High-dynamic navigation signal capturing method

Abstract

The invention discloses a high-dynamic navigation signal capturing method. The method comprises the following steps: initializing capturing parameters; satellite navigation signals are received and collected, and down-conversion and filtering amplification are carried out on data to obtain intermediate-frequency signals; based on the intermediate frequency signal and cosine carrier waves and sine carrier waves generated by a local carrier wave generator, obtaining homodromous and orthogonal dual-channel signals; determining a pseudo-random code sequence corresponding to the current search satellite, selecting different pseudo-random codes to be multiplied by the dual-channel signal, then performing coherent integral accumulation, constructing a complex signal, and converting the complex signal to a frequency domain; determining detection quantities corresponding to different pseudo-random codes, screening the maximum detection quantity, and outputting carrier Doppler frequency shift and pseudo-random code phase information corresponding to the maximum detection quantity based on the relationship between the maximum detection quantity and a capture threshold; and if the maximum detection quantity is smaller than the capture threshold, updating the capture threshold based on the noise power and a preset false alarm rate.

Description

Technical Field

[0001] The invention belongs to the technical field of satellite navigation and positioning, and in particular relates to a high-dynamic navigation signal capture method. Background Art

[0002] As a specific application of spread spectrum communication technology, satellite navigation signals use pseudo-random codes for spread spectrum modulation, support code division multiple access and arbitrary site selection, and have the advantages of anti-interference, anti-fading, low transmission power and high spectrum utilization. In the implementation of navigation receivers, only after successful completion of capture and tracking can the receiver extract the message in the navigation signal, thereby ensuring the normal operation of subsequent positioning and speed measurement functions. As the primary link of the baseband processing module, the capture module not only determines whether the receiver can correctly search for satellite signals, but also directly affects the effect of the tracking module. Therefore, the capture module plays an extremely important role in the navigation receiver.

[0003] Signal capture completes the search of the uncertainty range of code phase and Doppler frequency shift by performing two-dimensional search in the time domain and frequency domain. Usually, the entire uncertainty range is divided into multiple search units, each unit corresponding to a specific code phase offset and Doppler frequency shift. The receiver generates a local signal based on these offsets and mixes and correlates it with the received signal. When the correlation value exceeds the set threshold, it is determined that the signal exists, completing the initial synchronization of the local signal and the received signal, and serving as the initial condition for tracking.

[0004] The capture algorithm mainly includes three links: correlation, search and judgment. Each link involves multiple processing parameters, such as search interval, coherent integration time and capture threshold. Among them, the length of the coherent integration time directly affects the capture sensitivity of the signal, and the setting size of the capture threshold will affect the false alarm rate and detection probability of the signal. The current navigation signal capture technology usually adopts the method of fixing these processing parameters. However, under high dynamic conditions, the working environment of the receiver will change at any time. The size of the fixed capture threshold will not be able to dynamically adapt to the complex and changing signal environment. For example, in the case of large fluctuations in signal strength or unstable interference, the capture efficiency and accuracy are difficult to guarantee; in an environment with low signal strength or high noise, the fixed coherent integration time may cause capture failure, thereby reducing the real-time performance of the navigation system. Therefore, the existing capture method still has deficiencies in flexibility, adaptability and stability. Summary of the invention

[0005] The purpose of the present invention is to provide a high-dynamic navigation signal capture method to solve the problem that traditional capture methods cannot dynamically adjust their own parameters under different environments, resulting in low capture efficiency and accuracy.

[0006] In order to achieve the above tasks, the present invention adopts the following technical solutions:

[0007] A high-dynamic navigation signal acquisition method, comprising:

[0008] Step 1, initialize capture parameters;

[0009] Step 2, receiving and collecting satellite navigation signals, down-converting, filtering and amplifying the data to obtain intermediate frequency signals;

[0010] Step 3, obtaining a co-directional and orthogonal dual-channel signal based on the intermediate frequency signal and a cosine carrier and a sine carrier generated by a local carrier generator;

[0011] Step 4, determining the pseudo-random code sequence corresponding to the currently searched satellite, sliding the pseudo-random code sequence using a sliding window to adjust the phase of the pseudo-random code; multiplying the pseudo-random code at each sliding window position with the co-directional, orthogonal dual-channel signal;

[0012] Step 5, performing coherent integration accumulation for a preset coherent integration time on the multiplied in-phase and orthogonal dual-channel signals, and outputting two-way coherent accumulation values; constructing a complex signal based on the two-way coherent accumulation values;

[0013] Step 6, performing fast Fourier transform on the complex signal to convert it into a frequency domain signal;

[0014] Step 7, repeating steps 4-6 for each pseudo-random code, determining the detection amount calculated using the frequency domain signal under different pseudo-random codes and carrier Doppler frequency shifts, and determining the maximum detection amount therefrom;

[0015] Step 8, compare the maximum detection amount with the capture threshold. If the maximum detection amount is greater than the capture threshold, output the carrier Doppler frequency shift and pseudo-random code phase information corresponding to the maximum detection amount; if the maximum detection amount is less than the capture threshold, update the capture threshold based on the noise power and the preset false alarm rate.

[0016] Further, the intermediate frequency signal described in step 2 is expressed as:

[0017]

[0018] Among them, t is the time parameter, P s is the signal power, D(t) is the data code, τ1 is the data code delay, C(t) is the pseudo-random code, τ2 is the pseudo-random code delay, f IF is the intermediate frequency carrier frequency, φ0 is the initial phase, n(t) is Gaussian white noise, and obeys N(0,σ 2 ) distribution, σ 2 represents the variance of the distribution;

[0019] The in-phase and quadrature dual channel signals i0(t) and q0(t) described in step 3 are expressed as:

[0020]

[0021] where f e is the carrier Doppler shift of the intermediate frequency signal, φ is the initial phase of the cosine carrier and the sine carrier, δφ=φ0-φ;

[0022] The multiplication of the pseudo-random code at each sliding window position and the co-directional and orthogonal dual-channel signal in step 4 is expressed as:

[0023]

[0024] in represents a pseudo-random code, Delay for generating pseudo-random code.

[0025] Furthermore, the coherent integration accumulation of the multiplied in-phase and orthogonal dual-channel signals for a preset coherent integration time is performed in step 5, and two coherent accumulation values ​​are output; and a complex signal is constructed based on the two coherent accumulation values, including:

[0026]

[0027] Then, a complex signal is constructed based on the two coherent accumulation values ​​i(n) and q(n):

[0028]

[0029] Among them, the data code D(t-τ1) is in the integration time T coh The inside remains unchanged, so it is represented by a sampling point D(n); R(·) is the pseudo-random code autocorrelation function, t1 is the integration start time, T coh is the coherent integration time, j is the imaginary unit, and e is a natural constant.

[0030] Furthermore, the time domain complex signal i(n)+jq(n) is converted into a frequency domain signal as the detection quantity after fast Fourier transform: n=[0,N-1], I(k) and Q(k) are the real and imaginary parts after fast Fourier transform, n is an index variable, ranging from 0 to N-1, and N is the number of carrier Doppler frequency shift points to be searched;

[0031]

[0032] Among them I i (k), Q i (k) represent the frequency domain signals I(k) and Q(k) calculated from the i-th pseudo-random code phase and the k-th carrier Doppler shift, respectively. V i,kIndicates the corresponding detection amount; and determines the maximum detection amount

[0033]

[0034] Furthermore, in step 8, the counting variable and the coherent integration time are updated simultaneously while updating;

[0035] Compare whether the counting variable K is equal to the counting threshold value A to decide whether to continue searching for the current satellite; if K=A, determine that the received signal does not contain the current satellite information, and continue to search for the carrier Doppler frequency shift and pseudo-random code phase information of the next satellite signal until all satellites are searched and enter the tracking state; if K≠A, return to step 3.

[0036] Furthermore, the initialization capture parameters include the coherent integration time T coh , counting variable K, counting threshold value A, false alarm rate P fα and capture threshold V t .

[0037] Furthermore, the sliding window slides on the pseudo-random code sequence in a step size of 1 / 2 chip.

[0038] Furthermore, the noise power is determined as follows:

[0039]

[0040] Furthermore, the formula for updating the capture threshold is:

[0041]

[0042] Among them, P fα represents the false alarm rate, σ n represents the noise standard deviation.

[0043] A receiver includes a radio frequency front end and a capture module; wherein the radio frequency front end is used to implement the function of step 2 in the high-dynamic navigation signal capture method, and the functions of the remaining steps are implemented by the capture module.

[0044] A terminal device comprises a processor, a memory and a computer program stored in the memory; wherein when the processor executes the computer program, the high-dynamic navigation signal capture method is implemented.

[0045] A computer-readable storage medium stores a computer program; the computer program is characterized in that when executed by a processor, the high-dynamic navigation signal capture method is implemented.

[0046] Compared with the prior art, the present invention has the following technical features:

[0047] The present invention introduces an adaptive threshold algorithm, utilizes real-time signal feature analysis and self-parameter adjustment, realizes dynamic adjustment of the navigation signal capture threshold, adapts to signals of different strengths and noise levels, improves the capture probability of navigation signals of different strengths, especially weak signals, and ensures capture sensitivity; provides accurate initial conditions for subsequent signal tracking, improves the overall dynamic performance of the receiver, and can provide users with more stable and reliable navigation services. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of the navigation signal capture principle and structure based on adaptive threshold;

[0049] Figure 2 It is a flowchart of the adaptive capture threshold workflow;

[0050] Figure 3 It is a comparison diagram of detection probabilities of an adaptive capture threshold and a constant capture threshold under different signal-to-noise ratios in one embodiment of the present invention. DETAILED DESCRIPTION

[0051] The present invention provides a high-dynamic navigation signal capture method, which realizes efficient and accurate capture of high-dynamic navigation signals with different signal strengths by adding a capture threshold update module on the basis of a parallel frequency capture method. The specific steps of the present invention are as follows:

[0052] Step 1: The receiver capture module initializes capture parameters, including: coherent integration time T coh , counting variable K, counting threshold value A, false alarm rate P fα and capture threshold V t .

[0053] The coherent integration time T coh The length of will affect the power of the subsequent coherent integration output signal, and its value is an integer multiple of 1 millisecond, that is, an integer multiple of the pseudo-random code period, and the initial value is set to 1ms; the counting variable K is used to count the number of capture threshold updates. When a certain number of times is reached, it is determined that the received signal does not contain the current satellite information, and the initial value is set to 1; the counting threshold value A determines the number of updates and is set according to actual requirements; since false alarm events often mean continuing the subsequent traction and tracking process for non-existent signals, the hardware overhead and time overhead of these processes are very large, and the false alarm rate P needs to be set in advance according to actual requirements. fα , and set the corresponding initial capture threshold V according to the false alarm rate and the estimated received signal noise ratio t .

[0054] Step 2: The receiver RF front end receives and collects satellite navigation signals, down-converts, filters and amplifies the data to obtain an intermediate frequency signal. t is the time parameter, P s is the signal power, D(t) is the data code, τ1 is the data code delay, C(t) is the pseudo-random code, τ2 is the pseudo-random code delay, f IF is the intermediate frequency carrier frequency, φ0 is the initial phase, n(t) is Gaussian white noise, and obeys N(0,σ 2 ) distribution, σ 2 Represents the variance of the distribution.

[0055] Step 3: The receiver capture module captures the intermediate frequency signal s IF (t) respectively with the cosine carrier generated by the local carrier generator Sine carrier Multiply to form in-phase and quadrature dual channel signals i0(t) and q0(t):

[0056]

[0057] where f e is the carrier Doppler shift of the intermediate frequency signal, φ is the initial phase of the cosine carrier and the sine carrier, δφ=φ0-φ.

[0058] Step 4: The receiver capture module determines the pseudo-random code sequence corresponding to the current search satellite, and uses a sliding window to slide on the pseudo-random code sequence in steps of 1 / 2 chip to adjust the phase of the pseudo-random code. A pseudo-random code is obtained at the initial position of the sliding window and after each sliding. Until the entire pseudo-random code sequence is experienced;

[0059] The in-phase and quadrature dual channel signals i0(t) and q0(t) are respectively combined with the phase-adjustable pseudo-random code generated by the local code generator. Multiply them to get i1(t) and q1(t):

[0060]

[0061] in Delay for generating pseudo-random code.

[0062] Step 5: The receiver capture module performs coherent integration time T on the dual-channel signals multiplied by the pseudo-random code. coh The coherent integral accumulation of , outputs two coherent accumulation values ​​i(n) and q(n):

[0063]

[0064] Then, a complex signal is constructed based on the two coherent accumulation values ​​i(n) and q(n):

[0065]

[0066] Among them, since the data code D(t-τ1) is in the integration time T coh It remains unchanged during the period, so its value during this period can be represented by a sampling point D(n); R(·) is the pseudo-random code autocorrelation function, Δτ=τ 2- t1 is the integration start time, T coh is the coherent integration time, j is the imaginary unit, and e is a natural constant.

[0067] Step 6: The receiver capture module performs FFT on the obtained complex signal. The time domain complex signal i(n)+jq(n) is converted into a frequency domain signal after fast Fourier transform: n=[0,N-1], I(k) and Q(k) are the real part and imaginary part after fast Fourier transform respectively, n is the index variable, ranging from 0 to N-1, N is the number of carrier Doppler frequency shift points to be searched; each FFT corresponds to N points.

[0068] Step 7: Repeat steps 4-6 for each pseudo-random code in step 4 to calculate the detection amount Among them I i (k), Q i (k) represent the frequency domain signals I(k) and Q(k) calculated from the i-th pseudo-random code phase and the k-th carrier Doppler shift, respectively. V i,k Indicates the corresponding detection amount; and determines the maximum detection amount

[0069] Step 8: The receiver capture module compares the maximum detection quantity T m and capture threshold V t The size of T m >V t , output the carrier Doppler frequency shift f corresponding to the maximum detection amount e and pseudo-random code phase information τ2; if T m <V t , since each detection quantity V calculated in step 7 i,k are both less than the capture threshold V t , and because most of these values ​​are obtained when there is no signal, that is, these detection values ​​are basically all from noise, so averaging these values ​​can get a more reliable noise power σ n 2 , according to Parseval's theorem, we have False alarm rate P fα Given in advance, according to the calculated noise standard deviation σ n Updateable capture threshold At the same time, the counting variable K=K+1 is updated, and the coherent integration time T coh =K×1ms.

[0070] Step 9: The receiver capture module compares whether the counting variable K is equal to the counting threshold value A to determine whether to continue searching for the current satellite; if K = A, it is determined that the received signal does not contain the current satellite information, and the carrier Doppler frequency shift f of the next satellite signal is searched. e and the pseudo-random code phase information τ2 until all satellites are searched and then enter the tracking state; if K≠A, return to step 3.

[0071] Figure 1 This is a schematic diagram of the navigation signal capture principle and structure based on adaptive threshold. The digital intermediate frequency signal is first mixed with the replica carrier on the in-phase branch and the orthogonal branch, and then the mixing result is multiplied with the replica pseudo-random code. Then the correlation result is Fourier transformed after coherent integration and its modulus value is taken. Finally, the maximum detection amount is compared with the capture threshold to determine whether to update the capture threshold.

[0072] Figure 2 This is the workflow diagram of adaptive capture threshold. First, the capture parameters are initialized. Since the signal strength fluctuates greatly under high dynamic conditions, the capture threshold setting may no longer be suitable for real-time signal characteristics and must be determined step by step through iteration. The iterative process is: calculate each detection quantity and find the maximum value T m , compare the maximum detection value T m and capture threshold V t The size of T m >V t , output the carrier Doppler frequency shift and pseudo-random code phase information corresponding to the maximum detection amount; if T m <V t , update the capture parameters. If the counting variable K reaches the threshold value A, it is determined that the received signal does not contain the current satellite information, and the search for the next satellite continues until all satellites are searched and the tracking state is entered.

[0073] Figure 3 The counting threshold value A is 8, and the false alarm rate P fα When is 0.0001, the detection probability comparison diagram of adaptive capture threshold and constant capture threshold under different signal-to-noise ratios.

[0074] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A high-dynamic navigation signal capture method, characterized in that: include: Step 1, initialize capture parameters; Step 2, receiving and collecting satellite navigation signals, down-converting, filtering and amplifying the data to obtain intermediate frequency signals; Step 3, obtaining a co-directional and orthogonal dual-channel signal based on the intermediate frequency signal and a cosine carrier and a sine carrier generated by a local carrier generator; Step 4, determining the pseudo-random code sequence corresponding to the currently searched satellite, sliding the pseudo-random code sequence using a sliding window to adjust the phase of the pseudo-random code; multiplying the pseudo-random code at each sliding window position with the co-directional, orthogonal dual-channel signal; Step 5, performing coherent integration accumulation for a preset coherent integration time on the multiplied in-phase and orthogonal dual-channel signals, and outputting two-way coherent accumulation values; constructing a complex signal based on the two-way coherent accumulation values; Step 6, performing fast Fourier transform on the complex signal to convert it into a frequency domain signal; Step 7, repeating steps 4-6 for each pseudo-random code, determining the detection amount calculated using the frequency domain signal under different pseudo-random codes and carrier Doppler frequency shifts, and determining the maximum detection amount therefrom; Step 8, compare the maximum detection amount with the capture threshold. If the maximum detection amount is greater than the capture threshold, output the carrier Doppler frequency shift and pseudo-random code phase information corresponding to the maximum detection amount; if the maximum detection amount is less than the capture threshold, update the capture threshold based on the noise power and the preset false alarm rate.

2. The high dynamic navigation signal capture method according to claim 1, characterized in that: The intermediate frequency signal described in step 2 is expressed as: Among them, t is the time parameter, P s is the signal power, D(t) is the data code, τ1 is the data code delay, C(t) is the pseudo-random code, τ2 is the pseudo-random code delay, f IF is the intermediate frequency carrier frequency, φ0 is the initial phase, n(t) is Gaussian white noise, and obeys N(0,σ 2 ) distribution, σ 2 represents the variance of the distribution; The in-phase and quadrature dual channel signals i0(t) and q0(t) described in step 3 are expressed as: where f e is the carrier Doppler shift of the intermediate frequency signal, φ is the initial phase of the cosine carrier and the sine carrier, δφ=φ0-φ; The multiplication of the pseudo-random code at each sliding window position and the co-directional and orthogonal dual-channel signal in step 4 is expressed as: in represents a pseudo-random code, Delay for generating pseudo-random code.

3. The high dynamic navigation signal capture method according to claim 1, characterized in that: The step 5 of performing coherent integration accumulation for a preset coherent integration time on the multiplied in-phase and orthogonal dual-channel signals, and outputting two coherent accumulation values; and constructing a complex signal based on the two coherent accumulation values, includes: Then, a complex signal is constructed based on the two coherent accumulation values ​​i(n) and q(n): Among them, the data code D(t-τ1) is in the integration time T coh The inside remains unchanged, so it is represented by a sampling point D(n); R(·) is the pseudo-random code autocorrelation function, t1 is the integration start time, T coh is the coherent integration time, j is the imaginary unit, and e is a natural constant.

4. The high dynamic navigation signal capture method according to claim 1, characterized in that: The time domain complex signal i(n)+jq(n) is converted into a frequency domain signal as the detection quantity after fast Fourier transform: n=[0,N-1], I(k) and Q(k) are the real and imaginary parts after fast Fourier transform, n is an index variable, ranging from 0 to N-1, and N is the number of carrier Doppler frequency shift points to be searched; Among them I i (k), Q i (k) represent the frequency domain signals I(k) and Q(k) calculated from the i-th pseudo-random code phase and the k-th carrier Doppler shift, respectively. V i,k Indicates the corresponding detection amount; and determines the maximum detection amount 5. The high dynamic navigation signal capture method according to claim 1, characterized in that: The step 8 simultaneously updates the counting variable and the coherent integration time while updating; Compare whether the counting variable K is equal to the counting threshold value A to decide whether to continue searching for the current satellite; if K=A, determine that the received signal does not contain the current satellite information, and continue to search for the carrier Doppler frequency shift and pseudo-random code phase information of the next satellite signal until all satellites are searched and enter the tracking state; if K≠A, return to step 3.

6. The high dynamic navigation signal capture method according to claim 1, characterized in that: The initialization acquisition parameters include the coherent integration time T coh , counting variable K, counting threshold value A, false alarm rate P fα and capture threshold V t .

7. The high dynamic navigation signal capture method according to claim 1, characterized in that: The process of determining the noise power is:

8. The high dynamic navigation signal capture method according to claim 1, characterized in that: The formula for updating the capture threshold is: Among them, P fα represents the false alarm rate, σ n represents the noise standard deviation.

9. A receiver, comprising a radio frequency front end and a capture module; characterized in that: The radio frequency front end is used to implement the function of step 2 in the high-dynamic navigation signal capture method according to any one of claims 1-8, and the functions of the remaining steps are implemented by the capture module.

10. A computer-readable storage medium, wherein a computer program is stored in the medium; characterized in that: When the computer program is executed by a processor, the high-dynamic navigation signal acquisition method according to any one of claims 1-8 is implemented.

Images