High dynamic navigation signal radio frequency baseband integration method, device, equipment and medium

Abstract

The present invention relates to a method, device, equipment and medium for integrating radio frequency baseband of high dynamic navigation signal, including: obtaining the Doppler frequency of satellite signal in normal scene mode or high dynamic scene mode; inputting the Doppler frequency into a filter, outputting the initial state value of the position solution information of the Doppler frequency in the current state, the initial state value including the position coordinates of the satellite, the running speed of the satellite and the time variable; inputting the initial state value into a preset tracking channel, outputting the predicted state correction value of the Doppler frequency in the next state of the current state; correcting the position solution information of the next state of the current state output by the filter by the predicted state correction value, and obtaining the target position solution information. The problem that the existing satellite signal receiving and processing method is not suitable for the reception and processing of satellite signals in high dynamic scene mode is solved.

Description

Background Art

[0002] Doppler frequencies in different ranges correspond to different scene modes. The scene modes are specifically divided into ordinary scene modes and high dynamic scene modes. In the prior art, for dynamic tracking and positioning of satellite signals in ordinary scene modes, a filter with a conventional frequency sweep range can be used. However, for high dynamic scene modes, since the Doppler frequency range of satellite signals is larger, tracking and positioning of satellite signals in high dynamic scene modes requires expanding the range of the Doppler frequency sweep to capture the Doppler frequency and ultimately obtain position solution information. However, expanding the range of the filter frequency sweep will greatly increase the amount of subsequent incoherently accumulated data, requiring more computing resources, and increasing the power consumption, volume and cost of the receiver. Therefore, filters with conventional frequency sweep ranges cannot be used for dynamic tracking and positioning of satellite signals in multiple scene modes. Summary of the invention

[0003] In order to overcome the problem that filters with conventional frequency sweep ranges cannot dynamically track and locate satellite signals in multiple scenario modes, the present invention provides a high-dynamic navigation signal RF baseband integration method, device, equipment and medium.

[0004] In a first aspect, in order to solve the above technical problems, the present invention provides a high dynamic navigation signal radio frequency baseband integration method, comprising the following steps:

[0005] S1, obtaining the Doppler frequency of the satellite signal in the normal scene mode or the high dynamic scene mode;

[0006] S2, inputting the Doppler frequency into the filter, and outputting the initial state value of the position solution information of the Doppler frequency in the current state, the initial state value including the position coordinates of the satellite, the running speed of the satellite and the time variable;

[0007] S3, inputting the initial state value into the preset tracking channel, and outputting the predicted state correction value of the Doppler frequency in the next state of the current state;

[0008] S4, correcting the position solution information of the next state of the current state output by the filter through the predicted state correction value to obtain the target position solution information.

[0009] The beneficial effects of the high-dynamic navigation signal radio frequency baseband integration method provided by the present invention are:

[0010] After receiving the satellite signal by the above method, the Doppler frequency of the received satellite signal in the normal scene mode or the high dynamic scene mode is uniformly preprocessed by using a filter with a conventional sweep frequency range to obtain the initial state value of the position solution information of the Doppler frequency in the current state, and then the initial state value is input into a preset tracking channel to obtain the predicted state correction value of the next state, and finally the predicted state correction value is used to correct the position solution information of the next state of the previous state output by the filter, so as to obtain the target solution information. When the filter with a conventional sweep frequency range is used to process the Doppler frequency in the high dynamic scene, the position solution information of the next state of the output current state is inaccurate, so a preset tracking channel is constructed, and the predicted state correction value of the next state is obtained through the preset tracking channel, and the predicted state correction value is used to correct the inaccurate position solution information of the next state of the current state output by the filter, so as to obtain accurate target position solution information, thereby avoiding the need to expand the sweep frequency range of the filter for processing the Doppler frequency in the high dynamic scene, and solving the problem that the satellite signal receiving and processing method in the prior art is not suitable for the satellite signal receiving and processing in the high dynamic scene mode.

[0011] On the basis of the above technical solution, the high dynamic navigation signal radio frequency baseband integration method of the present invention can also be improved as follows.

[0012] Furthermore, the preset tracking channel includes a first tracking channel and a second tracking channel, and steps S3-S4 further include:

[0013] S3, inputting the initial state value into a preset first tracking channel, outputting a first predicted state correction value of the Doppler frequency in the next state of the current state, inputting the initial state value into a preset second tracking channel, outputting a second predicted state correction value of the Doppler frequency in the next state of the current state;

[0014] S4, compare the first predicted state correction value and the second predicted state correction value, select the smaller predicted state correction value as the target predicted state correction value, use the target predicted state correction value to correct the position solution information of the next state of the current state output by the filter, and obtain the target position solution information.

[0015] The beneficial effect of adopting the above further scheme is: by comparing the first predicted state correction value and the second predicted state correction value, a smaller predicted state correction value is obtained as the target predicted state correction value, thereby improving the accuracy of the correction of the position solution information of the next state of the current state output by the filter.

[0016] Furthermore, the satellite signal includes an intermediate frequency signal, and S1 specifically includes:

[0017] S11, performing a down-conversion operation on the intermediate frequency signal of the satellite signal to obtain a satellite baseband signal;

[0018] S12, downsampling the satellite baseband signal to obtain a target satellite baseband signal;

[0019] S13, performing coherent accumulation processing on the target satellite baseband signal and the pre-generated PN code,

[0020] Get the peak range;

[0021] S14, performing threshold screening processing on the peak range to obtain the Doppler frequency in the normal scene mode or the high dynamic scene mode.

[0022] The beneficial effect of adopting the above further scheme is: by performing down-conversion operation, down-sampling processing, and coherent accumulation processing with the pre-generated PN code on the acquired satellite signal, the peak range is obtained, and the peak range is threshold-screened (actually the peak range is divided and screened), and finally the Doppler frequency in the normal scene mode or the high dynamic scene mode is obtained. The whole method is simple to operate and the obtained Doppler frequency result is accurate.

[0023] Further, S13 specifically includes:

[0024] S13, performing coherent accumulation processing on the target satellite baseband signal and the pre-generated PN code based on a preset search step length and a preset coherent accumulation time to obtain a peak range.

[0025] The beneficial effect of adopting the above further scheme is that when the target satellite baseband signal is obtained, the peak range can be obtained by directly using the corresponding pre-generated PN code, preset search step size and preset coherent accumulation time to perform a coherent accumulation operation.

[0026] Furthermore, the construction process of the above preset tracking channel is as follows:

[0027] S31, according to the actual code phase, code phase noise, actual carrier frequency and carrier frequency noise obtained by state filtering the initial state value, determine the code phase error and the carrier frequency error by a first formula, wherein the first formula is:

[0028]

[0029]

[0030] in, They represent the code phase error and carrier frequency error of the g-th satellite at time k+1 respectively; represent the actual code phase, the predicted code phase and the code phase noise at time k+1 respectively; They represent the actual carrier frequency, the predicted carrier frequency and the carrier frequency noise at time k+1 respectively;

[0031] S32, according to the code phase error and the carrier frequency error, determine the pseudorange and pseudorange rate error of the initial state value by a second formula, wherein the second formula is:

[0032]

[0033] Where Δρ represents the pseudorange, represents the pseudorange rate error, Δτ g represents the code phase error, Δf g represents the carrier frequency error, f code represents the code rate parameter, f0 represents the carrier frequency parameter, and c represents the speed of light;

[0034] S33, according to the initial state value, the pseudorange and the pseudorange rate error, determine the state error value between the true value and the predicted value of the filter, and the measured value of the filter by a third formula, wherein the third formula is:

[0035] Δx=[δx,δy,δz,cδt b ,δv x ,δv y ,δv z ,cδt d ] T

[0036]

[0037] Among them, Δx represents the state error between the true value and the observed value of the filter, z represents the measured value of the filter, δx, δy, δz represent the difference between the true value and the predicted value of the satellite position coordinates x, y, z in the filter, respectively, and cδt b , cδt d Indicates the filter t b ,t d The difference between the actual value and the predicted value of the total distance traveled by light at time δv x ,δv y ,δv z Respectively represent the difference between the true value and the observed value of the satellite's running speed on the x, y, and z coordinates in the filter, They represent the difference between the true value and the observed value of the pseudorange of each satellite from the 1st satellite to the gth satellite, They represent the difference between the true value and the observed value of the pseudo-range rate error of each satellite from the 1st satellite to the gth satellite, and T represents the conversion calculation symbol;

[0038] S34, determining the predicted state error value according to the initial state value, the state error value and the measured value of the filter by using the fourth formula, wherein the fourth formula is:

[0039] ΔX k+1 =F k,k+1 ΔX k +W k ;

[0040] Z k+1 =H k+1 ΔX k+1 +V k ;

[0041] Where ΔX k+1 Indicates the predicted state error value of the filter in the next state of the current state, X k Indicates the initial state value under the current state, ΔX k The state error value of the initial state value of the filter in the current state, F k,k+1 Indicates the symbol for calculating the transition matrix from the current state to the next state, W k It represents the noise term after the filter performs matrix processing on the noise, H k+1 Represents the projection matrix calculation symbol between the observation quantity and state quantity of the filter, V k represents the noise term of the filter’s observations, Z k+1 The observation value of the filter representing the next state of the current state;

[0042] S35, according to the predicted state error value of the current state of the filter, the accuracy of the predicted state error value of the next state of the current state of the filter is evaluated by the fifth formula, wherein the fifth formula is:

[0043]

[0044]

[0045] Among them, P k-1,k Represents the mean square error matrix calculation symbol of the filter in the next state of the current state, P k Represents the mean square error matrix calculation symbol of the filter in the current state, P k The calculation result of represents the accuracy of the predicted state error value of the next state of the current state of the filter, F k-1,k Represents the transfer matrix coefficient of the filter in the next state of the current state, T represents the conversion calculation symbol, The symbol for calculating the conversion of the transfer matrix coefficients of the filter to the next state of the current state, Q represents the result of the filter noise after being processed by the covariance matrix;

[0046] S36, according to the actual measurement value output by the filter in the next state of the current state and the predicted state error value, the predicted state error value is corrected by the sixth formula to obtain the predicted state correction value, wherein the sixth formula is:

[0047]

[0048] P k =(IK k H k ) k-1,k ;

[0049] δx k+1 =δx k-1,k +K k (Z k -H k δx k-1,k );

[0050] Among them, K k Represents the gain matrix calculation symbol of the filter, represents the transposed matrix calculation symbol between the observation quantity and the state quantity of the filter in the current state, R represents the covariance matrix of the measurement noise, δx k-1,k represents the actual measured value of the filter output in the next state of the current state, I represents the unit matrix, δx k+1 It represents the predicted state correction value after the filter corrects the predicted state error value in the next state of the current state.

[0051] The beneficial effect of adopting the above further scheme is: by constructing the tracking channel by the above method, the predicted state correction value of the Doppler frequency in the next state of the current state and the position solution information of the next state of the current state output by the filter can be obtained through the initial state value, and finally the position solution information of the next state of the current state output by the filter is corrected by the predicted state correction value to obtain the target position solution information.

[0052] In a second aspect, the present invention provides a high-dynamic navigation signal radio frequency baseband integrated device, including a first acquisition module, a second acquisition module, a third acquisition module and a fourth acquisition module;

[0053] A first acquisition module is used to acquire the Doppler frequency of the satellite signal in a normal scene mode or a high dynamic scene mode;

[0054] The second acquisition module is used to input the Doppler frequency into the filter and output the initial state value of the position solution information of the Doppler frequency in the current state, wherein the initial state value includes the position coordinates of the satellite, the running speed of the satellite and the time variable;

[0055] A third acquisition module is used to input the initial state value into a preset tracking channel and output a predicted state correction value of the Doppler frequency in the next state of the current state;

[0056] The fourth acquisition module is used to correct the position solution information of the next state of the current state output by the filter through the predicted state correction value to obtain the target position solution information.

[0057] The beneficial effect of the high-dynamic navigation signal RF baseband integrated device provided by the present invention is: by inputting the Doppler frequency in the normal scene mode or the high-dynamic scene mode into the filter, the initial state value of the position solution information of the Doppler frequency in the current state is obtained, and then the initial state value is input into the preset tracking channel to obtain the predicted state correction value of the Doppler frequency in the normal scene mode or the high-dynamic scene mode in the next state of the current state, so as to use the predicted state correction value to correct the position solution information of the next state of the filter output of the current state to obtain the target position solution information. The above method can receive and process satellite signals in the normal scene mode, and can also receive and process satellite signals in the high-dynamic scene mode, which solves the problem that the satellite signal receiving and processing method in the prior art is not suitable for the reception and processing of satellite signals in the high-dynamic scene mode.

[0058] In a third aspect, the present invention further provides an electronic device comprising a memory, a processor, and a program stored in the memory and running on the processor, wherein when the processor executes the program, the steps of the high dynamic navigation signal RF baseband integration method as described above are implemented.

[0059] In a fourth aspect, the present invention further provides a computer-readable storage medium, which stores instructions. When the instructions are executed on a terminal device, the terminal device executes the steps of the high-dynamic navigation signal RF baseband integration method as described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0061] Figure 1 A schematic diagram of a flow chart of a high dynamic navigation signal radio frequency baseband integration method according to an embodiment of the present invention;

[0062] Figure 2 It is a structural schematic diagram of another high dynamic navigation signal radio frequency baseband integration method according to an embodiment of the present invention;

[0063] Figure 3 The results of a simulation experiment on received satellite signals using a conventional method in an embodiment of the present invention;

[0064] Figure 4 The results are simulation results of received satellite signals using a preset tracking channel in an embodiment of the present invention. DETAILED DESCRIPTION

[0065] The following examples are provided to further explain and supplement the present invention and do not constitute any limitation to the present invention.

[0066] The following describes the high dynamic navigation signal radio frequency baseband integration method, device, equipment and medium according to the embodiments of the present invention in conjunction with the accompanying drawings.

[0067] like Figure 1 As shown, the high dynamic navigation signal radio frequency baseband integration method of the embodiment of the present invention includes the following steps:

[0068] S1, obtains the Doppler frequency of the satellite signal in the normal scene mode or the high dynamic scene mode.

[0069] Among them, the difference between the normal scene mode and the high dynamic scene mode is that the range of the Doppler frequency of the satellite signal is different, and the range of the Doppler frequency of the satellite signal in the high dynamic scene mode is wider.

[0070] Specifically, S1 includes the following:

[0071] S11, performing a down-conversion operation on the intermediate frequency signal of the satellite signal to obtain a satellite baseband signal;

[0072] S12, downsampling the satellite baseband signal to obtain a target satellite baseband signal;

[0073] S13, performing coherent accumulation processing on the target satellite baseband signal and the pre-generated PN code to obtain a peak range;

[0074] S14, performing threshold screening processing on the peak range to obtain the Doppler frequency in the normal scene mode or the high dynamic scene mode.

[0075] Optionally, in this embodiment, a preset search step length is set for the Doppler frequency in the normal scene mode or the high dynamic scene mode, and the preset search step length is set by the user according to actual conditions.

[0076] Optionally, in this embodiment, a coherent accumulation time is preset for the Doppler frequency in the normal scene mode or the high dynamic scene mode, and the preset coherent accumulation time is set by the user according to actual conditions.

[0077] S2, input the Doppler frequency into the filter, and output the initial state value of the position solution information of the Doppler frequency in the current state, which includes the position coordinates of the satellite, the running speed of the satellite and the time variable.

[0078] Among them, the satellite's position coordinates represent the coordinate value of the satellite in the filter, the satellite's running speed represents the running speed of the satellite in the filter at the position coordinates, and the time variable represents the time required for light transmission in the filter (obtaining the starting time point and the ending time point).

[0079] S3, inputting the initial state value into a preset tracking channel, and outputting the predicted state correction value of the Doppler frequency in the next state of the current state.

[0080] Specifically, the construction process of the tracking channel is as follows:

[0081] S31, according to the actual code phase, code phase noise, actual carrier frequency and carrier frequency noise obtained by state filtering the initial state value, determine the code phase error and the carrier frequency error by a first formula, wherein the first formula is:

[0082]

[0083]

[0084] in, They represent the code phase error and carrier frequency error of the g-th satellite at time k+1 respectively; represent the actual code phase, the predicted code phase and the code phase noise at time k+1 respectively; They represent the actual carrier frequency, the predicted carrier frequency and the carrier frequency noise at time k+1 respectively;

[0085] S32, according to the code phase error and the carrier frequency error, determine the pseudorange and pseudorange rate error of the initial state value by a second formula, wherein the second formula is:

[0086]

[0087] Where Δρ represents the pseudorange, represents the pseudorange rate error, Δτ g represents the code phase error, Δf g represents the carrier frequency error, f code represents the code rate parameter, f0 represents the carrier frequency parameter, and c represents the speed of light;

[0088] S33, according to the initial state value, the pseudorange and the pseudorange rate error, determine the state error value between the true value and the predicted value of the filter, and the measured value of the filter by a third formula, wherein the third formula is:

[0089] Δx=[δx,δy,δz,cδt b ,δv x ,δv y ,δvy ,cδt d ] T

[0090]

[0091] Among them, Δx represents the state error between the true value and the observed value of the filter, z represents the measured value of the filter, δx, δy, δz represent the difference between the true value and the predicted value of the satellite position coordinates x, y, z in the filter, respectively, and cδt b , cδt d Indicates the filter t b ,t d The difference between the actual value and the predicted value of the total distance traveled by light at time δv x ,δv y ,δv z Respectively represent the difference between the true value and the observed value of the satellite's running speed on the x, y, and z coordinates in the filter, They represent the difference between the true value and the observed value of the pseudorange of each satellite from the 1st satellite to the gth satellite, They represent the difference between the true value and the observed value of the pseudo-range rate error of each satellite from the 1st satellite to the gth satellite, and T represents the conversion calculation symbol;

[0092] S34, determining the predicted state error value according to the initial state value, the state error value and the measured value of the filter by using the fourth formula, wherein the fourth formula is:

[0093] ΔX k+1 =F k,k+1 ΔX k +W k ;

[0094] Z k+1 =H k+1 ΔX k+1 +V k ;

[0095] Where ΔX k+1 Indicates the predicted state error value of the filter in the next state of the current state, X k Indicates the initial state value under the current state, ΔX k The state error value of the initial state value of the filter in the current state, F k,k+1 Indicates the symbol for calculating the transition matrix from the current state to the next state, W k It represents the noise term after the filter performs matrix processing on the noise, H k+1 Represents the projection matrix calculation symbol between the observation quantity and state quantity of the filter, V k represents the noise term of the filter’s observations, Zk+1 The observation value of the filter representing the next state of the current state;

[0096] S35, according to the predicted state error value of the current state of the filter, the accuracy of the predicted state error value of the next state of the current state of the filter is evaluated by the fifth formula, wherein the fifth formula is:

[0097]

[0098]

[0099] Among them, P k-1,k Represents the mean square error matrix calculation symbol of the filter in the next state of the current state, P k Represents the mean square error matrix calculation symbol of the filter in the current state, P k The calculation result of represents the accuracy of the predicted state error value of the next state of the current state of the filter, F k-1,k Represents the transfer matrix coefficient of the filter in the next state of the current state, T represents the conversion calculation symbol, The symbol for calculating the conversion of the transfer matrix coefficients of the filter to the next state of the current state, Q represents the result of the filter noise after being processed by the covariance matrix;

[0100] S36, according to the actual measurement value output by the filter in the next state of the current state and the predicted state error value, the predicted state error value is corrected by the sixth formula to obtain the predicted state correction value, wherein the sixth formula is:

[0101]

[0102] P k =(IK k H k ) k-1,k ;

[0103] δx k+1 =δx k-1,k +K k (Z k -H k δx k-1,k );

[0104] Among them, K k Represents the gain matrix calculation symbol of the filter, represents the transposed matrix calculation symbol between the observation quantity and the state quantity of the filter in the current state, R represents the covariance matrix of the measurement noise, δx k-1,k represents the actual measured value of the filter output in the next state of the current state, I represents the unit matrix, δx k+1It represents the predicted state correction value after the filter corrects the predicted state error value in the next state of the current state.

[0105] Optionally, in this embodiment, two tracking channels are provided, namely a first tracking channel and a second tracking channel. Then the above S3 includes:

[0106] S3, input the initial state value into the preset first tracking channel, output the first predicted state correction value of the Doppler frequency in the next state of the current state, input the initial state value into the preset second tracking channel, and output the second predicted state correction value of the Doppler frequency in the next state of the current state.

[0107] S4, correcting the position solution information of the next state of the current state output by the filter through the predicted state correction value to obtain the target position solution information.

[0108] Optionally, the above S4 includes:

[0109] Compare the first predicted state correction value and the second predicted state correction value, select the smaller predicted state correction value as the target predicted state correction value, use the target predicted state correction value to correct the position solution information of the next state of the current state output by the filter, and obtain the target position solution information.

[0110] After the above steps S1-S4, the received satellite signal is simulated and the following is obtained: Figure 3-Figure 4 The simulation results shown are Figure 3 and Figure 4 The horizontal axis in the table represents time in seconds. Figure 3 and Figure 4 The vertical axes represent instantaneous frequency in Hz. It can be seen that for the filter-based carrier frequency offset evaluation of the satellite signal in any scenario mode, the method of this embodiment has a better effect.

[0111] like Figure 2 As shown, the high dynamic navigation signal radio frequency baseband integrated device of the embodiment of the present invention includes a first acquisition module 202, a second acquisition module 203, a third acquisition module 204 and a fourth acquisition module 205;

[0112] A first acquisition module 202 is used to acquire the Doppler frequency of the satellite signal in a normal scene mode or a high dynamic scene mode;

[0113] The second acquisition module 203 is used to input the Doppler frequency into the filter and output the initial state value of the position solution information of the Doppler frequency in the current state, wherein the initial state value includes the position coordinates of the satellite, the running speed of the satellite and the time variable;

[0114] The third acquisition module 204 is used to input the initial state value into a preset tracking channel and output a predicted state correction value of the Doppler frequency in the next state of the current state;

[0115] The fourth acquisition module 205 is used to correct the position solution information of the next state of the current state output by the filter through the predicted state correction value to obtain the target position solution information.

[0116] Optionally, the first acquisition module 202 includes a satellite band signal acquisition module, a target satellite band signal acquisition module, a peak range acquisition module and a Doppler frequency acquisition module, wherein:

[0117] A satellite band signal acquisition module is used to down-convert the intermediate frequency signal of the satellite signal to obtain a satellite baseband signal;

[0118] The target satellite baseband signal acquisition module is used to downsample the satellite baseband signal to obtain the target satellite baseband signal;

[0119] A peak range acquisition module is used to perform coherent accumulation processing on the target satellite baseband signal and the pre-generated PN code to obtain a peak range;

[0120] The Doppler frequency acquisition module is used to perform threshold screening on the peak range to obtain the Doppler frequency in the normal scene mode or the high dynamic scene mode.

[0121] Optionally, the device further includes a tracking channel construction module for constructing a tracking channel, and the construction method refers to the high-dynamic navigation signal RF baseband integration method mentioned above.

[0122] Optionally, the third acquisition module 204 includes a first predicted state correction value acquisition module and a second predicted state correction value acquisition module, wherein:

[0123] A first predicted state correction value acquisition module is used to input the initial state value into a preset first tracking channel and output a first predicted state correction value of the Doppler frequency in the next state of the current state;

[0124] The second predicted state correction value acquisition module is used to input the initial state value into a preset second tracking channel and output the second predicted state correction value of the Doppler frequency in the next state of the current state.

[0125] Optionally, the fourth acquisition module 205 includes a comparison module and a correction module, wherein:

[0126] A comparison module, used for comparing the first predicted state correction value and the second predicted state correction value, and selecting the smaller predicted state correction value as the target predicted state correction value;

[0127] The correction module is used to correct the position solution information of the next state of the current state output by the filter using the target predicted state correction value to obtain the target position solution information.

[0128] An electronic device according to an embodiment of the present invention comprises a memory, a processor and a program stored in the memory and running on the processor, wherein the processor implements part or all of the steps of any of the above-mentioned automatic image annotation methods when executing the program.

[0129] Among them, the electronic device can be a computer, a mobile phone, etc. Correspondingly, its program is a computer software or a mobile phone APP, etc., and the above-mentioned parameters and steps in an electronic device of the present invention can refer to the parameters and steps in the embodiment of the high-dynamic navigation signal RF baseband integration method above, and will not be repeated here.

[0130] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present disclosure can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, generally referred to as "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code. Computer-readable storage media can be, for example, but not limited to - electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above.

[0131] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0132] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A high dynamic navigation signal radio frequency baseband integration method, characterized in that: The following steps are involved: S1, obtaining the Doppler frequency of the satellite signal in the normal scene mode or the high dynamic scene mode; S2, inputting the Doppler frequency into a filter, and outputting an initial state value of the position solution information of the Doppler frequency in the current state, wherein the initial state value includes the position coordinates of the satellite, the running speed of the satellite, and a time variable; S3, inputting the initial state value into a preset tracking channel, and outputting a predicted state correction value of the Doppler frequency in the next state of the current state; S4, correcting the position solution information of the next state of the current state output by the filter by using the predicted state correction value to obtain the target position solution information; The construction process of the preset tracking channel is as follows: S31, determining a code phase error and a carrier frequency error by a first formula according to an actual code phase, code phase noise, actual carrier frequency and carrier frequency noise obtained by state filtering the initial state value, wherein the first formula is: in, They represent the code phase error and carrier frequency error of the g-th satellite at time k+1 respectively; represent the actual code phase, the predicted code phase and the code phase noise at time k+1 respectively; They represent the actual carrier frequency, the predicted carrier frequency and the carrier frequency noise at time k+1 respectively; S32, determining the pseudorange and pseudorange rate error of the initial state value according to the code phase error and the carrier frequency error by a second formula, wherein the second formula is: Where Δρ represents the pseudorange, represents the pseudorange rate error, Δτ g represents the code phase error, Δf g represents the carrier frequency error, f code represents the code rate parameter, f0 represents the carrier frequency parameter, and c represents the speed of light; S33, determining a state error value between a true value and a predicted value of the filter and a measured value of the filter by a third formula according to the initial state value, the pseudorange and the pseudorange rate error, wherein the third formula is: Δx=[δx,δy,δz,cδt b ,δv x ,δv y ,δv z ,cδt d ] T Among them, Δx represents the state error between the true value and the observed value of the filter, z represents the measured value of the filter, δx, δy, δz represent the difference between the true value and the predicted value of the satellite position coordinates x, y, z in the filter, respectively, and cδt b , cδt d Indicates the filter t b ,t d The difference between the actual value and the predicted value of the total distance traveled by light at time δv x ,δv y ,δv z Respectively represent the difference between the true value and the observed value of the satellite's running speed in the x, y, and z coordinates in the filter, δρ1…,δρ g They represent the difference between the true value and the observed value of the pseudorange of each satellite from the 1st satellite to the gth satellite, They represent the difference between the true value and the observed value of the pseudo-range rate error of each satellite from the 1st satellite to the gth satellite, and T represents the conversion calculation symbol; S34, determining a predicted state error value according to the initial state value, the state error value and the measured value of the filter by using a fourth formula, wherein the fourth formula is: ΔX k+1 =F k,k+1 ΔX k +W k ; With k+1 =H k+1 ΔX k+1 +V k ; Where ΔX k+1 represents the predicted state error value of the filter in the next state under the current state, X represents the initial state value under the current state, ΔX k represents the state error value of the initial state value of the filter in the current state, F k,k+1 Indicates the symbol for calculating the transition matrix from the current state to the next state, W k It represents the noise term after the filter performs matrix processing on the noise, H k+1 Represents the projection matrix calculation symbol between the observation quantity and the state quantity of the filter in the next state of the current state, V k represents the noise term of the filter’s observations, Z k+1 The observation value of the filter representing the next state of the current state; S35, according to the predicted state error value of the current state of the filter, the accuracy of the predicted state error value of the next state of the current state of the filter is evaluated by the fifth formula, wherein the fifth formula is: Among them, P k-1,k Represents the mean square error matrix calculation symbol of the filter in the next state of the current state, P k Represents the mean square error matrix calculation symbol of the filter in the current state, P k The calculation result of represents the accuracy of the predicted state error value of the next state of the current state of the filter. The symbol for calculating the conversion of the transfer matrix coefficients of the filter to the next state of the current state, Q represents the result of the filter noise after being processed by the covariance matrix; S36, according to the actual measurement value output by the filter in the next state of the current state and the predicted state error value, the predicted state error value is corrected by the sixth formula to obtain a predicted state correction value, wherein the sixth formula is: P k =(I-K k H k )P k-1,k ; δx k+1 =δx k-1,k +K k (Z k -H k δx k-1,k ); Among them, K k Represents the gain matrix calculation symbol of the filter, represents the transposed matrix calculation symbol between the observation quantity and the state quantity of the filter in the current state, R represents the covariance matrix of the measurement noise, δx k-1,k represents the actual measured value of the filter output in the next state of the current state, I represents the unit matrix, δx k+1 represents the predicted state correction value after the filter corrects the predicted state error value in the next state of the current state, H k Represents the projection matrix calculation symbol between the observation quantity and the state quantity of the filter in the current state, Z k The observation value of the filter representing the current state.

2. The method according to claim 1, characterized in that The preset tracking channel includes a first tracking channel and a second tracking channel, and the steps S3 and S4 include: S3, inputting the initial state value into a preset first tracking channel, outputting a first predicted state correction value of the Doppler frequency in a next state of the current state, inputting the initial state value into a preset second tracking channel, outputting a second predicted state correction value of the Doppler frequency in a next state of the current state; S4, compare the first predicted state correction value and the second predicted state correction value, select the smaller predicted state correction value as the target predicted state correction value, use the target predicted state correction value to correct the position solution information of the next state of the current state output by the filter, and obtain the target position solution information.

3. The method according to claim 1, characterized in that The satellite signal includes an intermediate frequency signal, and S1 specifically includes: S11, performing a down-conversion operation on the intermediate frequency signal of the satellite signal to obtain a satellite baseband signal; S12, downsampling the satellite baseband signal to obtain a target satellite baseband signal; S13, performing coherent accumulation processing on the target satellite baseband signal and the pre-generated PN code to obtain a peak range; S14, performing threshold screening processing on the peak range to obtain the Doppler frequency in the normal scene mode or the high dynamic scene mode.

4. The method according to claim 3, characterized in that The S13 specifically includes: S13, performing coherent accumulation processing on the target satellite baseband signal and the pre-generated PN code based on a preset search step length and a preset coherent accumulation time to obtain a peak range.

5. High dynamic navigation signal radio frequency baseband integrated device, characterized in that: It includes a first acquisition module, a second acquisition module, a third acquisition module and a fourth acquisition module; The first acquisition module is used to acquire the Doppler frequency of the satellite signal in a normal scene mode or a high dynamic scene mode; The second acquisition module is used to input the Doppler frequency into a filter and output an initial state value of the position solution information of the Doppler frequency in a current state; The third acquisition module is used to input the initial state value into a preset tracking channel and output a predicted state correction value of the Doppler frequency in the next state of the current state; The fourth acquisition module is used to correct the position solution information of the next state of the current state output by the filter through the predicted state correction value to obtain the target position solution information; The third acquisition module is specifically used for: According to the actual code phase, code phase noise, actual carrier frequency and carrier frequency noise obtained by state filtering the initial state value, the code phase error and the carrier frequency error are determined by a first formula, wherein the first formula is: in, They represent the code phase error and carrier frequency error of the g-th satellite at time k+1 respectively; represent the actual code phase, the predicted code phase and the code phase noise at time k+1 respectively; They represent the actual carrier frequency, the predicted carrier frequency and the carrier frequency noise at time k+1 respectively; According to the code phase error and the carrier frequency error, the pseudorange and pseudorange rate error of the initial state value are determined by a second formula, wherein the second formula is: Where Δρ represents the pseudorange, represents the pseudorange rate error, Δτ g represents the code phase error, Δf g represents the carrier frequency error, f code represents the code rate parameter, f0 represents the carrier frequency parameter, and c represents the speed of light; According to the initial state value, the pseudorange and the pseudorange rate error, the state error value between the true value and the predicted value of the filter and the measured value of the filter are determined by a third formula, wherein the third formula is: Δx=[δx,δy,δz,cδt b ,δv x ,δv y ,δv z ,cδt d ] T Among them, Δx represents the state error between the true value and the observed value of the filter, z represents the measured value of the filter, δx, δy, vz represent the difference between the true value and the predicted value of the satellite position coordinates x, y, z in the filter, respectively, and cδt b , cδt d Indicates the filter t b ,t d The difference between the actual value and the predicted value of the total distance traveled by light at time δv x ,δv y ,δv z Respectively represent the difference between the true value and the observed value of the satellite's running speed in the x, y, and z coordinates in the filter, δρ1…,δρ g They represent the difference between the true value and the observed value of the pseudorange of each satellite from the 1st satellite to the gth satellite, They represent the difference between the true value and the observed value of the pseudo-range rate error of each satellite from the 1st satellite to the gth satellite, and T represents the conversion calculation symbol; According to the initial state value, the state error value and the measured value of the filter, the predicted state error value is determined by a fourth formula, wherein the fourth formula is: ΔX k+1 =F k,++1 ΔX k +W k ; With k+1 =H k+1 ΔX k+1 +V k ; Where ΔX k+1 represents the predicted state error value of the filter in the next state under the current state, X represents the initial state value under the current state, ΔX k represents the state error value of the initial state value of the filter in the current state, F k,k+1 Indicates the symbol for calculating the transition matrix from the current state to the next state, W k It represents the noise term after the filter performs matrix processing on the noise, H k+1 Represents the projection matrix calculation symbol between the observation quantity and the state quantity of the filter in the next state of the current state, V k represents the noise term of the filter’s observations, Z k+1 The observation value of the filter representing the next state of the current state; According to the predicted state error value of the current state of the filter, the accuracy of the predicted state error value of the next state of the current state of the filter is evaluated by the fifth formula, wherein the fifth formula is: Among them, P k-1,k Represents the mean square error matrix calculation symbol of the filter in the next state of the current state, P k Represents the mean square error matrix calculation symbol of the filter in the current state, P k The calculation result of represents the accuracy of the predicted state error value of the next state of the current state of the filter. The symbol for calculating the conversion of the transfer matrix coefficients of the filter to the next state of the current state, Q represents the result of the filter noise after being processed by the covariance matrix; S36, according to the actual measurement value output by the filter in the next state of the current state and the predicted state error value, the predicted state error value is corrected by the sixth formula to obtain a predicted state correction value, wherein the sixth formula is: P k =(I-K k H k )P k-1,k ; δx k+1 =δx k-1,k +K k (Z k -H k δx k-1,k ); Among them, K k Represents the gain matrix calculation symbol of the filter, represents the transposed matrix calculation symbol between the observation quantity and the state quantity of the filter in the current state, R represents the covariance matrix of the measurement noise, δx k-1,k represents the actual measured value of the filter output in the next state of the current state, I represents the unit matrix, δx k+1 represents the predicted state correction value after the filter corrects the predicted state error value in the next state of the current state, H k Represents the projection matrix calculation symbol between the observation quantity and the state quantity of the filter in the current state, Z k The observation value of the filter representing the current state.

6. An electronic device comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the steps of the high-dynamic navigation signal radio frequency baseband integration method as described in any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device executes the steps of the high-dynamic navigation signal radio frequency baseband integration method as described in any one of claims 1 to 4.

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