Satellite navigation high-precision anti-interference method based on virtual center

Abstract

The invention provides a satellite navigation high-precision anti-interference method based on a virtual center, which realizes space-frequency high-precision anti-interference processing by using an MVDR algorithm based on virtual center constraint on the basis of array antenna and radio frequency channel correction. Comprising a channel consistency correction module, an array antenna receiving module, a down-conversion module, an ADC sampling module, a space-frequency anti-interference processing module and a virtual center constraint module, and realizes high-precision anti-interference processing of satellite navigation signals. According to the invention, the requirement on the isolation degree of the central oscillator and the oscillator is high; on the other hand, four corners of the antenna array are not fully utilized, maximization of the aperture of the array plane is not achieved, and in order to improve the anti-interference performance and the anti-interference number, under the same size condition, eight-array-element array arrangement is adopted, a center array is achieved in a virtual mode, the phase center is convenient to adjust, and high-precision anti-interference is better achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of navigation, in particular to a satellite navigation signal anti-interference method. BACKGROUND

[0002] Global Navigation Satellite System (GNSS) has the characteristics of high satellite orbit and weak satellite signal, and the receiver is easily affected by interference. Array anti-interference technology has been widely used in GNSS anti-interference receivers, which include array antenna, multi-channel radio frequency front end, A / D converter, anti-interference processor and satellite signal receiving processor in the back end.

[0003] The array anti-interference processor can be divided into space, space-time and space-frequency types: the space anti-interference processing is to adjust the directional pattern of the array antenna by weighting and summing the signals received by each antenna element, so as to realize interference suppression by aligning the "null" to the interference direction; the space-time anti-interference processor adds a time domain filter behind each array element channel to suppress interference from two dimensions of time and space, thereby improving the interference suppression capability, especially the wideband interference suppression capability, but the implementation complexity is also greatly increased; the space-frequency anti-interference processing is a suboptimal scheme of space-time anti-interference processing, which converts the time domain data to frequency domain by fast Fourier transform (FFT), and then converts back to time domain after completing the anti-interference processing in frequency domain. The advantage of anti-interference processing in frequency domain is that each frequency point can be processed independently, and the MN×MN dimension (N is the number of array elements, and M is the number of time domain taps) matrix operation of space-time anti-interference processing is reduced to N×N dimension, thereby greatly reducing the implementation complexity.

[0004] The array anti-interference will introduce a carrier phase measurement bias related to the signal incident direction, which will cause the failure of the integer ambiguity fixing of the carrier phase, and limit the application of array anti-interference technology in high-precision measurement field. By using the method of the present application, the measurement bias is reduced or even eliminated by correcting the hardware non-ideal characteristics and using virtual center high-precision anti-interference processing, so as to realize the anti-interference function while meeting the high-precision application requirement. SUMMARY

[0005] In order to overcome the shortcomings of the prior art, the present application provides a satellite navigation high-precision anti-interference method based on virtual center, which uses the MVDR algorithm based on virtual center constraint to realize space-frequency high-precision anti-interference processing on the basis of array antenna and radio frequency channel correction.

[0006] The technical scheme flow of the present application is shown in Figure 2 The present application provides a satellite navigation high-precision anti-interference method based on virtual center, which uses the MVDR algorithm based on virtual center constraint to realize space-frequency high-precision anti-interference processing on the basis of array antenna and radio frequency channel correction.

[0007] The technical scheme adopted by the present application to solve its technical problems comprises the following steps:

[0008] Step 1: complete the virtual center array antenna design, and perform channel consistency correction;

[0009] Step 2: the array antenna receives satellite navigation signals, and the radio frequency module down-converts to obtain analog intermediate frequency signals;

[0010] Step 3: the ADC module samples and processes the intermediate frequency signals, and the sampling rate is greater than 2 times the intermediate frequency frequency;

[0011] Step 4: after the windowing preprocessing of the time domain signals obtained by the multi-channel sampling, N-point FFT transformation is performed to obtain frequency domain signals;

[0012] Step 5: correlation accumulation is performed on each frequency point of the frequency domain signals to obtain an autocorrelation matrix;

[0013] Step 6: solve the anti-interference weighting vector for each frequency point based on the virtual center constraint;

[0014] Step 7: multiply the weighting coefficient by the conjugate of the frequency domain signal to obtain the frequency domain signal after anti-interference processing;

[0015] Step 8: perform N-point inverse FFT transformation on the frequency domain signal after anti-interference processing to obtain the satellite navigation intermediate frequency signal after anti-interference processing.

[0016] In the step 1, the virtual center array antenna adopts virtual center design, and the array has no center element. When performing anti-interference processing, a virtual center element is synthesized, which is convenient for adjusting the phase center of the antenna, and the anti-interference performance and the number of anti-interference elements are comprehensively considered. Under the same size condition, the array is arranged in the form as shown in Figure 1 (a), 1-4 elements are arranged at a distance of 1 wavelength from the center point with an interval angle of 90°, and the starting angle is 45°, and 5-8 elements are arranged at a distance of 1 / 2 wavelength from the center point with an interval angle of 90°, and the starting angle is 0°.

[0017] The channel consistency correction adopts an active correction method, which corrects the array by setting an auxiliary source in the vertical direction of the virtual center of the array to make the amplitude and phase of the signals received by each element consistent.

[0018] In the step 4, the frequency domain signal after the windowing preprocessing and FFT transformation of the time domain signal is represented as:

[0019]

[0020] In the formula, w(n) represents a window function, x i(n) represents the time domain signal of the i-th antenna array element AD, 0 < i < 8, n represents the time domain sampling point, N represents the total number of FFT transform points, X i (k) represents the frequency domain signal of the i-th antenna array element, k represents the frequency domain sampling point, and X represents the array antenna frequency domain signal.

[0021] In the step 5, the autocorrelation matrix of each frequency point of the frequency domain signal is represented as:

[0022]

[0023] In the formula, [R(k)] im is the correlation matrix of the frequency domain signal sampling point k, i and m respectively represent the row number and column number of the correlation matrix, 0 < i, m < 8, the element of the i-th row and the m-th column in the correlation matrix is calculated by the frequency domain signal of the i-th antenna array element and the m-th antenna array element, X i (k, l) represents the sampling point k of the frequency domain signal obtained by the i-th antenna array element frequency domain signal by the l-th FFT transform, X m (k, l) respectively represent the sampling point k of the frequency domain signal obtained by the m-th antenna array element frequency domain signal by the l-th FFT transform, L represents the accumulation number of the correlation matrix, and * represents the conjugate operation.

[0024] In the step 6, the minimum of the output power after the space domain weighting is taken as the optimization target, and the anti-interference weighting vector is solved based on the virtual center constraint, and is represented as:

[0025]

[0026] In the formula, ω(k) represents the anti-interference weighting vector of the k-th frequency point, R -1 (k) is the inverse matrix of R(k), a s (k) is the constraint direction vector of the k-th frequency point, is a s (k) is the conjugate transpose, the virtual center constraint a s (k) takes the value of [1; 1; 1; 1; 0; 0; 0; 0] T or [1; 1; 1; 1; 1; 1; 1; 1] T .

[0027] In the step 7, the frequency domain signal after the anti-interference processing is represented as:

[0028] Y(k) = ω H (k) X(k)

[0029] In the formula, ω H (k) is the conjugate transpose of ω(k), and Y(k) represents the frequency domain signal after the anti-interference.

[0030] The beneficial effect of the present application is that, since the existing high-precision anti-interference array design mostly adopts a uniform circular array arrangement mode, the array pattern is a regular hexagon, contains a center array element, and the antenna phase center may be unstable due to the influence of the antenna array element, and the center array element and the array isolation degree are required to be high; on the other hand, the four corners of the antenna array cannot be fully utilized, and the maximization of the array aperture cannot be realized. In order to improve the anti-interference performance and the number of anti-interference, under the same size condition, the present application adopts an 8-array element array arrangement, the center array element is realized by a virtual mode, the phase center is convenient to adjust, and it is more conducive to high-precision anti-interference. BRIEF DESCRIPTION OF DRAWINGS

[0031] Figure 1 is a schematic diagram of the virtual center antenna array of the present application. Wherein Figure 1 (a) is an antenna array arrangement, Figure 1 (b) is an auxiliary source correction schematic diagram.

[0032] Figure 2 is a flowchart of an anti-interference method.

[0033] Figure 3 is an antenna pattern after anti-interference. DETAILED DESCRIPTION

[0034] The present application will be further described below in combination with the drawings and examples.

[0035] Step 1: adopt the array arrangement mode shown in (a), the auxiliary source is placed in the vertical direction of the center of the antenna array to emit signals, and the relative positional relationship is as shown in (b), measure the received signal phase of each array element, and compensate the phase difference of each array element to be 0. Figure 1 Figure 1 (b) shown, measure the received signal phase of each array element, and compensate the phase difference of each array element to be 0.

[0036] Step 2: test scene arrangement 6 interference sources are uniformly distributed at an interval of 60° around the antenna array, the elevation angle is 10°, and the signal-to-interference ratio is 100dB; taking the BDS-B3I signal as an example, the sampling rate is 62MHz, the spread spectrum code rate is 10.23e6, and the intermediate frequency frequency is 21.52e6MHz.

[0037] Step 3: take the AD data length as 2ms.

[0038] Step 4: pre-process the time domain signal sampled by the AD by using the hamming window function and perform 1024-point FFT transformation:

[0039]

[0040] X(k)=[X1(k)X2(k)…X M (k)] T

[0041] ​In the formula, w takes hamming window function, k is FFT frequency point, 1≤k≤1024;

[0042] Step 5: the autocorrelation matrix of each frequency point is calculated as:

[0043]

[0044] In the formula, i, m represent different array elements, 0<i, j≤8.

[0045] Step 6: the corresponding weighting vector can be obtained by taking the minimum of the spatially weighted output power as the optimization target:

[0046]

[0047] In the formula, the constraint direction vector a s (k) takes [1; 1; 1; 1; 1; 1; 1; 1].

[0048] Step 7: the frequency domain signal after interference suppression processing is Y(k) = ω(k) H X(k).

[0049] Step 8: the satellite navigation intermediate frequency signal after interference suppression is obtained by performing 1024-point inverse FFT on Y.

[0050] The phase centers of different direction satellite signals after interference suppression are stabilized at the virtual center of the antenna array, and the sampling interference suppression weighting vector draws the antenna directional diagram as shown in Figure 3 , which can suppress interference while ensuring the signal reception performance of non-interference directions. The method can meet the requirements of interference suppression performance and high-precision application.

Claims

1. A high-precision anti-interference method for satellite navigation based on virtual center, characterized in that The steps include: Step 1: Complete the virtual center array antenna design and perform channel consistency calibration; Step 2: The array antenna receives the satellite navigation signal, and the RF module down-converts the signal to an analog intermediate frequency signal. Step 3: The ADC module samples and processes the intermediate frequency signal, with a sampling rate greater than 2 times the intermediate frequency; Step 4: After windowing preprocessing, the time domain signal obtained by multi-channel sampling is subjected to N-point FFT transformation to obtain the frequency domain signal; Step 5: Perform correlation accumulation on each frequency point of the frequency domain signal to obtain the autocorrelation matrix; Step 6: Solve the anti-interference weighting vector for each frequency point based on the virtual center constraint; Step 7: Multiply the weighted coefficient by the conjugate of the frequency domain signal to obtain the frequency domain signal after anti-interference processing; Step 8: Perform an N-point inverse FFT transform on the frequency domain signal after anti-interference processing to obtain the anti-interference satellite navigation intermediate frequency signal.

2. The high-precision anti-interference method for satellite navigation based on a virtual center according to claim 1, characterized in that: In the step 1, the virtual center array antenna adopts a virtual center design, and there is no center array on the array surface. The virtual center array is synthesized during the anti-interference processing, which is convenient for adjusting the antenna phase center. At the same time, the anti-interference performance and the number of anti-interferences are comprehensively considered. Under the same size conditions, the array form shown in Figure 1 (a) is adopted. At a distance of 1 wavelength from the center point, arrays No. 1 to No. 4 are arranged at an interval of 90°, with a starting angle of 45°. At a distance of 1 / 2 wavelength from the center point, arrays No. 5 to No. 8 are arranged at an interval of 90°, with a starting angle of 0°.

3. The high-precision anti-interference method for satellite navigation based on virtual center according to claim 1, characterized in that: The channel consistency correction adopts an active correction method, and by setting an auxiliary source in the vertical direction of the virtual center of the array, the array is corrected so that the amplitude and phase of the received signal of each array remain consistent.

4. The high-precision anti-interference method for satellite navigation based on virtual center according to claim 1, characterized in that: The frequency domain signal after the time domain signal in step 4 is pre-processed by windowing and FFT transformation is expressed as: Where, w(n) represents a window function, and x i (n) represents the time-domain signal sampled by the AD of the i-th antenna element, where 0 < i ≤ 8, n represents the time-domain sampling point, N represents the total number of FFT transformation points, and X i (k) represents the frequency-domain signal of the i-th antenna element, k represents the frequency-domain sampling point, and X represents the frequency-domain signal of the array antenna.

5. The high-precision anti-interference method for satellite navigation based on virtual center according to claim 1, characterized in that: In step 5, the autocorrelation matrix of each frequency point of the frequency domain signal is expressed as: Where, [R(k)] im is the correlation matrix related to the k-th sampling point of the frequency-domain signal. i and m respectively represent the row number and column number of the correlation matrix, where 0 < i, m ≤ 8. The element in the i-th row and m-th column of the correlation matrix is calculated from the frequency-domain signals of the i-th and m-th antenna elements. X i (k, l) represents the k-th sampling point of the frequency-domain signal obtained by the l-th FFT transform of the frequency-domain signal of the i-th antenna element. X m (k, l) respectively represent the k-th sampling point of the frequency-domain signal obtained by the l-th FFT transform of the frequency-domain signal of the m-th antenna element. L represents the cumulative number of times of the correlation matrix, and * represents the conjugate operation.

6. The high-precision anti-interference method for satellite navigation based on virtual center according to claim 1, characterized in that: In step 6, the optimization goal is to minimize the weighted output power in the spatial domain. Based on the virtual center constraint, the anti-interference weighted vector is expressed as: Where ω(k) represents the anti-interference weighting vector of the kth frequency point, R -1 (k) is the inverse matrix of R(k), a s (k) is the constraint direction vector of the kth frequency point, for a s (k) Conjugate transpose, virtual center constraint a s (k) takes the value [1; 1; 1; 1; 0; 0; 0; 0] T or [1; 1; 1; 1; 1; 1; 1] T .

7. The high-precision anti-interference method for satellite navigation based on virtual center according to claim 1, characterized in that: In step 7, the frequency domain signal after anti-interference processing is expressed as: Y(k)=ω H (k)X(k) Where, ω H (k) is the conjugate transpose of ω(k), and Y(k) represents the frequency domain signal after anti-interference.

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