-1 A _i ^H x=x ^H P _i x

Noise power estimation is based on the same principle, using noise signal amplitude estimation:

P _noise,i =||xA _i α _i || ²

Then the noise power can be obtained:

P _noise,i =x ^H xx ^H A _i (A _i ^H A _i ) ^-1 A _i ^H x=x ^H Q _i x

Finally, the signal-to-noise ratio SNR expression can be expressed according to the received signal as:

in,

In the formula, x represents the original navigation baseband signal, A vector representing the transmitted uniform signal. Thus, the signal-to-noise ratio of the current channel can be obtained.

Further improvement: the estimated delay of the satellite navigation signal in the second step on each channel obeys a Gaussian distribution centered on the true delay, and the current signal-to-noise ratio is combined with the filter bandwidth to construct an asymptotic covariance matrix of the distribution The specific process is:

Estimated delay of the satellite navigation signal on the ith channel obey the following distribution:

where B is the filter bandwidth. Therefore, the asymptotic covariance matrix of the delay can be represented by the original satellite navigation signal, and the expression is as follows:

And the noise power in the ith channel is as follows:

Each desired satellite navigation signal is drowned in noise, so the signal energy x ^H x >> the projection of the original signal on the ith signal subspace, i.e. so,

Therefore, the asymptotic covariance matrix can be expressed as:

Further improvement: In the third step, the PVT covariance matrix is derived to obtain a new test statistic. The specific process is:

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 signal can be derived as:

Among them, C _P =cC _r , c represents the speed of light, and in this method, only the diagonal elements of the PVT covariance matrix representing the three-dimensional position of the receiver are considered. Typically, the fourth dimension of the PVT covariance matrix, the clock bias, is not considered. Therefore, three parameters are chosen

The PVT standard deviation obtained by this method is:

And thus construct a new test statistic. Different from 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 residual sum of squares (WSSE), which is composed of the error vector and the noise covariance matrix, Expressed as:

Among them, E represents the error vector (K×1) obeying the Gaussian distribution N(0, ∑); ∑ represents the noise covariance matrix (K×K), where,

Further improvement: the fourth step is to detect and identify satellite faults;

According to the expected false alarm probability, combined with the new test statistic, the threshold value is obtained. When the threshold value is greater than the test statistic, it means that there is no satellite fault; when the threshold value is less than the test statistic, it means that there is a satellite fault, and the satellite fault is identified.

Advantages of the present invention: 1. The existing receiver autonomous integrity monitoring method is implemented based on pseudorange measurements, and does not consider the influence of the original navigation signal received by the receiver on the integrity monitoring performance. The method can utilize the original satellite navigation 2. In the case of noise (such as weak multipath), the signal-to-noise ratio of this method will change, and then the PVT covariance and statistics can be measured. Therefore, the method can detect noises or even faults that have a slight impact on the PVT, so as to issue alarm information to the user in time, and improve the sensitivity of the integrity monitoring method.

Description of drawings

Figure 1 is a schematic structural diagram of the present invention.

Detailed ways

The present invention will be described in detail below with reference to the accompanying drawings.

As shown in Figure 1, the following concepts and definitions are first introduced:

1. Integrity: It means that when the positioning result is unavailable, the system can send an alarm service to the user in time, so as to avoid the wrong positioning result from causing positioning error or navigation danger to the user.

2. Fault detection (FD): refers to the judgment of the existence of the fault of the monitored system;

3. Fault isolation (FI): refers to the identification and elimination of satellite faults.

The present invention provides a method for monitoring the positioning integrity of a receiver based on an original satellite navigation signal. The specific steps are as follows:

The first step is to use the original satellite navigation signal to represent the current signal-to-noise ratio of the i-th channel;

The satellite navigation baseband signal model is:

Among them, α _i represents the complex amplitude of the ith satellite navigation signal, a _i (θ) represents the transmitted uniform signal vector, n is the additive white Gaussian noise with zero mean, and the distribution obeyed is n～N(0,δ ² ).

Among them, c _i represents the ith navigation signal transmitted by pseudo-random noise (Pseudo-random noise, PRN), and the PRN code mainly includes fine ranging code (P code) and coarse ranging code (C/A code), They realize the pseudo-code spread spectrum of the navigation message, so that it can be further modulated to the L1 carrier frequency or the L2 carrier frequency through the BPSK modulation method, thereby forming the L1 signal or the L2 signal. The delay τ _i (θ) and the Doppler parameter f _i (θ) can be calculated from the estimated PVT, and [t ₁ ,...,t _N ] is the vector of time samples;

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 expressed according to the signal model:

P _sig,i =E[(A _i α _i ) ^H (A _i α _i )]=α _i ^H A _i ^H A _i α _i

The ith magnitude is an unknown parameter, and the linear signal model can be estimated using the least squares method:

Therefore, the signal power expression can be expressed as:

P _sig,i =x ^H A _i (A _i ^H A _i ) ^-1 A _i ^H x=x ^H P _i x

Noise power estimation is based on the same principle, using noise signal amplitude estimation:

P _noise,i =||xA _i α _i || ²

Then the noise power can be obtained:

P _noise,i =x ^H xx ^H A _i (A _i ^H A _i ) ^-1 A _i ^H x=x ^H Q _i x

Finally, the signal-to-noise ratio SNR expression can be expressed according to the received signal as:

in

In the formula, x represents the original baseband signal and represents the vector of the transmitted unified signal.

In the second step, the estimated delay of the satellite navigation signal on each channel obeys a Gaussian distribution centered on the real delay, and the current signal-to-noise ratio is combined with the filter bandwidth to construct an asymptotic covariance matrix of the distribution;

Estimated delay of the signal on the ith channel obey the following distribution:

where B is the filter bandwidth. Therefore, the asymptotic covariance matrix of the delay can be represented by the original satellite navigation signal, and the expression is as follows:

And the noise power in the ith channel is as follows:

Each desired satellite navigation signal is drowned in noise, so the signal energy x ^H x >> the projection of the original signal on the ith signal subspace, i.e. so,

Therefore, the asymptotic covariance matrix can be expressed as:

The third step is to derive the PVT covariance matrix to obtain a new test statistic;

When the delayed asymptotic covariance matrix is obtained, it can be deduced from this that the PVT covariance matrix of the prior method is:

Among them, C _P =cC _r , c represents the speed of light, and in this method, only the diagonal elements of the PVT covariance matrix representing the three-dimensional position of the receiver are considered. Typically, the fourth dimension of the PVT covariance matrix, the clock bias, is not considered. Therefore, three parameters are chosen

The PVT standard deviation obtained by this method is:

And thus construct a new test statistic. Different from the test statistic in the weighted least squares residual method, the test statistic of the weighted least squares residual method is obtained from the weighted sum squared residual (WSSE), that is, it is composed of an error vector and a noise covariance matrix, which represents for:

Among them, E represents the error vector (K×1) obeying the Gaussian distribution N(0, ∑); ∑ represents the noise covariance matrix (K×K), where,

The fourth step is to detect and identify satellite faults.

According to the expected false alarm probability, combined with the new test statistic, the threshold value is obtained. When the threshold value is greater than the test statistic, it means that there is no satellite fault; when the threshold value is less than the test statistic, it means that there is a satellite fault, and the satellite fault is identified.

The detailed algorithm flow chart is shown in Figure 1:

① Calculate the current signal-to-noise ratio (SNR) of the i-th channel by using the original satellite navigation signal x.

②The estimated delay of the satellite navigation signal on each channel obeys a Gaussian distribution centered on the real delay, and the current signal-to-noise ratio SNR is combined with the filter bandwidth B to construct the asymptotic covariance matrix C _r of the distribution.

③ Derive the PVT covariance matrix from the asymptotic covariance matrix C _r .

④ Then get a new test statistic.

⑤ Calculate the threshold value T _th in combination with the expected false alarm probability value P _fa .

⑥ Detect and identify satellite faults.

The above descriptions are only the embodiments of the present invention, and are not intended to limit the scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the description and drawings of the present invention, or directly or indirectly applied to other related technologies Fields are similarly included in the scope of patent protection of the present invention.

Claims (5)

1. a receiver positioning integrity monitoring method based on original satellite navigation signal, is characterized in that: comprise the following steps; The first step is to use the original satellite navigation signal to calculate the current signal-to-noise ratio of the i-th channel; In the second step, the estimated delay of the satellite navigation signal on each channel obeys a Gaussian distribution centered on the real delay, and the current signal-to-noise ratio is combined with the filter bandwidth to construct an asymptotic covariance matrix of the distribution; The third step is to derive the PVT covariance matrix, and then obtain a new test statistic from its diagonal elements; The fourth step is to detect and identify satellite faults. 2. a kind of receiver positioning integrity monitoring method based on original satellite navigation signal as claimed in claim 1 is characterized in that: described first step utilizes original satellite navigation signal to calculate the current signal-to-noise ratio of the i-th channel out, the specific process is: The satellite navigation baseband signal model is: Among them, α _i represents the complex amplitude of the ith satellite navigation signal, a _i (θ) represents the transmitted uniform signal vector, n is the additive white Gaussian noise with zero mean, and the distribution obeyed is n～N(0,δ ² ); Among them, c _i represents the ith navigation signal transmitted by pseudo-random noise (Pseudo-random noise, PRN). The PRN code mainly includes the fine ranging code (P code) and the coarse ranging code (C/A code). The pseudo code spread spectrum of the navigation message is realized, so that it can be further modulated to the L1 carrier frequency or the L2 carrier frequency through the BPSK modulation method, thereby forming the L1 signal or the L2 signal. The delay τ _i (θ) and the Doppler parameter f _i (θ) can be calculated from the estimated PVT, and [t ₁ ,...,t _N ] is the vector of time samples; 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 expressed according to the signal model: P _sig,i =E[(A _i α _i ) ^H (A _i α _i )]=α _i ^H A _i ^H A _i α _i The ith magnitude is an unknown parameter, and the linear signal model can be estimated using the least squares method: Therefore, the signal power expression can be expressed as: P _sig,i =x ^H A _i (A _i ^H A _i ) ^-1 A _i ^H x=x ^H P _i x Noise power estimation is based on the same principle, using noise signal amplitude estimation: P _noise,i =||xA _i α _i || ² Then the noise power can be obtained: P _noise,i =x ^H xx ^H A _i (A _i ^H A _i ) ^-1 A _i ^H x=x ^H Q _i x Finally, the SNR expression can be expressed according to the received signal as: in, In the formula, x represents the original navigation baseband signal, The vector representing the transmitted unified navigation signal, from which the signal-to-noise ratio of the current channel can be obtained. 3. The method for monitoring the positioning integrity of a receiver based on the original satellite navigation signal according to claim 1, wherein the estimated delay of the satellite navigation signal in the second step asymptotically obeys the following: The Gaussian distribution centered on the true delay combines the current signal-to-noise ratio with the filter bandwidth, and the specific process of constructing the asymptotic covariance matrix of the distribution is as follows: Estimated delay of the satellite navigation signal on the ith channel obey the following distribution: In the formula, B represents the filter bandwidth, so the asymptotic covariance matrix of the delay can be represented by the original satellite navigation signal, and the expression is as follows: And the noise power in the ith channel is as follows: Each desired satellite navigation signal is drowned in noise, so the signal energy x ^H x >> the projection of the original satellite navigation signal on the ith signal subspace, i.e. so, Therefore, the asymptotic covariance matrix can be expressed as: 4. a kind of receiver positioning integrity monitoring method based on original satellite navigation signal as claimed in claim 1, is characterized in that: described 3rd step derives PVT covariance matrix, obtains new test statistic, and concrete process is : 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 signal can be derived as: Among them, C _P =cC _r , c represents the speed of light, and in this method, only the diagonal elements of the PVT covariance matrix representing the three-dimensional position of the receiver are considered. Typically, the fourth dimension of the PVT covariance matrix, the clock bias, is not considered. Therefore, three parameters are chosen The PVT standard deviation obtained by this method is: And thus construct a new test statistic. Different from 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 residual sum of squares (WSSE), which is composed of the error vector and the noise covariance matrix, Expressed as: Among them, E represents the error vector (K×1) obeying the Gaussian distribution N(0, ∑); ∑ represents the noise covariance matrix (K×K), where, 5. a kind of receiver positioning integrity monitoring method based on original satellite navigation signal as claimed in claim 1 is characterized in that: described 4th step carries out the detection and identification of satellite fault: According to the false alarm probability required by the satellite navigation application, it is combined with the new test statistic to obtain the threshold value. When the threshold value is greater than the test statistic, it means that there is no satellite fault; when the threshold value is less than the test statistic , it indicates that there is a satellite fault, and the satellite fault is identified.