A weak signal high resolution direction finding method of random passive matched filtering

Abstract

The present application belongs to the field of radio direction finding, and particularly relates to a weak signal high resolution direction finding method of random passive matched filtering. According to the direction finding device and the related parameters of random matched filtering, the array receiving signal of the direction finding device and the reference signal of passive matched filtering are determined; then the random matched filtering sample extraction matrix is determined, and the reference signal of random matched filtering is determined from the reference signal of passive matched filtering according to the random matched filtering sample extraction matrix; then the snapshot signal outputted by random matched filtering and its autocorrelation matrix are determined from the reference signal of random matched filtering and the array receiving signal of the direction finding device; finally, the high resolution spatial spectrum is determined from the autocorrelation matrix, and the direction finding result of random passive matched filtering is determined from the spectral peak position of the high resolution spatial spectrum. The present application can realize the purpose of improving the resolution capability and direction finding precision of signals with similar directions of arrival under the condition of low signal to noise ratio.

Description

Technical Field

[0001] This invention belongs to the field of radio direction finding, specifically relating to a high-resolution direction finding method for weak signals using random passive matched filtering, and more specifically, a method for high-resolution direction finding of weak signals that are difficult to distinguish in the time and spatial domains using random passive matched filtering under strong signal backgrounds. Background Technology

[0002] Matched filtering is a commonly used method for signal detection. By using known waveform information of the signal to perform matched filtering on the received signal, the signal-to-noise ratio gain can be obtained, thereby improving the detection capability of weak signals at long distances and the accuracy of parameter estimation.

[0003] In applications where passive signal processing, such as receiving signals using antenna arrays and performing conventional beamforming, is employed, the waveforms of each signal component in the received signal are often not precisely known. Therefore, it is difficult to directly obtain signal-to-noise ratio (SNR) gain through matched filtering. However, in the increasingly complex electromagnetic spectrum, the received signal contains multiple signal components arriving at the same frequency, at different times, and from different directions, and these components exhibit significant correlation. In such cases, passive signal processing methods, failing to utilize the correlation between multiple signal components in the received signal, still have considerable room for improvement in their ability to detect weak, long-range signals and the accuracy of parameter estimation. Therefore, in recent years, many methods have been developed that utilize strong signals with high SNR in the received signal for passive matched filtering, achieving a certain SNR gain and thus improving the detection capability and parameter estimation accuracy of weak, long-range signals with low SNR.

[0004] However, when there is more than one weak, long-range signal with a low signal-to-noise ratio in the received signal and their frequency domains completely overlap, passive spatial-temporal joint processing is required to distinguish and estimate the arrival time and direction of arrival of multiple weak, long-range signals. Since the received signal, after passive matched filtering, only one snapshot data point corresponds to each arrival time, conventional beamforming direction-finding methods suitable for a single snapshot data point are insufficient to distinguish multiple weak, long-range signals with similar directions of arrival, leading to direction-finding failure.

[0005] Therefore, it is necessary to develop a new passive signal processing method when performing passive matched filtering on the received signal. If multiple snapshots can be obtained for a given arrival time, a high-resolution beamforming method suitable for multiple snapshots can be used to distinguish multiple weak long-range signals with similar directions of arrival. This combines the passive matched filtering method with the high-resolution direction finding method, thereby improving the ability to distinguish and perform direction finding on multiple signals with similar directions of arrival under low signal-to-noise ratio conditions. Summary of the Invention

[0006] This invention addresses the problem that after passive matched filtering, the received signal only has one snapshot data for a given arrival time. It proposes a high-resolution direction finding method for weak signals using random matched filtering, which can obtain multiple equivalent snapshot data for a given arrival time. This improves the resolution and direction finding accuracy of multiple signals with similar directions of arrival under low signal-to-noise ratio conditions.

[0007] The technical solution of this invention is as follows:

[0008] A high-resolution direction finding method for weak signals using random passive matched filtering (RQR) is disclosed. First, the number of antennas, the number of search directions, the set of search directions, and the set of direction vectors corresponding to the search direction set are set for the direction finding device. The number of snapshots of the array received signal from the direction finding device, the number of samples of the reference signal for RQR, and the number of snapshots of the output signal from RQR are also set. Second, the array received signal and the reference signal for RQR are determined. Then, the RQR sample extraction matrix is ​​determined, and the RQR reference signal is determined from the RQR reference signal based on the RQR sample extraction matrix. Next, the snapshot signal output by RQR and its autocorrelation matrix are determined using the RQR reference signal and the array received signal from the direction finding device. Finally, the high-resolution spatial spectrum is determined from the autocorrelation matrix, and the direction finding result of RQR is determined from the spectral peak positions of the high-resolution spatial spectrum.

[0009] The present invention specifically includes the following steps:

[0010] S1. Set the number of antennas for the direction finding device to... The number of search directions is Search direction is , and search direction The direction vectors that correspond one-to-one are The number of snapshots for the direction finding equipment's array to receive signals is The number of reference signal samples for random matched filtering is And the number of snapshots of the signal output by the random matched filter is ;

[0011] S2. Determine the array received signal of the direction finding equipment as... 1-th order matrix The reference signal for passive matched filtering is rank vector ;

[0012] S3. Then determine the random matched filter sample extraction matrix as follows: 1-th order matrix , In the matrix Each line From n elements, one element is randomly selected as 1, and the other elements are zero. The probability of selecting a 1 for each element is 1 / 2. Based on the random matched filtering sample extraction matrix and the passive matched filtering reference signal, the reference signal for random matched filtering is determined as follows: ;

[0013] S4. Based on the reference signal from the random matched filter and the array received signal from the direction-finding device, determine the snapshot signal output by the random matched filter as follows:

[0014] ,

[0015] in, This is the transpose of the vector. The conjugate of the vectors is given by the autocorrelation matrix.

[0016] ,

[0017] in, It is the conjugate transpose of the vector;

[0018] S5. Determine the set of search directions using the autocorrelation matrix. The high-resolution spatial spectrum corresponding to each search direction is:

[0019]

[0020] in, The inverse of the matrix. Then determine the maximum value of the high-resolution spatial spectrum. And iterate through the spectral peak positions to search the set. For each search direction, determine whether three inequalities are satisfied simultaneously.

[0021]

[0022] The search direction is , ,in, For integers, satisfying , To satisfy the inequality The number of search directions; finally, the direction finding results of the random passive matched filtering are determined as a set. The search direction.

[0023] The beneficial effects of this invention are as follows: The low-resolution direction finding method for weak signals using random passive matched filtering can not only enhance the accuracy of low-resolution direction finding by utilizing random passive matched filtering, but also increase the snapshot data required for high-resolution direction finding by using random matched filtering, thereby enhancing the resolution of low-resolution direction finding. Thus, under low signal-to-noise ratio conditions, it can improve the resolution and direction finding accuracy of multiple signals with similar incoming wave directions. It is suitable for passive radio direction finding situations where long-range weak signals and short-range strong signals are mixed in time and frequency, and where strong direct wave signals from external radiation sources and weak echo signals reflected from targets are mixed. Detailed Implementation

[0024] The practicality of the present invention will be analyzed below with reference to the embodiments.

[0025] Example: In this example, the number of antennas for the direction-finding device is set. =8. Number of search directions =360 degrees and the set of search directions is {0,1,…,358,359} degrees, and the set of direction vectors corresponding one-to-one with the search directions is {a(0),a(1),…,a(358),a(359)}, the array receiving signal snapshot number of the direction finding equipment is L=250; the number of reference signal samples for random matched filtering is =125 and the number of snapshots of the signal output from the random matched filter is =32. The direction of arrival of the strong signal is 225 degrees, and the signal-to-noise ratio is 32.04dB. The directions of arrival of the weak signal are 80 degrees and 90 degrees, and the time delays are 7.3 and 7.5 microseconds, respectively. The signal-to-noise ratio of both is 6.36dB, which is 25.68dB lower than that of the strong signal.

[0026] Conventional beamforming direction finding methods only show peaks near the direction of strong signals, failing to detect the two weak signals because no peaks satisfying the three inequality conditions are found near the two weak signal directions. Passive spatial-temporal joint processing methods show only one peak satisfying the three inequality conditions near the two weak signal directions, also failing to distinguish the two weak signals. If the nearest peak position is used to determine the weak signal direction, the absolute value of the direction finding error for the two weak signals averages over 7 degrees. However, the high-resolution weak signal direction finding method using random passive matched filtering of this invention shows peaks satisfying the three inequality conditions near both the direction of strong signals and the two weak signal directions, with an average direction finding error of less than 1 degree for the two weak signals. This achieves the goal of improving the resolution and direction finding accuracy of multiple signals with similar incoming directions under low signal-to-noise ratio conditions.

Claims

1. A high-resolution direction finding method for weak signals using random passive matched filtering, characterized in that, Includes the following steps: S1. Set the number of antennas for the direction finding device to... The number of search directions is Search direction is , and search direction The direction vectors that correspond one-to-one are The number of snapshots for the direction finding equipment's array to receive signals is The number of reference signal samples for random matched filtering is And the number of snapshots of the signal output by the random matched filter is ; S2, Define the array receiving signal of the direction finding device as... 1-th order matrix The reference signal for passive matched filtering is rank vector ; S3. Define the random matched filter sample extraction matrix as follows: 1-th order matrix , In the matrix Each line From n elements, one element is randomly selected as 1, and the other elements are zero. The probability of selecting a 1 for each element is 1 / 2. Based on the random matched filtering sample extraction matrix and the passive matched filtering reference signal, the reference signal for random matched filtering is determined as follows: ; S4. Based on the reference signal from the random matched filter and the array received signal from the direction-finding device, determine the snapshot signal output by the random matched filter as follows: ， in, This is the transpose of the vector. Given the conjugate of the vectors, the autocorrelation matrix is: ， in, It is the conjugate transpose of the vector; S5. Determine the set of search directions using the autocorrelation matrix. The high-resolution spatial spectrum corresponding to each search direction is: ， in, The inverse of the matrix. Then determine the maximum value of the high-resolution spatial spectrum. And iterate through the spectral peak positions to search the set. For each search direction, determine whether three inequalities are satisfied simultaneously. ， The search direction is , ,in, For integers, satisfying , To satisfy the inequality The number of search directions; finally, the direction finding results of random passive matched filtering are obtained as a set. The search direction.

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