A signal environment statistical method for wideband array multibeam receivers

Abstract

This invention discloses a signal environment statistics method for a broadband array multi-beam receiver, comprising: generating two-dimensional matrix amplitude data of "frequency and beam" based on the array data of the broadband array multi-beam receiver; obtaining the peak search result formed by a single beat based on the two-dimensional matrix amplitude data of "frequency and beam"; estimating the azimuth resolution unit corresponding to the peak search result; obtaining a long pulse frequency descriptor based on the peak search result formed by adjacent beats and its corresponding azimuth resolution unit; reporting the long pulse frequency descriptor based on preset minimum and maximum beat number thresholds; and graphically displaying the reported long pulse frequency descriptor to allow operators to understand the signal environment in the broadband array multi-beam receiver. This invention can output spatiotemporal frequency and energy domain statistical results with moderate data volume, engineering feasibility, and high resolution for operators to understand the signal environment.

Description

Technical Field

[0001] This invention relates to the field of passive radar receiving technology, and in particular to a signal environment statistical method for broadband array multi-beam receivers. Background Technology

[0002] Passive radar does not emit electromagnetic signals itself; instead, it detects and identifies targets by intercepting radar signals from target radiation sources. With the development and widespread use of various electronic devices, the electromagnetic environment has become increasingly complex. Radar signals are often submerged in various communication, interference, and clutter signals, posing significant challenges to operators in assessing the situation and implementing closed-loop management. Therefore, effectively understanding the current signal environment (the energy distribution of various radiation source signals in the dimensions of time, space, and frequency) can help operators focus on current tasks, adjust work strategies in a timely manner, and improve the quality of receiver signal interception.

[0003] Wideband array multibeam receivers are increasingly used in passive radar due to their advantages such as large bandwidth, wide spatial range, and high gain. However, due to their high sampling rate and large number of beams, the amount of data processed in real time is extremely large. Taking 1GHz sampling, 1024-point FFT, and 32 beams as an example, after frequency domain beamforming, the output is 16*10^6 ms / s. 9 Point frequency domain amplitude and phase data. This data provides the most detailed depiction of the energy distribution of the current signal environment in the spatiotemporal frequency dimensions (frequency interval of 1GHz / 1024≈1MHz, time interval of 1024*1 / 1GHz=1.024us, 32 beams). However, such a large amount of data is unacceptable and impossible to directly transmit and graphically display.

[0004] In engineering, reducing the amplitude and phase data after frequency domain beamforming to decrease the data volume is a feasible approach. Maximum hold spectrum is a typical method. Its processing involves: first, taking the maximum value along the beam dimension for the amplitude data of the frequency domain beamforming formed in each cycle; then, through long-term accumulation (typically 200ms, encompassing many cycles), performing maximum hold processing on the amplitude values ​​of each frequency point in different cycles, effectively compressing the data volume. In the paper "An Autocorrelation Method for Extracting Antenna Scanning Period Based on Maximum Hold Spectrum" (Electronic Information Countermeasures Technology, 2018, Vol. 1, by Fan Shengzhao et al.), maximum hold spectrum data can extract the antenna scanning period of strong signals, but the maximum hold processing also results in the loss of a large amount of weak signals. Furthermore, the maximum hold spectrum has a very low temporal resolution for describing the radiation source signal (accumulation time, typically 200ms), and it also loses the azimuth / beam dimension distribution information of the signal, providing operators with a very coarse understanding of the signal environment. Summary of the Invention

[0005] In view of this, the present invention provides a signal environment statistics method for a broadband array multi-beam receiver to solve the above-mentioned technical problems.

[0006] This invention discloses a signal environment statistics method for a broadband array multi-beam receiver, which includes the following steps:

[0007] Step 1: Based on the data of each array element in the broadband array multi-beam receiver, generate two-dimensional matrix amplitude data of "frequency and beam";

[0008] Step 2: Based on the amplitude data of the "frequency, beam" two-dimensional matrix, obtain the peak search result formed by a single beat:

[0009] Step 3: Estimate the azimuth resolution unit corresponding to the peak search result;

[0010] Step 4: Based on the peak search results formed by adjacent beats and their corresponding azimuth resolution units, obtain the long pulse frequency descriptor;

[0011] Step 5: Based on the preset minimum and maximum number of beats thresholds for the long pulse frequency descriptor, report the long pulse frequency descriptor;

[0012] Step 6: Display the reported long pulse frequency description word graphically so that the operator can understand the signal environment in the broadband array multi-beam receiver.

[0013] Further, step 1 includes:

[0014] Data from each array element in a broadband array multi-beam receiver is acquired at a high sampling rate. After broadband signal narrowband segmentation and beamforming processing, two-dimensional matrix amplitude data of "frequency and beam" is generated.

[0015] The amplitude data of the "frequency, beam" two-dimensional matrix is ​​represented as follows:

[0016]

[0017] Where K is the number of effective frequency points in the FFT output spectrum; L is the number of multibeams; and y i,j This represents the signal amplitude received at the i-th frequency point and the j-th beam.

[0018] Further, step 2 includes:

[0019] Step 21: Perform amplitude peak search processing based on the amplitude data of the "frequency, beam" two-dimensional matrix;

[0020] Step 22: By using beamforming and frequency masking, exclude signal amplitude data with known frequency and azimuth from peak search processing;

[0021] Step 23: Sort the amplitude peak search results according to the amplitude size, and output a preset number of peak search results with larger amplitudes.

[0022] Further, step 3 includes:

[0023] The azimuth coverage area of ​​the broadband array multibeam receiver is divided into several azimuth resolution units. Based on the peak search results output in step 2, the corresponding azimuth resolution units are estimated.

[0024] Furthermore, in dividing the azimuth coverage area of ​​the broadband array multi-beam receiver into several azimuth resolution units:

[0025] The broadband array multi-beam receiver uses the amplitude comparison method for angle measurement, which can take the azimuth range pointed to by adjacent beams as a azimuth resolution unit, or further subdivide it into smaller azimuth resolution units.

[0026] Further, step 4 includes:

[0027] The peak amplitudes generated by adjacent beats are correlated and fused based on "frequency and azimuth resolution unit". The fusion result of multiple beats is called a long pulse frequency descriptor, whose elements include {start beat number, end beat number, frequency, maximum frequency point, minimum frequency point, azimuth resolution unit number, amplitude mean, amplitude standard deviation, maximum amplitude value, and minimum amplitude value}.

[0028] Further, step 5 includes:

[0029] Set the minimum and maximum number of beats thresholds for long pulse frequency descriptor reporting;

[0030] During the fusion process, if the long pulse frequency description word exceeds the maximum number of ticks threshold, it will be reported and processed immediately.

[0031] When a long pulse frequency descriptor is not associated with a peak in the next clock cycle, the existing number of clock cycles of the long pulse frequency descriptor is compared with the minimum number of clock cycles threshold. If the existing number of clock cycles exceeds the minimum number of clock cycles threshold, the output is reported.

[0032] Furthermore, the minimum number of beats threshold is a key parameter used to control the amount of data in the long pulse frequency descriptor. The larger the minimum number of beats threshold of the long pulse frequency descriptor, the lower the probability of false alarms of the long pulse frequency descriptor due to random noise, and the lower the overall data amount of the long pulse frequency descriptor in probability.

[0033] Further, step 6 includes:

[0034] LFDW graphical display: The display and control console software receives the reported long pulse frequency description word and displays the time, space, frequency and amplitude information contained in the long pulse frequency description word in a graphical way for the operator to understand the signal environment.

[0035] Because of the adoption of the above technical solution, the present invention has the following advantages:

[0036] 1. Based on the minimum number of beats threshold for reporting LFDW, the amount of data generated for LFDW can be flexibly controlled: When there is only white noise, due to the randomness of amplitude at different frequencies and different beams, the probability of finding the peak multiple times in a row is greatly reduced. The higher the minimum number of beats threshold, the lower the corresponding probability. When there is a signal with a large single frame length / duration, since the multi-beat spectrum data it contains is described by one LFDW data, the total amount of data is greatly compressed compared to the original frequency domain beamforming amplitude and phase data. The corresponding data transmission and graphical display processing also become completely feasible in engineering.

[0037] 2. Compared to the coarse description of the signal environment by the maximum hold spectrum (typical time resolution of 200ms, no azimuth / beam distribution information), the LFDW extracted by this invention contains more complete spatiotemporal frequency and energy distribution description information of the signal environment: the time resolution is consistent with the FFT beat length; the azimuth distribution of the signal is described by dividing it into azimuth resolution units; the frequency distribution information of the LFDW is described, and the frequency resolution is consistent with the FFT frequency resolution; the amplitude information includes mean, standard deviation, maximum value, minimum value, etc., with richer categories. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in the embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0039] Figure 1 This is a flowchart illustrating a signal environment statistics method for a broadband array multi-beam receiver according to an embodiment of the present invention.

[0040] Figure 2 This is a schematic diagram of a graphical display example of LFDW on a display console according to an embodiment of the present invention. Detailed Implementation

[0041] The present invention will be further described in conjunction with the accompanying drawings and embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art should fall within the protection scope of the present invention.

[0042] The following is in conjunction with the appendix Figure 1 Taking a broadband DBF receiver employing frequency domain beamforming and FFT frequency domain detection as an example, the present invention will be described in further detail:

[0043] Step 1: The receiver will process the collected multi-array data through FFT transformation, channel amplitude and phase correction, frequency domain beamforming, etc., to form a two-dimensional amplitude matrix data of "frequency and beam".

[0044]

[0045] Where K is the number of effective frequency points in the FFT output spectrum; L is the number of multibeams; and y i,j This represents the signal amplitude received at the i-th frequency point and the j-th beam;

[0046] Step 2: For the two-dimensional amplitude matrix data, perform peak search processing on a frequency-by-frequency basis. For each frequency point, only select the beam data with the largest amplitude as the peak amplitude data, and record the amplitude data of the left and right adjacent beams. After obtaining the amplitude peaks of all frequency points, sort them according to the amplitude size. Select a maximum of 2 to 4 peak amplitudes with the largest amplitudes for subsequent processing, and discard the rest.

[0047] Meanwhile, operators can set beam masking and frequency masking to exclude strong signals with known frequencies and azimuths from peak search processing, so as to focus on discovering other unknown signals.

[0048] Step 3: Take the azimuth range between adjacent beams as the azimuth resolution unit. Then compare the amplitude value of the peak beam with that of its adjacent beams to determine the azimuth resolution unit where the peak amplitude signal is located. In this way, the four-element statistical information of each peak amplitude is determined, including {current beat number, azimuth resolution unit number, frequency, amplitude}.

[0049] Step 4: The peak amplitude statistics of adjacent beats are correlated based on "azimuth resolution unit number, frequency" and other factors (considering the tolerance of azimuth and frequency, a certain tolerance can be set for correlation, such as a difference of one azimuth resolution unit number or one FFT frequency point, which is also considered a successful correlation). Then, the results are fused to generate multi-beat statistical results, namely the Long Pulse Frequency Description Word (LFDW). The elements include {start beat number, end beat number, frequency, maximum frequency point, minimum frequency point, azimuth resolution unit number, mean amplitude, standard deviation of amplitude, maximum amplitude value, minimum amplitude value}.

[0050] Step 5: Based on the user-defined minimum and maximum clock count thresholds for LFDW reporting, determine whether the current LFDW has finished fusion processing and meets the output conditions, including {start clock number, end clock number, maximum frequency, minimum frequency, azimuth resolution unit number, amplitude mean, amplitude standard deviation, maximum amplitude, and minimum amplitude}. When the LFDW does not associate with a peak value in the next clock, compare the existing clock count of the LFDW with the minimum clock count threshold. Only those exceeding the minimum clock count threshold are reported for output; LFDWs that do not exceed the minimum clock count threshold are discarded. By manually changing the minimum clock count threshold, the amount of data output by the LFDW can be controlled, thereby reducing the amount of data.

[0051] Step 6: The display and control console software receives the reported LFDW data and graphically displays the multi-dimensional information contained in the LFDW data, including time (elements such as start and end beat numbers), space (azimuth resolution unit number), frequency (maximum and minimum frequency points), and amplitude (mean amplitude, standard deviation amplitude, maximum amplitude, and minimum amplitude), for the operator to understand the signal environment; an example of a three-dimensional graphical display is shown below. Figure 2 As shown, the X-axis represents the time beat number, the Y-axis represents the azimuth resolution unit number, the Z-axis represents the frequency, and the amplitude is distinguished by color.

[0052] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A signal environment statistical method for a broadband array multi-beam receiver, characterized in that, Includes the following steps: Step 1: Based on the data of each array element in the broadband array multi-beam receiver, generate two-dimensional matrix amplitude data of "frequency and beam"; Step 2: Based on the amplitude data of the "frequency, beam" two-dimensional matrix, obtain the peak search result formed by a single beat: Step 3: Estimate the azimuth resolution unit corresponding to the peak search result; Step 4: Based on the peak search results formed by adjacent beats and their corresponding azimuth resolution units, obtain the long pulse frequency descriptor; Step 5: Based on the preset minimum and maximum number of beats thresholds for the long pulse frequency descriptor, report the long pulse frequency descriptor; Step 6: Display the reported long pulse frequency description word graphically so that the operator can understand the signal environment in the broadband array multi-beam receiver; Step 1 includes: Data from each array element in a broadband array multi-beam receiver is acquired at a high sampling rate. After broadband signal narrowband segmentation and beamforming processing, two-dimensional matrix amplitude data of "frequency and beam" is generated. The amplitude data of the "frequency, beam" two-dimensional matrix is ​​represented as follows: Where K is the number of effective frequency points in the FFT output spectrum; L is the number of multibeams. Indicates the first The frequency point, the first The amplitude of the signal received by each beam; Step 2 includes: Step 21: Perform amplitude peak search processing based on the amplitude data of the "frequency, beam" two-dimensional matrix; Step 22: By using beamforming and frequency masking, exclude signal amplitude data with known frequency and azimuth from peak search processing; Step 23: Sort the amplitude peak search results according to the amplitude size, and output the 1-4 peak search results with the largest amplitude; Step 3 includes: The azimuth coverage area of ​​the broadband array multibeam receiver is divided into several azimuth resolution units. Based on the peak search results output in step 2, the corresponding azimuth resolution units are estimated. Step 4 includes: The peak amplitudes generated by adjacent beats are correlated and fused based on "frequency and azimuth resolution unit". The fusion result of multiple beats is called a long pulse frequency descriptor, whose elements include {start beat number, end beat number, frequency, maximum frequency point, minimum frequency point, azimuth resolution unit number, amplitude mean, amplitude standard deviation, amplitude maximum value, amplitude minimum value}. Step 5 includes: Set the minimum and maximum number of beats thresholds for long pulse frequency descriptor reporting; During the fusion process, if the long pulse frequency description word exceeds the maximum number of ticks threshold, it will be reported and processed immediately. When a long pulse frequency descriptor is not associated with a peak in the next clock cycle, the existing number of clock cycles of the long pulse frequency descriptor is compared with the minimum number of clock cycles threshold. If the existing number of clock cycles exceeds the minimum number of clock cycles threshold, the output is reported.

2. The method according to claim 1, characterized in that, In dividing the azimuth coverage area of ​​the broadband array multibeam receiver into several azimuth resolution units: The broadband array multi-beam receiver uses amplitude comparison angle measurement, which can treat the azimuth range pointed to by adjacent beams as a azimuth resolution unit.

3. The method according to claim 1, characterized in that, The minimum number of beats threshold is a key parameter used to control the amount of data in the long pulse frequency descriptor. The larger the minimum number of beats threshold of the long pulse frequency descriptor, the lower the probability of false alarms due to random noise, and the lower the overall data amount of the long pulse frequency descriptor.

4. The method according to claim 1, characterized in that, Step 6 includes: Graphical display of long pulse frequency descriptors: The display and control console software receives the reported long pulse frequency descriptors and displays the time, space, frequency, and amplitude information contained in the long pulse frequency descriptors in a graphical manner for the operator to understand the signal environment.

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