Method and system for generating visual views based on directional interferometer array data

Abstract

The application discloses a kind of visualization view generation method and system based on directional interferometer array data, which is based on the prior information of the amplitude and interference phase of each channel of directional interferometer array of different direction radiation source, obtains the probability distribution of each signal direction, combines the time-frequency two-dimensional distribution obtained by time-frequency analysis, to realize the time-frequency-space direction three-dimensional radiation source separation and situation display, on this basis, along time dimension and azimuth respectively to be synthesized to obtain frequency-azimuth two-dimensional situation chart and 2.5d fast time-frequency-direction situation chart, the distribution and dynamic change of multiple radiation source signals in time, frequency, space direction can be directly indicated from situation chart, also provide effective situation information for further automatic interpretation and discrimination processing.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electromagnetic environment visualization, and particularly relates to a visualization view generation method and system based on directional interferometer array data. BACKGROUND

[0002] Passive detection, identification and positioning of unmanned aerial vehicles (UAVs) by passively intercepting and processing communication signals transmitted by the UAVs is one of the main technical means for UAV detection. At present, there are many types of UAVs, and the communication signals have a very wide frequency range, from several hundred MHz to 6-8 GHz. In order to have the ability to measure the direction of signals in a wide frequency range from low frequency to high frequency, UAV radio detection equipment generally uses directional interferometer array antennas.

[0003] For the detection, analysis and identification of UAV signals, for a long time, it has been mainly carried out in one-dimensional frequency domain or two-dimensional time-frequency domain. In high-dimensional electromagnetic space, the characteristics of signals are more abundant, and multi-source signals are more distinguishable from each other, which is more conducive to the detection, analysis and identification of multi-source signals under complex conditions.

[0004] The UAV radio detection equipment using directional interferometer array can theoretically provide an additional spatial direction resolution dimension on the basis of the original time and frequency dimensions. However, the commonly used spatial spectrum processing mechanism is difficult to be applied to directional interferometers. In addition, the significant difference between UAV communication signals and other general signals is the moving target characteristic that the intensity and direction change with slow time. Therefore, there is an urgent need for electromagnetic situation generation and visualization technology that can be used for directional interferometer array and has moving target display. SUMMARY

[0005] The present application provides a visualization view generation method and system based on directional interferometer array data, which is used to overcome the defects that the prior art is difficult to be applied to directional interferometers.

[0006] To achieve the above-mentioned purpose, the present application provides a visualization view generation method based on directional interferometer array data, comprising the following steps:

[0007] Obtaining directional interferometer array data, pre-processing the directional interferometer array data to obtain signal time-frequency data;

[0008] Conjugate processing a pair of interferometer antennas to obtain multi-channel interference data;

[0009] According to the calibration data of each channel at each frequency, the signal time-frequency data and the multi-channel interference data are calculated by using Gaussian weighted interpolation to obtain ideal multi-channel parameters under different azimuth sampling θ' conditions;

[0010] According to the ideal multi-channel parameters, the posterior probability of the azimuth of the sampled signal at different time and different frequency is calculated.

[0011] According to the normalized direction pattern of each direction corresponding to an effective channel and the effective channel, the amplitude of the direction pattern correction is calculated, the amplitudes are averaged, and the amplitude of each direction signal is obtained;

[0012] According to the posterior probability and the amplitude of the direction signal, a fast time-frequency-azimuth situation map is obtained.

[0013] The frequency-azimuth two-dimensional situation map is obtained by averaging the fast time-frequency-azimuth situation map along the time dimension.

[0014] The azimuth of the fast time-frequency-azimuth situation map is encoded as a phase, and the azimuth dimension is averaged and compressed to obtain a 2.5d fast time-frequency-azimuth situation map.

[0015] To achieve the above object, the application further provides a visual view generation system based on directional interferometer array data, which comprises:

[0016] A data acquisition module is configured to acquire directional interferometer array data, pre-process the directional interferometer array data to obtain signal time-frequency data, and perform conjugate processing on pairs of interferometer antennas to obtain multi-channel interference data.

[0017] A visual view generation module is configured to calculate the signal time-frequency data and the multi-channel interference data by using Gaussian weighted interpolation according to the calibration data of each channel at each frequency to obtain ideal multi-channel parameters under different azimuth sampling θ' conditions, calculate the posterior probability of the azimuth of the sampling signal at different time and different frequencies according to the ideal multi-channel parameters, calculate the amplitude of the direction pattern correction according to the normalized direction pattern of each direction corresponding to an effective channel and the effective channel, average the amplitudes to obtain the amplitude of each direction signal, obtain a fast time-frequency-azimuth situation map according to the posterior probability and the amplitude of the direction signal, average the fast time-frequency-azimuth situation map along the time dimension to obtain a frequency-azimuth two-dimensional situation map, encode the azimuth of the fast time-frequency-azimuth situation map as a phase, and average and compress the azimuth dimension to obtain a 2.5d fast time-frequency-azimuth situation map.

[0018] To achieve the above object, the application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0019] To achieve the above object, the application further provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the above method when executed by a processor.

[0020] Compared with the prior art, the application has the following advantages:

[0021] The method for generating a visual view based on directional interferometer array data provided by the application obtains the probability distribution of each signal direction based on the prior information of the amplitude and interference phase of each channel of the directional interferometer array of different direction radiation sources, and combines the time-frequency two-dimensional distribution obtained by time-frequency analysis, so as to realize the time-frequency-space direction three-dimensional radiation source separation and situation display. On this basis, the frequency-azimuth two-dimensional situation map and the 2.5d fast time-frequency-direction situation map are obtained by being synthesized along the time dimension and the azimuth, respectively. The distribution and dynamic change of multiple radiation source signals in the time, frequency and space direction can be directly indicated on the situation map, and effective situation information is also provided for further automatic interpretation and discrimination processing. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute some embodiments of the application, and for those skilled in the art, other drawings can also be obtained according to the structures shown in these drawings without creative labor.

[0023] Figure 1 The method for generating a visual view based on directional interferometer array data provided by the application provides a flow chart.

[0024] Figure 2 The distribution diagram of the interferometer array;

[0025] Figure 3 The amplitude (left) and phase (right) diagrams of the relevant data of one channel of the unmanned aerial vehicle signal directional interferometer array;

[0026] Figure 4 The frequency and azimuth situation map calculated from the measured data;

[0027] Figure 5 The time-frequency data (one channel) measured by the directional interferometer;

[0028] Figure 6 The 2.5d fast time-frequency-azimuth situation map corresponding to the time-frequency data measured by the directional interferometer.

[0029] The implementation, functional features and advantages of the application will be further described with reference to the embodiments and the drawings. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative effort are within the protection scope of the present application.

[0031] In addition, the technical solutions among the various embodiments of the present application can be combined with each other, but it must be based on the fact that a person of ordinary skill in the art can realize the combination, and when the combination of the technical solutions appears to be contradictory or unachievable, it should be considered that the combination of the technical solutions does not exist and is not within the protection scope of the present application.

[0032] The present application provides a visualization view generation method based on directional interferometer array data, as shown in Figure 1 The method comprises the following steps:

[0033] 101: Obtain directional interferometer array data, and pre-process the directional interferometer array data to obtain signal time-frequency data.

[0034] The signal time-frequency data comprises two channels of amplitude and phase.

[0035] 102: Perform conjugate processing on a pair of interferometer antennas (as shown in Figure 2 ) to obtain multi-channel interference data.

[0036] The multi-channel interference data comprises amplitude and phase, and is recorded as Mag and Phase respectively, both of which are HxWxC three-dimensional matrices, wherein H, W and C are respectively the number of time sampling points, the number of frequency sampling points and the number of channels, and a typical data is as shown in Figure 3 .

[0037] 103: According to the calibration data of each channel at each frequency, the signal time-frequency data and the multi-channel interference data are calculated by using Gaussian weighted interpolation to obtain ideal multi-channel parameters under different azimuth sampling θ'.

[0038] 104: According to the ideal multi-channel parameters, the posterior probability of the azimuth of the signal sampled at different times and different frequencies is calculated.

[0039] 105: According to the effective channel corresponding to each direction and the normalized directional diagram of the effective channel, the amplitude of the directional diagram correction is calculated, and the amplitudes are averaged to obtain the amplitude of each direction signal.

[0040] 106: According to the posterior probability and the amplitude of the direction signal, a fast time-frequency-azimuth situation map is obtained.

[0041] Fast time-frequency-azimuth PIP, representing the distribution of signal energy in time, frequency, and azimuth.

[0042] 107: Average the fast time-frequency-azimuth PIP along the time dimension to obtain a frequency-azimuth PIP, as shown in Figure 4

[0043] The frequency-azimuth PIP forms a video electromagnetic PIP when displayed along the slow time, which can show the intensity and azimuth variation of the electromagnetic moving target.

[0044] 108: Encode the azimuth of the fast time-frequency-azimuth PIP as phase and average and compress along the azimuth dimension to obtain a 2.5d fast time-frequency-azimuth PIP, as shown in Figure 5 and 6

[0045] The 2.5d fast time-frequency-azimuth PIP can intuitively show the distribution of signal in time, frequency, azimuth, and amplitude compared with the fast time-frequency-azimuth PIP.

[0046] In one embodiment, for step 101, the directional interferometer array data is preprocessed to obtain signal time-frequency data, including:

[0047] The directional interferometer array data is processed by short-time Fourier transform to obtain signal time-frequency data.

[0048] In the next embodiment, for step 103, the calibration data includes the amplitudes of different direction signals in each channel The differential amplitudes between adjacent channels The differential amplitude uncertainty The phase And the phase uncertainty

[0049] In another embodiment, for step 103, the ideal multi-channel parameters include amplitude a f,c (θ'), differential amplitude Δa f,c (θ'), differential amplitude uncertainty σ_Δa f,c (θ'), phase And the phase uncertainty

[0050] In one embodiment, for step 104, the posterior probability of the signal azimuth at each time and frequency sample is calculated according to the matching of the differential amplitude and phase of each channel at each time and frequency sample with the ideal multi-channel amplitude and phase online prediction of the different azimuth direction signals, denoted as P t,f (θ') and the probability of no signal ​​

[0051] According to the ideal multi-channel parameter, the posterior probability of the azimuth of the sampling signal at different time and different frequency is calculated, including:

[0052] According to the ideal multi-channel parameter, the log-likelihood probability of different azimuths is calculated:

[0053]

[0054] In the formula, is the log-likelihood probability of different azimuths in the amplitude dimension, is the log-likelihood probability of different azimuths in the phase dimension; C valid is the number of effective channels, that is, 2; c is the number of effective channels, that is, 2;

[0055] According to the preset parameter, the log-likelihood probability of no signal is calculated:

[0056]

[0057] In the formula, σ n Δa, is a preset parameter; the log-likelihood probability of no signal is expressed as a uniform distribution, and is generally taken as σ n Δa=6dB,

[0058] According to the log-likelihood probability of different azimuths and the log-likelihood probability of no signal, the posterior probability of the azimuth of the sampling signal at different time and different frequency is calculated:

[0059]

[0060]

[0061] In the formula, P t,f is the posterior probability of the azimuth of the sampling signal at different time and different frequency; Pr n is the prior probability of the sampling point being a signal, which is generally set to 0.2; P n is the posterior probability of the sampling point being a non-signal.

[0062] In the next embodiment, for step 105, the amplitude of the corrected direction pattern is calculated according to the effective channel corresponding to each direction and the normalized direction pattern of the effective channel, the amplitudes are averaged, and the amplitude of the signal of each direction is obtained, including:

[0063] The amplitude of the corrected direction pattern is calculated according to the effective channel corresponding to each direction and the normalized direction pattern of the effective channel, and the amplitudes are averaged to obtain the amplitude of the signal of each direction.

[0064]

[0065] wherein, is the observed amplitude at time t, frequency f, channel c; is the normalized amplitude at frequency f, direction of arrival θ' in channel c; is the maximum amplitude of each channel; is the amplitude of each direction of arrival signal.

[0066] In another embodiment, for step 106, a fast time-frequency-azimuth situation map is obtained according to the posterior probability and the amplitude of the direction of arrival signal, comprising:

[0067] The posterior probability P t,f (θ') and the amplitude of the direction of arrival signal are multiplied to obtain a fast time-frequency-azimuth situation map:

[0068]

[0069] The application also proposes a visualization view generation system based on directional interferometer array data, comprising:

[0070] A data acquisition module is configured to acquire directional interferometer array data, pre-process the directional interferometer array data to obtain signal time-frequency data, and perform conjugate processing on pairs of interferometer antennas to obtain multi-channel interference data.

[0071] A visualization view generation module is configured to calculate the signal time-frequency data and the multi-channel interference data using Gaussian weighted interpolation according to the calibration data of each channel at each frequency to obtain ideal multi-channel parameters under different azimuth sampling θ'; calculate the posterior probability of the azimuth of the sampling signal at different time and different frequency according to the ideal multi-channel parameters; calculate the amplitude of the direction pattern correction according to the effective channel corresponding to each direction of arrival and the normalized direction pattern of the effective channel, average the amplitudes to obtain the amplitude of each direction of arrival signal; obtain a fast time-frequency-azimuth situation map according to the posterior probability and the amplitude of the direction of arrival signal; average the fast time-frequency-azimuth situation map along the time dimension to obtain a frequency-azimuth two-dimensional situation map; encode the azimuth of the fast time-frequency-azimuth situation map as a phase and average and compress along the azimuth dimension to obtain a 2.5d fast time-frequency-azimuth situation map.

[0072] The application also proposes a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method when executing the computer program.

[0073] The application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the method.

[0074] The above merely describes the preferred embodiments of the present application, and is not intended to limit the patent scope of the present application. Any equivalent structural transformation, direct / indirect application in other related technical fields, or the like, which is made under the inventive concept of the present application, and based on the content of the present application and the accompanying drawings, is included in the patent protection scope of the present application.

Claims

1. A method for generating a visualized view based on directional interferometer array data, characterized by, The method comprises the following steps: obtaining directional interferometer array data, preprocessing the directional interferometer array data to obtain signal time-frequency data; performing conjugate processing on pairs of interferometer antennas to obtain multi-channel interference data; According to the calibration data of each channel at each frequency, the signal time-frequency data and the multi-channel interference data are calculated by using Gaussian weighted interpolation to obtain different azimuth sampling ideal multi-channel parameters under the condition calculating the posterior probability of the azimuth of the signal sampled at different times and different frequencies according to the ideal multi-channel parameters; calculating the amplitude of the pattern correction according to the effective channel corresponding to each direction and the normalized pattern of the effective channel, averaging the amplitudes to obtain the amplitude of each incoming signal; obtaining a fast time-frequency-azimuth situation map according to the posterior probability and the amplitude of the incoming signal; averaging the fast time-frequency-azimuth situation map along the time dimension to obtain a frequency-azimuth two-dimensional situation map; encoding the azimuth of the fast time-frequency-azimuth situation map into a phase and averaging and compressing along the azimuth dimension to obtain a 2.5D fast time-frequency-azimuth situation map; The ideal multi-channel parameters include amplitude , differential amplitude , differential amplitude uncertainty , phase , and phase uncertainty ; calculating the posterior probability of the azimuth of the signal sampled at different times and different frequencies according to the ideal multi-channel parameters, comprising: calculating the log-likelihood probability of different azimuths according to the ideal multi-channel parameters: wherein is the log-likelihood probability for different bearings in the amplitude dimension, is the log-likelihood probability for different bearings in the phase dimension, is the closest two channels to the boresight for each bearing sample, taking into account that the directional interferometer is only valid within a certain beam range, is the number of valid channels; calculating the log-likelihood probability of no signal according to the preset parameters: In the formula, , is a preset parameter; calculating the posterior probability of the azimuth of the signal sampled at different times and different frequencies according to the log-likelihood probability of different azimuths and the log-likelihood probability of no signal: In the formula, P (t, f | S) is the posterior probability of the signal direction of the sampling signal at different times and different frequencies; P (S) is the prior probability of the sampling point being a signal, and P n P (N) is the posterior probability of the sampling point being a non-signal.

2. The visual view generation method of claim 1, wherein, preprocessing the directional interferometer array data to obtain signal time-frequency data, comprising: performing short-time Fourier transform processing on the directional interferometer array data to obtain signal time-frequency data.

3. The visual view generation method of claim 1, wherein, The calibration data includes amplitudes of different incoming signals in each channel , differential amplitudes from adjacent channels , differential amplitude uncertainty , phases , and phase uncertainty .

4. The visual view generation method of claim 1, wherein, calculating the amplitude of the pattern correction according to the effective channel corresponding to each direction and the normalized pattern of the effective channel, averaging the amplitudes to obtain the amplitude of each incoming signal, comprising: calculating the amplitude of the pattern correction according to the effective channel corresponding to each direction and the normalized pattern of the effective channel, averaging the amplitudes to obtain the amplitude of each incoming signal: wherein is the observed amplitude at time t, frequency f, and channel c; is the observed amplitude at frequency f, direction of arrival is the normalized amplitude produced in channel c; is the maximum amplitude in each channel; is the amplitude of each direction of arrival signal.

5. The visual view generation method of claim 1, wherein, obtaining a fast time-frequency-azimuth situation map according to the posterior probability and the amplitude of the incoming signal, comprising: The posterior probability and the amplitude of the incoming signal are multiplied, resulting in a fast time-frequency-azimuth picture: 。 6. A system for generating visualizations based on directional interferometer array data, the system comprising: comprising: a data acquisition module for obtaining directional interferometer array data, preprocessing the directional interferometer array data to obtain signal time-frequency data; performing conjugate processing on pairs of interferometer antennas to obtain multi-channel interference data; The visual view generation module is configured to calculate the signal time-frequency data and the multi-channel interference data by using Gaussian weighted interpolation according to the calibration data of each channel at each frequency, to obtain different azimuth sampling ideal multi-channel parameters under the condition; calculate posterior probabilities of azimuths of sampling signals at different time and different frequencies according to the ideal multi-channel parameters; calculate amplitudes of the directivity pattern correction according to the corresponding effective channels of each direction of arrival and the normalized directivity pattern of the effective channels, average the amplitudes, and obtain the amplitudes of each direction of arrival signal; obtain a fast time-frequency-azimuth situation map according to the posterior probabilities and the amplitudes of the direction of arrival signals; average the fast time-frequency-azimuth situation map along the time dimension to obtain a frequency-azimuth two-dimensional situation map; encode the azimuth of the fast time-frequency-azimuth situation map as a phase, and average and compress along the azimuth dimension to obtain a 2.5d fast time-frequency-azimuth situation map; The ideal multi-channel parameters include amplitude , differential amplitude , differential amplitude uncertainty , phase , and phase uncertainty ; calculating the posterior probability of the azimuth of the signal sampled at different times and different frequencies according to the ideal multi-channel parameters, comprising: calculating the log-likelihood probability of different azimuths according to the ideal multi-channel parameters: wherein is the log-likelihood probability for different bearings in the amplitude dimension, is the log-likelihood probability for different bearings in the phase dimension, is the closest two channels to the boresight for each bearing sample, taking into account that the directional interferometer is only valid within a certain beam range, is the number of valid channels; calculating the log-likelihood probability of no signal according to the preset parameters: In the formula, , is a preset parameter; calculating the posterior probability of the azimuth of the signal sampled at different times and different frequencies according to the log-likelihood probability of different azimuths and the log-likelihood probability of no signal: wherein P (t, f | S) is the posterior probability of the signal direction for the sampling signal at different time and frequency; P (S) is the prior probability of the sampling point being a signal, n P (N | S) is the posterior probability of the sampling point being a non-signal. 7.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-6 when the computer program is executed by the processor. The processor executes the computer program to realize the steps of the method of any one of claims 1-5.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the method of any one of claims 1-5.

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