A signal tracking method and system for a satellite navigation system receiver

Abstract

The application relates to the technical field of satellite navigation, and discloses a satellite navigation system receiver signal tracking method and system. The method comprises the following steps: obtaining a local carrier signal according to a carrier phase residual at a previous moment, performing coherent integration processing on an intermediate frequency carrier signal to obtain a coherent integration value; establishing a carrier signal state model and a carrier signal observation model of an extended Kalman filter of the intermediate frequency carrier signal according to the coherent integration value, performing extended Kalman filter iterative calculation on the coherent integration value to obtain a state vector estimation value of the intermediate frequency carrier signal; performing multi-channel carrier signal joint tracking on the coherent integration values corresponding to the intermediate frequency carrier signals of each antenna element, and obtaining a carrier phase residual at a current moment according to the obtained dynamic phase weight value, correcting the phase of the corresponding state vector estimation value to obtain a carrier signal phase estimation value. The method improves the signal tracking precision of the satellite navigation system receiver.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of satellite navigation system, and particularly relates to a signal tracking method and system of a satellite navigation system receiver. BACKGROUND

[0002] The satellite navigation system has the outstanding advantages of high-precision positioning and high-reliable time service. However, in the actual application process, the signal transmission and reception link of the satellite navigation system has significant vulnerability and limitation. On the one hand, when the satellite signal is transmitted from the outer space to the ground receiver, the signal strength is weak and is easily affected by the complex electromagnetic environment. At present, the number of various electronic devices (such as communication base stations, industrial control devices, consumer electronics, etc.) is growing explosively. The electromagnetic signals generated when a large number of electronic devices are running are superimposed on each other, forming a dense electromagnetic interference environment, which makes it difficult for the satellite navigation receiver antenna to capture the target navigation signal meeting the quality requirements, and even may be deceived by the fake interference signal, causing positioning deviation, time service failure and other problems, which seriously threatens the safety of the application system relying on satellite navigation. On the other hand, the complex application scenarios such as urban high-rise building dense areas, forest coverage areas and canyon areas are increasing. In such scenarios, the obstacles such as buildings, trees and terrain will cause serious channel shielding to the satellite signal, resulting in signal interruption or aggravation of multipath effect, further reducing the signal reception quality and working stability of the satellite navigation receiver.

[0003] In the prior art, the array signal processing technology is mainly used in the satellite navigation receiver to overcome interference. The signal processing logic of the traditional antenna array receiver is mostly set as: before the satellite intermediate frequency carrier signal enters the baseband processing module, the adaptive array processing operation is first performed on the intermediate frequency carrier signal. The processing operation usually includes key steps such as beam forming and null suppression, so as to improve the signal gain and suppress the multipath interference signal. However, the traditional antenna array receiver has great dependence on external information sources, and is not suitable for the increasingly complex signal environment. The signal tracking estimation accuracy is low.

[0004] Therefore, how to improve the signal tracking accuracy of the satellite navigation system receiver has become a technical problem to be solved by those skilled in the art. SUMMARY

[0005] The present application provides a signal tracking method and system of a satellite navigation system receiver, to solve the technical problem of how to improve the signal tracking accuracy of the satellite navigation system receiver, and to achieve the effect of improving the signal tracking accuracy of the satellite navigation system receiver.

[0006] In a first aspect, the present application provides a signal tracking method of a satellite navigation system receiver, the method comprising:

[0007] According to the carrier phase residual of each antenna array element at the last time, a local carrier signal is obtained, and coherent integration processing is performed on the intermediate frequency carrier signal output by each antenna array element according to the local carrier signal, to obtain a coherent integration value of each intermediate frequency carrier signal;

[0008] According to the coherent integration value, a carrier signal state model and a carrier signal observation model corresponding to the extended Kalman filter of the intermediate frequency carrier signal are established, and the coherent integration value is iteratively calculated based on the carrier signal state model and the carrier signal observation model to obtain a state vector estimation value of each intermediate frequency carrier signal;

[0009] Based on the local carrier signal, multi-channel carrier signal joint tracking is performed on the coherent integration value to obtain a dynamic phase weight value of each antenna array element;

[0010] According to the dynamic phase weight value, the carrier phase residual of each antenna array element at the current time is obtained, and the phase of the corresponding state vector estimation value is corrected according to the carrier phase residual at the current time to obtain a carrier signal phase estimation value of the intermediate frequency carrier signal.

[0011] Preferably, the coherent integration processing performed on the intermediate frequency carrier signal output by each antenna array element according to the local carrier signal to obtain the coherent integration value of each intermediate frequency carrier signal comprises:

[0012] According to the local carrier signal, target signal extraction and phase alignment are performed on the intermediate frequency carrier signal output by each antenna array element to obtain a baseband complex signal;

[0013] The complex domain superposition is performed on each baseband complex signal to obtain the coherent integration value of each intermediate frequency carrier signal.

[0014] Preferably, the establishment of the carrier signal state model and the carrier signal observation model corresponding to the extended Kalman filter of the intermediate frequency carrier signal according to the coherent integration value comprises:

[0015] The state vector and the state transition matrix of the intermediate frequency carrier signal are established, and the state vector and the state transition matrix are converted into a carrier signal state equation of the extended Kalman filter; a state noise covariance matrix is established according to the integration time, the intermediate frequency carrier signal angular frequency, and the power spectrum intensity of the state driving noise of the numerically controlled oscillator;

[0016] According to the carrier signal state equation and the state noise covariance matrix, a carrier signal state model is constructed;

[0017] Based on the coherence integral value, the carrier signal observation equation of the extended Kalman filter is set; based on the carrier-to-noise ratio of the intermediate frequency carrier signal, the observation noise covariance matrix is ​​set.

[0018] Based on the carrier signal observation equation and the observation noise covariance matrix, a carrier signal observation model is constructed.

[0019] Preferably, setting the carrier signal observation equation of the extended Kalman filter based on the coherent integral value includes:

[0020] The branch coherence matrix is ​​obtained based on the coherence integral value, the integration time, and the carrier phase of the intermediate frequency carrier signal;

[0021] The observation noise matrix is ​​obtained based on the coherent integral value of the co-directional observation noise in the co-directional branch and the orthogonal observation noise in the orthogonal branch.

[0022] Based on the branch coherence matrix and the observation noise matrix, the carrier signal observation equation of the extended Kalman filter is set.

[0023] Preferably, the step of performing extended Kalman filter iterative calculation on the coherent integral value based on the carrier signal state model and the carrier signal observation model to obtain the state vector estimate of each intermediate frequency carrier signal includes:

[0024] Based on the state noise covariance matrix, the carrier signal state equation, the state vector estimate of the previous time step, and the posterior error variance matrix of the previous time step, the single-step state prediction value and the prior error variance matrix of the current time step are obtained.

[0025] Based on the carrier signal observation equation, the coherent integral value is transformed to obtain the linearized observation matrix after the linearized observation function;

[0026] The Kalman gain is obtained based on the prior error variance matrix, the observation noise covariance matrix, and the linearized observation matrix.

[0027] Based on the single-step state prediction value, the Kalman gain, the carrier signal observation equation, and the linearized observation matrix, the coherent integral value is estimated to obtain the estimated state vector value at the current time. Then, based on the Kalman gain, the linearized observation matrix, and the prior error variance matrix, the posterior error variance matrix at the current time is estimated to obtain the posterior error variance matrix at the current time.

[0028] Preferably, the linearized observation matrix is ​​set as a matrix relating to the coherent integral value, the integration time, the total number of antenna elements, and the estimated phase value of the local carrier signal.

[0029] Preferably, the step of performing multi-channel carrier signal joint tracking on the coherent integral value based on the local carrier signal to obtain the dynamic phase weight value of each antenna element includes:

[0030] Based on the coherent integral value, an initial reference signal for each antenna element is obtained, and based on the initial reference signal, an initial phase weight value for the coherent integral value is obtained.

[0031] Based on the local carrier signal and the initial phase weight value, the initial reference signal is dynamically iteratively updated to obtain the dynamic reference signal of each antenna element at the current moment;

[0032] Based on the dynamic reference signal at the current moment, the initial phase weight value is dynamically iteratively updated to obtain the dynamic phase weight value of each antenna element at the current moment.

[0033] Preferably, the step of obtaining the carrier phase residual of each antenna element at the current moment based on the dynamic phase weight value, and based on the carrier phase residual at the current moment, includes:

[0034] Cross-correlation is performed between the intermediate frequency carrier signal of any one of the antenna array elements and the combined reference signal constructed by weighted combination of the remaining antenna array elements;

[0035] The phase difference between the intermediate frequency carrier signal and the combined reference signal is extracted to obtain the carrier phase residual of each antenna element at the current moment.

[0036] Preferably, the step of correcting the phase of the corresponding state vector estimate based on the carrier phase residual at the current time to obtain the carrier signal phase estimate of the intermediate frequency carrier signal includes:

[0037] The phase sum between the carrier phase residual at the current moment and the corresponding state vector estimate is calculated to obtain the carrier signal phase estimate of the intermediate frequency carrier signal.

[0038] Secondly, the present invention provides a signal tracking system for a satellite navigation system receiver, which implements the signal tracking method for the satellite navigation system receiver described above. The system includes: a coherent integration processing module, an extended Kalman filter processing module, a phase weight value dynamic update module, and a phase correction module.

[0039] The coherent integration processing module is used to obtain a local carrier signal based on the carrier phase residual of each antenna element at the previous moment, and to perform coherent integration processing on the intermediate frequency carrier signal output by each antenna element based on the local carrier signal to obtain the coherent integration value of each intermediate frequency carrier signal.

[0040] The extended Kalman filter processing module is used to establish a carrier signal state model and a carrier signal observation model corresponding to the extended Kalman filter of the intermediate frequency carrier signal based on the coherent integral value, and to perform extended Kalman filter iterative calculation on the coherent integral value based on the carrier signal state model and the carrier signal observation model to obtain the state vector estimate of each intermediate frequency carrier signal.

[0041] The phase weight value dynamic update module is used to perform multi-channel carrier signal joint tracking on the coherent integral value based on the local carrier signal to obtain the dynamic phase weight value of each antenna element.

[0042] The phase correction module is used to obtain the carrier phase residual of each antenna element at the current time according to the dynamic phase weight value, and to correct the phase of the corresponding state vector estimate according to the carrier phase residual at the current time, so as to obtain the carrier signal phase estimate of the intermediate frequency carrier signal.

[0043] This application provides a signal tracking method and system for a satellite navigation system receiver. Compared with the prior art, the beneficial effects of the embodiments of this application are as follows:

[0044] This application utilizes the similarity of transmission channels and the correlation of signals between antenna array elements to divide the signal carrier phase change into a common carrier phase caused by satellite motion and a residual carrier phase caused by differences in the array antenna positions, and tracks them separately. This improves the accuracy of signal carrier phase estimation in complex electromagnetic environments. The single-channel signal tracking loop structure in the antenna array elements is optimized and adjusted to improve the tracking sensitivity of each array element to its respective received signal, thereby improving the tracking performance of weak signals in interference environments. The application also transforms the joint processing of spatial signals of the antenna array from the intermediate frequency signal processing level to the baseband signal processing level, avoiding the computational load and hardware resource consumption caused by the large bandwidth and high precision of intermediate frequency signal processing. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the signal tracking method steps of a satellite navigation system receiver according to a preferred embodiment of the present invention;

[0046] Figure 2 This is a schematic diagram of the structure of a signal tracking system for a satellite navigation system receiver according to a preferred embodiment of the present invention;

[0047] Figure label:

[0048] 1- Coherent integration processing module, 2- Extended Kalman filter processing module, 3- Dynamic update module for phase weight values, 4- Phase correction module. Detailed Implementation

[0049] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. The embodiments are given for illustrative purposes only and should not be construed as limiting the invention. The accompanying drawings are for reference and illustration only and do not constitute a limitation on the scope of protection of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of this invention. In the description of the present invention, unless otherwise stated, "a plurality of" means two or more.

[0050] In the description of this invention, it should be noted that, unless otherwise expressly specified and limited, the term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0051] In the description of this invention, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0052] Please see Figure 1 The diagram illustrates the steps of a signal tracking method for a satellite navigation system receiver. In an embodiment of the present invention, a signal tracking method for a satellite navigation system receiver is provided, the method comprising:

[0053] S1. Based on the carrier phase residual of each antenna element at the previous moment, a local carrier signal is obtained. Then, based on the local carrier signal, coherent integration processing is performed on the intermediate frequency (IF) carrier signal output by each antenna element to obtain the coherent integration value of each IF carrier signal. In a preferred embodiment of this application, a weak signal anti-interference tracking method based on extended Kalman filtering is proposed to track the IF carrier signal captured by each antenna element in the antenna array. The numerically controlled oscillator outputs a local carrier signal based on the carrier phase residual of the previous moment. Based on the local carrier signal, coherent integration processing is performed on the IF carrier signal output by each antenna element. Coherent integration processing is a key signal processing technology that utilizes "signal phase consistency" to improve the signal-to-noise ratio. Its core is to superimpose multiple received signals while "preserving signal phase information," thereby enhancing the useful signal and suppressing random noise. Specifically, through a phase converter, the target signal is extracted from the IF carrier signal output by the RF front-end of each antenna array, and the extracted signal is phase-aligned using the local carrier signal to obtain a baseband complex signal. Since the phase information of the signal needs to be represented by complex numbers, with the real part representing the amplitude and the imaginary part representing the phase, the baseband complex signals are superimposed in the complex domain to obtain the coherent integral value. In the complex domain superposition, the pseudocode signal of the satellite navigation system in the intermediate frequency carrier signal is enhanced according to the linear relationship of the number of superposition segments because its phase is aligned with the local carrier signal. The random noise in the intermediate frequency carrier signal is enhanced according to the number of superposition segments because its phase is random. The signal-to-noise ratio of the final output coherent integral value is significantly improved compared with the intermediate frequency carrier signal output by a single antenna element.

[0054] S2 establishes a carrier signal state model and a carrier signal observation model corresponding to the extended Kalman filter of the intermediate frequency carrier signal based on the coherent integral value, and performs extended Kalman filter iterative calculation on the coherent integral value based on the carrier signal state model and the carrier signal observation model to obtain the state vector estimate of each intermediate frequency carrier signal; In a preferred embodiment of this application, the signal tracking method of the satellite navigation system receiver includes a single-channel carrier signal tracking stage and a multi-channel carrier signal joint tracking stage. For the single-channel carrier signal tracking stage, an extended Kalman filter is used to replace the maximum likelihood estimator, and an extended Kalman filter carrier signal state model and a carrier signal observation model are established. The carrier signal state model includes a carrier signal state equation and a state noise covariance matrix. For the carrier signal state equation, a state vector and a state transition matrix of the intermediate frequency carrier signal are established. The change process of the state vector value is expressed as follows:

[0055]

[0056] in, express The carrier phase of the intermediate frequency carrier signal at a given time. express The carrier Doppler frequency shift of the intermediate frequency carrier signal at a given time. express The rate of change of the carrier Doppler frequency of the intermediate frequency carrier signal at time t. , and They represent ( The higher-order terms after performing a Taylor expansion on the intermediate frequency carrier signal at time ) Indicates the integration time.

[0057] The change process of the above state vector values ​​is modeled as the carrier signal state equation of the extended Kalman filter, which is expressed as:

[0058]

[0059] in, express Error state quantity at time t. express( Error state quantity at time ) express( The carrier Doppler frequency shift of the intermediate frequency carrier signal at time ) express( The rate of change of the carrier Doppler frequency of the intermediate frequency carrier signal at time ) , , This represents the state-driven noise of the numerically controlled oscillator. It is white noise from the random phase walk of the clock crystal oscillator. It is white noise with random walk at the clock crystal frequency. It's clock crystal frequency noise. express The Doppler shift of the local carrier signal before the end of the extended Kalman filter.

[0060] Furthermore, based on the integration time, the angular frequency of the intermediate frequency carrier signal, and the power spectral intensity of the state-driven noise of the extended Kalman filter, a state noise covariance matrix is ​​established, which is expressed as:

[0061]

[0062] in, express The angular frequency of the intermediate frequency carrier signal at any given time. express The power spectral intensity, express The power spectral intensity, express The power spectral intensity.

[0063] The carrier signal observation model includes the carrier signal observation equation and the observation noise covariance matrix. The carrier signal observation equation is expressed as:

[0064]

[0065] in, This represents the observed value output by the phase detector, which is the coherent integral value. express The first observation value in the same phase branch at any given time. express The second observation value at any given moment on the orthogonal branch. express In-phase observation noise of the same-phase branch at the same time. express Orthogonal observation noise of the orthogonal branch at each moment.

[0066]

[0067] in, express The first coherent integral value of the same phase branch at any given time. express The second coherent integral value at any given moment on the orthogonal branch.

[0068]

[0069] in, express The observation noise matrix at time 1ms is set to 1ms.

[0070] Based on the carrier-to-noise ratio of the intermediate frequency carrier signal, the observation noise covariance matrix is ​​set, and the observation noise covariance matrix is ​​expressed as:

[0071]

[0072] in, This indicates the carrier-to-noise ratio of the intermediate frequency carrier signal. This represents a two-dimensional identity matrix.

[0073] Furthermore, based on the carrier signal state model and the carrier signal observation model, extended Kalman filtering iterative calculation is performed on the coherent integral value to obtain the state vector estimate and the posterior error variance matrix. Specifically, based on the state noise covariance matrix of the carrier signal state model, the carrier signal state equation of the carrier signal state model, the state vector estimate of the previous time step, and the posterior error variance matrix of the previous time step, the single-step state prediction value and the prior error variance matrix of the current time step are obtained. The calculation formulas are as follows:

[0074]

[0075]

[0076] in, express State vector estimate at time t. express The prior error variance matrix at time t. express The single-step state prediction value at time 10:00. express The prior error variance matrix at time step 1. The single-step state prediction represents the prior state estimate of the current state obtained solely using prior knowledge of the process, without considering process noise.

[0077] Based on the carrier signal observation equation of the carrier signal observation model, the coherence integral value is transformed to obtain the linearized observation matrix after linearizing the observation function. The linearized observation matrix is ​​expressed as:

[0078]

[0079] in, express Linearized observation matrix at time step, Indicates the total number of antenna array elements. express The phase estimate of the local carrier signal at time [time]. This represents the observation noise of the intermediate frequency carrier signal.

[0080] Furthermore, based on the prior error variance matrix, the observation noise covariance matrix of the carrier signal observation model, and the linearized observation matrix, the Kalman gain is obtained, which is expressed as:

[0081]

[0082] in, This represents the Kalman gain.

[0083] Based on the single-step state prediction value, Kalman gain, carrier signal observation equation, and linearized observation matrix, the coherent integral value is estimated to obtain the estimated state vector value at the current time, as shown below:

[0084]

[0085] in, express State vector estimate at time t.

[0086] Based on the Kalman gain, the linearized observation matrix, and the prior error variance matrix, the posterior error variance matrix of the previous time step is estimated to obtain the posterior error variance matrix of the current time step, as shown below:

[0087]

[0088] in, express The prior error variance matrix at time t.

[0089] In the preferred embodiment of this application, the common carrier phase estimation is performed using extended Kalman filtering, achieving the optimal estimation result and exhibiting excellent filtering performance.

[0090] S3. Based on the local carrier signal, perform multi-channel carrier signal joint tracking on the coherent integral value to obtain the dynamic phase weight value of each antenna element. In a preferred embodiment of this application, for the multi-channel carrier signal joint tracking stage, a reference signal is generated by a signal synthesis method, and the average phase value and average frequency are estimated to integrate the tracking results of all channels. Specifically, based on the coherent integral value, an initial reference signal for each antenna element is obtained, and based on the initial reference signal, an initial phase weight value for the coherent integral value is obtained. The initial reference signal is represented as follows:

[0091]

[0092] in, Represents antenna array elements The conjugate of the coherent integral values.

[0093] Based on the local carrier signal and the initial phase weight value, the initial reference signal is dynamically iteratively updated to obtain the dynamic reference signal for each antenna element at the current moment. The expression for updating the dynamic reference signal is:

[0094]

[0095] in, express Dynamic reference signal at any given time, This indicates the antenna element number used to calculate the reference signal. express Time antenna array element The complex conjugate of the intermediate frequency carrier signal, In addition to the array elements The numbering of other antenna array elements besides express Time antenna array element The dynamic phase weight value, express The local carrier signal at any given time.

[0096] Furthermore, based on the dynamic reference signal at the current moment, the initial phase weight value is dynamically iteratively updated to obtain the dynamic phase weight value of each antenna element at the current moment. The update formula for the dynamic phase weight value at the current moment is:

[0097]

[0098] in, express Time antenna array element The dynamic phase weight value, express Time Array Element The intermediate frequency carrier signal at that location, express Time antenna array element The complex conjugate of the dynamic phase weight value, Represents antenna array elements The number of sampling points for cross-correlation calculation.

[0099] S4. Based on the dynamic phase weight value, obtain the carrier phase residual of each antenna element at the current moment, and based on the carrier phase residual at the current moment, correct the phase of the corresponding state vector estimate to obtain the carrier signal phase estimate of the intermediate frequency carrier signal; In a preferred embodiment of this application, by cross-correling the intermediate frequency carrier signal received by one of the wire array elements with the combined reference signal constructed by the weighted combination of the other wire array elements in the wire array, extract its phase difference value to obtain the carrier phase residual of the wire array element relative to the array center, and the carrier phase residual is expressed as follows:

[0100]

[0101] in, express Time antenna array element carrier phase residual, This indicates the extraction of the phase angle.

[0102] Furthermore, based on the carrier phase residual of each intermediate frequency carrier signal, the corresponding state vector estimate is corrected to obtain the carrier signal phase estimate of the intermediate frequency carrier signal, which is expressed as:

[0103]

[0104] in, express Time antenna array element The estimated phase value of the carrier signal. express Time antenna array element The phase of the state vector estimate.

[0105] In a preferred embodiment of the present invention, a local carrier signal is obtained based on the carrier phase residual of each antenna element at the previous moment. Then, based on the local carrier signal, coherent integration processing is performed on the intermediate frequency (IF) carrier signal output by each antenna element to obtain the coherent integral value of each IF carrier signal. Based on the coherent integral value, a carrier signal state model and a carrier signal observation model corresponding to the extended Kalman filter of the IF carrier signal are established. Based on the carrier signal state model and the carrier signal observation model, iterative calculation of the coherent integral value using extended Kalman filtering is performed to obtain the state vector estimate of each IF carrier signal. Based on the local carrier signal, multi-channel carrier signal joint tracking is performed on the coherent integral value to obtain the dynamic phase weight value of each antenna element. Based on the dynamic phase weight value, the carrier phase residual of each antenna element at the current moment is obtained. Based on the carrier phase residual at the current moment, the phase of the corresponding state vector estimate is corrected to obtain the carrier signal phase estimate of the IF carrier signal. The signal tracking method for satellite navigation system receivers disclosed in this application utilizes the similarity of transmission channels and the correlation of signals between antenna array elements to divide the signal carrier phase change into a common carrier phase caused by satellite motion and a residual carrier phase caused by differences in array antenna positions, and tracks them separately. This improves the accuracy of signal carrier phase estimation in complex electromagnetic environments. The method also optimizes and adjusts the single-channel signal tracking loop structure in the antenna array elements, improving the tracking sensitivity of each array element for its respective received signal. This enhances the tracking performance of weak signals in interference environments. Furthermore, it transforms the joint processing of spatial signals of the antenna array from the intermediate frequency signal processing level to baseband signal processing, avoiding the computational burden and hardware resource consumption caused by the large bandwidth and high precision of intermediate frequency signal processing.

[0106] Accordingly, such as Figure 2 The diagram shows the structure of a signal tracking system for a satellite navigation system receiver. Based on a signal tracking method for a satellite navigation system receiver, this embodiment of the invention also provides a signal tracking system for a satellite navigation system receiver, implementing the signal tracking method for a satellite navigation system receiver disclosed in this embodiment of the invention. The system includes: a coherent integration processing module 1, an extended Kalman filter processing module 2, a phase weight value dynamic update module 3, and a phase correction module 4.

[0107] The coherent integration processing module 1 is used to obtain a local carrier signal based on the carrier phase residual of each antenna element at the previous moment, and to perform coherent integration processing on the intermediate frequency carrier signal output by each antenna element based on the local carrier signal to obtain the coherent integration value of each intermediate frequency carrier signal.

[0108] The extended Kalman filter processing module 2 is used to establish a carrier signal state model and a carrier signal observation model corresponding to the extended Kalman filter of the intermediate frequency carrier signal based on the coherent integral value, and to perform extended Kalman filter iterative calculation on the coherent integral value based on the carrier signal state model and the carrier signal observation model to obtain the state vector estimate value of each intermediate frequency carrier signal.

[0109] The phase weight value dynamic update module 3 is used to perform multi-channel carrier signal joint tracking on the coherent integral value based on the local carrier signal to obtain the dynamic phase weight value of each antenna element.

[0110] The phase correction module 4 is used to obtain the carrier phase residual of each antenna element at the current time according to the dynamic phase weight value, and to correct the phase of the corresponding state vector estimate according to the carrier phase residual at the current time, so as to obtain the carrier signal phase estimate of the intermediate frequency carrier signal.

[0111] Specific limitations regarding the signal tracking system of a satellite navigation system receiver can be found in the above-described limitations regarding the signal tracking method of a satellite navigation system receiver, and will not be repeated here. Those skilled in the art will recognize that the various modules and steps described in conjunction with the embodiments disclosed in this invention can be implemented in hardware, software, or a combination of both. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0112] In summary, the signal tracking method and system for a satellite navigation system receiver provided in this application solve the technical problem of how to improve the signal tracking accuracy of a satellite navigation system receiver. The method includes: obtaining a local carrier signal based on the carrier phase residual of each antenna element at the previous moment; performing coherent integration processing on the intermediate frequency carrier signal output by each antenna element based on the local carrier signal to obtain a coherent integral value for each intermediate frequency carrier signal; establishing a carrier signal state model and a carrier signal observation model corresponding to the extended Kalman filter of the intermediate frequency carrier signal based on the coherent integral value; performing extended Kalman filter iterative calculation on the coherent integral value based on the carrier signal state model and the carrier signal observation model to obtain a state vector estimate for each intermediate frequency carrier signal; performing multi-channel carrier signal joint tracking on the coherent integral value based on the local carrier signal to obtain a dynamic phase weight value for each antenna element; obtaining the carrier phase residual of each antenna element at the current moment based on the dynamic phase weight value; and correcting the phase of the corresponding state vector estimate based on the carrier phase residual at the current moment to obtain a carrier signal phase estimate for the intermediate frequency carrier signal. The signal tracking method for satellite navigation system receivers disclosed in this application utilizes the similarity of transmission channels and the correlation of signals between antenna array elements to divide the signal carrier phase change into a common carrier phase caused by satellite motion and a residual carrier phase caused by differences in array antenna positions, and tracks them separately. This improves the accuracy of signal carrier phase estimation in complex electromagnetic environments. The method also optimizes and adjusts the single-channel signal tracking loop structure in the antenna array elements, improving the tracking sensitivity of each array element for its respective received signal. This enhances the tracking performance of weak signals in interference environments. Furthermore, it transforms the joint processing of spatial signals of the antenna array from the intermediate frequency signal processing level to baseband signal processing, avoiding the computational burden and hardware resource consumption caused by the large bandwidth and high precision of intermediate frequency signal processing.

[0113] The various embodiments in this specification are described in a progressive manner. For directly identical or similar parts of the embodiments, refer to each other. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. It should be noted that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0114] The embodiments described above are merely preferred embodiments of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various improvements and substitutions without departing from the technical principles of this application, and these improvements and substitutions should also be considered within the scope of protection of this application. Therefore, the scope of protection of this patent application should be determined by the scope of the claims.

Claims

1. A signal tracking method for a satellite navigation system receiver, characterized in that, The method includes: Based on the carrier phase residual of each antenna element obtained at the previous moment, the local carrier signal is obtained, and based on the local carrier signal, the intermediate frequency carrier signal output by each antenna element is coherently integrated to obtain the coherent integral value of each intermediate frequency carrier signal. Based on the coherent integral value, a carrier signal state model and a carrier signal observation model corresponding to the extended Kalman filter of the intermediate frequency carrier signal are established. Based on the carrier signal state model and the carrier signal observation model, the extended Kalman filter is iteratively calculated on the coherent integral value to obtain the state vector estimate of each intermediate frequency carrier signal. Based on the local carrier signal, multi-channel carrier signal joint tracking is performed on the coherent integral value to obtain the dynamic phase weight value of each antenna element. This includes: obtaining an initial reference signal for each antenna element based on the coherent integral value, and obtaining an initial phase weight value for the coherent integral value based on the initial reference signal; dynamically iteratively updating the initial reference signal based on the local carrier signal and the initial phase weight value to obtain the dynamic reference signal of each antenna element at the current moment; and dynamically iteratively updating the initial phase weight value based on the dynamic reference signal at the current moment to obtain the dynamic phase weight value of each antenna element at the current moment. Based on the dynamic phase weight value, the carrier phase residual of each antenna element at the current moment is obtained, and the phase of the corresponding state vector estimate is corrected based on the carrier phase residual at the current moment to obtain the carrier signal phase estimate of the intermediate frequency carrier signal.

2. The signal tracking method for a satellite navigation system receiver as described in claim 1, characterized in that, The step of performing coherent integration processing on the intermediate frequency carrier signal output by each antenna element based on the local carrier signal to obtain the coherent integration value of each intermediate frequency carrier signal includes: Based on the local carrier signal, target signal extraction and phase alignment are performed on the intermediate frequency carrier signal output by each antenna element to obtain a baseband complex signal; The complex domain superposition of each baseband complex signal is performed to obtain the coherent integral value of each intermediate frequency carrier signal.

3. The signal tracking method for a satellite navigation system receiver as described in claim 1, characterized in that, The step of establishing the carrier signal state model and carrier signal observation model corresponding to the extended Kalman filter of the intermediate frequency carrier signal based on the coherent integral value includes: Establish the state vector and state transition matrix of the intermediate frequency carrier signal, and convert the state vector and state transition matrix into the state equation of the extended Kalman filter carrier signal; establish the state noise covariance matrix based on the integration time, the angular frequency of the intermediate frequency carrier signal, and the power spectral intensity of the state drive noise of the numerically controlled oscillator. Based on the carrier signal state equation and the state noise covariance matrix, a carrier signal state model is constructed. Based on the coherence integral value, the carrier signal observation equation of the extended Kalman filter is set; based on the carrier-to-noise ratio of the intermediate frequency carrier signal, the observation noise covariance matrix is ​​set. Based on the carrier signal observation equation and the observation noise covariance matrix, a carrier signal observation model is constructed.

4. The signal tracking method for a satellite navigation system receiver as described in claim 3, characterized in that, The step of setting the carrier signal observation equation of the extended Kalman filter based on the coherent integral value includes: The branch coherence matrix is ​​obtained based on the coherence integral value, the integration time, and the carrier phase of the intermediate frequency carrier signal; The observation noise matrix is ​​obtained based on the coherent integral value of the co-directional observation noise in the co-directional branch and the orthogonal observation noise in the orthogonal branch. Based on the branch coherence matrix and the observation noise matrix, the carrier signal observation equation of the extended Kalman filter is set.

5. The signal tracking method for a satellite navigation system receiver as described in claim 3, characterized in that, The step of performing extended Kalman filter iterative calculation on the coherent integral value based on the carrier signal state model and the carrier signal observation model to obtain the state vector estimate of each intermediate frequency carrier signal includes: Based on the state noise covariance matrix, the carrier signal state equation, the state vector estimate of the previous time step, and the posterior error variance matrix of the previous time step, the single-step state prediction value and the prior error variance matrix of the current time step are obtained. Based on the carrier signal observation equation, the coherent integral value is transformed to obtain the linearized observation matrix after the linearized observation function; The Kalman gain is obtained based on the prior error variance matrix, the observation noise covariance matrix, and the linearized observation matrix. Based on the single-step state prediction value, the Kalman gain, the carrier signal observation equation, and the linearized observation matrix, the coherent integral value is estimated to obtain the estimated state vector value at the current time. Then, based on the Kalman gain, the linearized observation matrix, and the prior error variance matrix, the posterior error variance matrix at the current time is estimated to obtain the posterior error variance matrix at the current time.

6. The signal tracking method for a satellite navigation system receiver as described in claim 5, characterized in that, The linearized observation matrix is ​​set as a matrix relating to the coherent integral value, the integration time, the total number of antenna elements, and the estimated phase value of the local carrier signal.

7. The signal tracking method for a satellite navigation system receiver as described in claim 1, characterized in that, The step of obtaining the carrier phase residual of each antenna element at the current moment based on the dynamic phase weight value, and based on the carrier phase residual at the current moment, includes: Cross-correlation is performed between the intermediate frequency carrier signal of any one of the antenna array elements and the combined reference signal constructed by weighted combination of the remaining antenna array elements; The phase difference between the intermediate frequency carrier signal and the combined reference signal is extracted to obtain the carrier phase residual of each antenna element at the current moment.

8. The signal tracking method for a satellite navigation system receiver as described in claim 1, characterized in that, The step of correcting the phase of the corresponding state vector estimate based on the carrier phase residual at the current moment to obtain the carrier signal phase estimate of the intermediate frequency carrier signal includes: The phase sum between the carrier phase residual at the current moment and the corresponding state vector estimate is calculated to obtain the carrier signal phase estimate of the intermediate frequency carrier signal.

9. A signal tracking system for a satellite navigation system receiver, used to implement the signal tracking method for the satellite navigation system receiver according to any one of claims 1-8, characterized in that, The system includes: a coherent integration processing module, an extended Kalman filter processing module, a phase weight value dynamic update module, and a phase correction module; The coherent integration processing module is used to obtain a local carrier signal based on the carrier phase residual of each antenna element at the previous moment, and to perform coherent integration processing on the intermediate frequency carrier signal output by each antenna element based on the local carrier signal to obtain the coherent integration value of each intermediate frequency carrier signal. The extended Kalman filter processing module is used to establish a carrier signal state model and a carrier signal observation model corresponding to the extended Kalman filter of the intermediate frequency carrier signal based on the coherent integral value, and to perform extended Kalman filter iterative calculation on the coherent integral value based on the carrier signal state model and the carrier signal observation model to obtain the state vector estimate of each intermediate frequency carrier signal. The phase weight value dynamic update module is used to perform multi-channel carrier signal joint tracking on the coherent integral value based on the local carrier signal to obtain the dynamic phase weight value of each antenna element. This includes: obtaining an initial reference signal for each antenna element based on the coherent integral value, and obtaining an initial phase weight value for the coherent integral value based on the initial reference signal; dynamically iteratively updating the initial reference signal based on the local carrier signal and the initial phase weight value to obtain the dynamic reference signal for each antenna element at the current time; and dynamically iteratively updating the initial phase weight value based on the dynamic reference signal at the current time to obtain the dynamic phase weight value for each antenna element at the current time. The phase correction module is used to obtain the carrier phase residual of each antenna element at the current time according to the dynamic phase weight value, and to correct the phase of the corresponding state vector estimate according to the carrier phase residual at the current time, so as to obtain the carrier signal phase estimate of the intermediate frequency carrier signal.

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