Multi-target interference effect real-time analysis method and system in electronic warfare simulation

Abstract

The invention relates to the field of data analysis in electronic warfare simulation, in particular to a multi-target interference effect real-time analysis method and system in electronic warfare simulation, and the method comprises the steps: building a dynamic multi-path channel model through obtaining multi-path propagation parameters of all interference targets in a target region; simulating a time domain superposition process of an interference signal waveform and a real signal waveform at a receiving end according to the dynamic multi-path channel model to obtain a receiving end synthetic signal and extract signal characteristic parameters; carrying out weighted fusion on the signal characteristic parameters to obtain a dynamic interference efficiency value of the interference target; according to a comparison relationship between the dynamic interference efficiency value and a preset interference efficiency threshold value, adjusting an emission parameter; and when the dynamic interference efficiency value of the interference target is greater than or equal to a preset interference efficiency threshold value, outputting the emission parameter as an interference strategy parameter. The problems of signal misalignment, one-sided interference evaluation and the like in a complex electromagnetic environment are solved, and the accuracy of interference effect analysis and battlefield adaptability are remarkably improved.

Description

Technical Field

[0001] The invention relates to the field of data analysis in electronic warfare simulation, and in particular to a real-time analysis method and system for multi-target interference effects in electronic warfare simulation. Background Art

[0002] With the rapid development of electronic warfare technology, simulation analysis of multi-target jamming effects has become an important means to evaluate the effectiveness of electronic warfare systems. Real-time analysis of multi-target jamming effects in complex battlefield environments is of great significance. In complex electromagnetic environments, signal propagation is often accompanied by multipath effects and is significantly affected. The jamming signal and the real signal are dynamically superimposed by various influencing factors at the receiving end, which may lead to problems such as signal distortion, false alarm or missed detection, directly affecting the effectiveness of the jamming strategy.

[0003] However, existing technologies still have obvious limitations in multipath modeling, interference effect quantification, and dynamic parameter optimization, making it difficult to meet the real-time analysis needs in highly dynamic electromagnetic environments. Currently, existing interference effect evaluation relies on a single indicator and lacks comprehensive analysis of multi-dimensional features, making it difficult to fully reflect the actual impact of complex electromagnetic environments on interference strategies.

[0004] Therefore, a real-time analysis method for multi-target interference effects in electronic warfare simulation is urgently needed to solve problems such as signal inaccuracy and one-sided evaluation in complex electromagnetic environments, and significantly improve the accuracy and adaptability of interference effect analysis. Summary of the invention

[0005] (1) Technical issues to be resolved The purpose of the present invention is to provide a real-time analysis method and system for multi-target interference effects in electronic warfare simulation, so as to solve the problem that in a complex electromagnetic environment, signal propagation is often accompanied by multipath effects and is significantly affected, and interference signals and real signals are dynamically superimposed at the receiving end due to multiple influencing factors, which may lead to signal distortion, false alarm or missed detection, and directly affect the effectiveness of the interference strategy.

[0006] (2) Technical solution To achieve the above object, on the one hand, the present invention provides a method for real-time analysis of multi-target interference effects in electronic warfare simulation, the method comprising: S1. Acquire multipath propagation parameters corresponding to each interference target in the target area, wherein the multipath propagation parameters include time delay, path attenuation coefficient and phase offset; and construct a dynamic multipath channel model according to the multipath propagation parameters.

[0007] S2. Generate an interference signal corresponding to the interference target according to a preset interference strategy, simulate the time domain superposition process of the interference signal and the real signal at the receiving end according to the dynamic multipath channel model, and obtain a receiving end synthetic signal.

[0008] S3. Perform multi-dimensional feature analysis on the synthetic signal at the receiving end to extract signal feature parameters, where the signal feature parameters include a signal-to-noise ratio deterioration value, a phase distortion amount, and a target detection false alarm rate increment.

[0009] S4. Obtain the dynamic interference effectiveness value of the interference target by weighted fusion of the signal characteristic parameters; adjust the transmission parameters of the corresponding interference target according to the comparison relationship between the dynamic interference effectiveness value and the preset interference effectiveness threshold; until the dynamic interference effectiveness value of the interference target is greater than or equal to the preset interference effectiveness threshold, the transmission parameters are output as interference strategy parameters.

[0010] Furthermore, the method of generating an interference signal corresponding to an interference target according to a preset interference strategy, simulating a time domain superposition process of the interference signal and a real signal at a receiving end according to the dynamic multipath channel model, and obtaining a synthetic signal at a receiving end includes: According to the multipath propagation parameters in the dynamic multipath channel model, time delay compensation, attenuation coefficient weighting and phase offset correction are performed on each path component of the interference signal and the real signal to obtain a multipath signal component set; the multipath signal component set includes the interference signal multipath component and the real signal multipath component.

[0011] The multipath components of the interference signal and the multipath components of the real signal are aligned in the time domain according to the sampling points and superimposed point by point to obtain the synthetic signal at the receiving end.

[0012] The dynamic changes of multipath propagation parameters in the current electromagnetic environment are monitored in real time. If the change in the number of paths, delay or phase offset is detected to exceed the preset tolerance threshold, the dynamic multipath channel model is updated.

[0013] Spectrum analysis is used to verify whether the synthesized signal at the receiving end meets the preset bandwidth constraint conditions. If it exceeds the preset bandwidth constraint range, the weight distribution of the path attenuation coefficient in the dynamic multipath channel model is adjusted until the spectrum of the synthesized signal at the receiving end converges to the preset bandwidth constraint range.

[0014] Furthermore, the method for adjusting the weight distribution of the path attenuation coefficient in the dynamic multipath channel model includes: The contribution of each path component of the synthetic signal at the receiving end to the condition exceeding the preset bandwidth constraint is obtained; the attenuation coefficient weights of the first N path components with the highest contribution are proportionally reduced according to the contribution, and the attenuation coefficient weights of the remaining path components are simultaneously increased while the total attenuation coefficient weight remains constant; N is the minimum positive integer that satisfies that the sum of the contributions of the first N path components is greater than or equal to a preset contribution threshold.

[0015] Furthermore, the method for obtaining the contribution of each path component of the receiving end composite signal to the condition exceeding the preset bandwidth constraint includes: According to the spectrum analysis result of the synthetic signal at the receiving end, an out-of-limit frequency band range in which the signal energy exceeds the preset bandwidth constraint condition is determined.

[0016] An independent spectrum analysis is performed on the signal waveform of each path component in the dynamic multi-path channel model, and the energy integral value of each path component within the over-limit frequency band is extracted respectively.

[0017] An energy integral ratio of the energy integral value of each path component to the total energy integral value of all path components within the out-of-limit frequency band is calculated, and the energy integral ratio is used as the contribution of the corresponding path component to exceeding the preset bandwidth constraint condition.

[0018] Furthermore, the method of performing multi-dimensional feature analysis on the receiving end synthetic signal to extract signal feature parameters includes: The synthetic signal at the receiving end is subjected to time domain analysis, and the difference between the average power of the synthetic signal and the baseline power is calculated to obtain the signal-to-noise ratio deterioration value; the synthetic signal at the receiving end is subjected to phase demodulation, and the instantaneous phase deviation root mean square value of the synthetic signal waveform is extracted to obtain the phase distortion; the synthetic signal at the receiving end is subjected to false alarm rate statistical analysis, and the increment of the current detection false alarm rate and the baseline false alarm rate is calculated to obtain the target detection false alarm rate increment.

[0019] Furthermore, the method of adjusting the transmission parameters of the corresponding interference target according to the comparison relationship between the dynamic interference effectiveness value and the preset interference effectiveness threshold includes: The transmission parameters include interference signal frequency, transmission power and beam pointing angle; if the dynamic interference efficiency value of the current interference target is less than the preset interference efficiency threshold, the adjustment amount of the interference signal frequency, transmission power and beam pointing angle is calculated respectively according to the efficiency difference between the dynamic interference efficiency value and the preset interference efficiency threshold.

[0020] The adjustment amount of the interference signal frequency is determined by a frequency deviation compensation algorithm, and the compensation direction is to offset the center frequency of the interference target receiving frequency band; the adjustment amount of the transmission power is linearly amplified according to the proportional coefficient of the efficiency difference, and the maximum transmission power does not exceed the preset safe transmission power threshold; the adjustment amount of the beam pointing angle dynamically optimizes the beam pointing angle weight according to the deviation value between the interference target azimuth and the current beam pointing angle.

[0021] The adjusted interference signal frequency, transmission power and beam pointing angle are used to generate an updated interference signal through data analysis.

[0022] Furthermore, the method of generating an updated interference signal by analyzing the adjusted interference signal frequency, transmission power and beam pointing angle includes: A baseband modulation signal is generated according to the adjusted interference signal frequency, the baseband modulation signal is up-converted to the adjusted interference signal frequency and a radio frequency modulation signal is generated; the adjusted transmission power is used as the amplitude gain coefficient, the radio frequency modulation signal is power amplified, and the amplified radio frequency modulation signal is limited; according to the adjusted beam pointing angle weight, the limited radio frequency modulation signal is multi-channel weighted processed to obtain a multi-channel spatial signal set, and the multi-channel spatial signal set is synthesized by an array antenna model to form a beam signal pointing to the interference target direction.

[0023] If the bandwidth of the beam signal is greater than or equal to the preset bandwidth tolerance, the compensation direction of the interference signal frequency or the beam pointing angle weight is readjusted until the bandwidth of the beam signal is less than the preset bandwidth tolerance. The compensation direction of the interference signal frequency or the beam pointing angle weight is readjusted until the bandwidth of the beam signal is less than the preset bandwidth tolerance.

[0024] Furthermore, the method of obtaining the dynamic interference effectiveness value of the interference target by weighted fusion of the signal characteristic parameters includes: According to the dynamic parameters of the current electromagnetic environment, the weight coefficients corresponding to the signal-to-noise ratio degradation value, phase distortion variable and false alarm rate increment are obtained from the pre-trained interference effect evaluation model.

[0025] The signal-to-noise ratio deterioration value, phase distortion value and false alarm rate increment are normalized according to the weight coefficient to obtain characteristic parameter values; the characteristic parameter values ​​are linearly superimposed according to the weight coefficient to obtain a dynamic interference effectiveness value.

[0026] Furthermore, the method of obtaining the weight coefficients corresponding to the signal-to-noise ratio degradation value, the phase distortion value and the false alarm rate increment from the pre-trained interference effect evaluation model according to the current electromagnetic environment dynamic parameters includes: The electromagnetic environment characteristic parameters of each historical interference scene and the corresponding interference effectiveness measured values ​​are obtained to construct a pre-trained interference effect evaluation model; the electromagnetic environment characteristic parameters include the number of signal propagation paths, the standard deviation of path delay and the power spectrum density of environmental noise.

[0027] The dynamic parameters of the current electromagnetic environment are collected in real time, and the cosine similarity between the dynamic parameters of the electromagnetic environment and the characteristic parameters of the electromagnetic environment is calculated, and the historical interference scene with the highest similarity is matched as the benchmark interference scene; the initial weight coefficient corresponding to the benchmark interference scene is obtained from the pre-trained interference effect evaluation model.

[0028] The deviation value between the dynamic parameters of the current electromagnetic environment and the characteristic parameters of the electromagnetic environment of the benchmark interference scenario is obtained, and the initial weight coefficient is dynamically corrected by linear interpolation to obtain the weight coefficient adapted to the current electromagnetic environment and used as the weight coefficient corresponding to the signal-to-noise ratio degradation value, phase distortion value and false alarm rate increment.

[0029] On the other hand, based on the same inventive concept, the present invention also provides a real-time analysis system for multi-target interference effects in electronic warfare simulation, the system comprising: a data processing module, a synthetic signal analysis module, a signal characteristic parameter acquisition module, and an interference analysis management module, and the modules are sequentially connected in communication; The data processing module is used to obtain the multipath propagation parameters corresponding to each interference target in the target area, wherein the multipath propagation parameters include time delay, path attenuation coefficient and phase offset; and construct a dynamic multipath channel model according to the multipath propagation parameters.

[0030] The synthetic signal analysis module is used to generate an interference signal corresponding to the interference target according to a preset interference strategy, and simulate the time domain superposition process of the interference signal and the real signal at the receiving end according to the dynamic multipath channel model to obtain a receiving end synthetic signal.

[0031] A signal characteristic parameter acquisition module is used to perform multi-dimensional feature analysis on the synthetic signal of the receiving end to extract signal characteristic parameters, wherein the signal characteristic parameters include a signal-to-noise ratio degradation value, a phase distortion variable, and a target detection false alarm rate increment; The interference analysis management module is used to obtain the dynamic interference effectiveness value of the interference target by weighted fusion of the signal characteristic parameters; adjust the transmission parameters of the corresponding interference target according to the comparison relationship between the dynamic interference effectiveness value and the preset interference effectiveness threshold; until the dynamic interference effectiveness value of the interference target is greater than or equal to the preset interference effectiveness threshold, the transmission parameters are output as interference strategy parameters.

[0032] (3) Beneficial effects Compared with the prior art, the present invention has the following beneficial effects: 1. By constructing a dynamic multipath channel model, simulating the time domain superposition process of the interference signal and the real signal, combining multi-dimensional feature analysis to extract key signal feature parameters, and weighted fusion to obtain the dynamic interference effectiveness value of each interference target, the interference effect can be accurately evaluated, providing a reliable basis for adjusting the interference strategy.

[0033] 2. Based on the comparison between the dynamic interference effectiveness value and the preset interference effectiveness threshold, the transmission parameters can be adaptively adjusted, including the interference signal frequency, transmission power and beam pointing angle, to ensure that the interference effect is sustained and effective and adapt to complex and changing electromagnetic environments.

[0034] 3. Monitor the dynamic changes of multipath propagation parameters in the electromagnetic environment in real time, update the dynamic multipath channel model in a timely manner, and ensure that the synthetic signal at the receiving end meets the preset bandwidth constraints by adjusting the path attenuation coefficient weight distribution and other methods, thereby improving the pertinence and effectiveness of the interference signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 The present invention is a flowchart of a method for real-time analysis of multi-target interference effects in electronic warfare simulation.

[0036] Figure 2 The present invention is a schematic diagram of the module composition of a real-time analysis system for multi-target interference effects in electronic warfare simulation. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] It is necessary to explain the application scenarios conceived in the present invention. The present invention is a real-time analysis method and system for multi-target interference effects in electronic warfare simulation, which is used to solve problems such as signal inaccuracy and one-sided interference assessment in complex electromagnetic environments, significantly improve the accuracy of multi-target interference effect analysis and battlefield adaptability, provide reliable decision-making support for electronic confrontation, and improve combat effectiveness.

[0039] like Figure 1 As shown, this embodiment provides a method for real-time analysis of multi-target interference effects in electronic warfare simulation, the method comprising: S1. Obtain the multipath propagation parameters corresponding to each interference target in the target area, wherein the multipath propagation parameters include time delay, path attenuation coefficient and phase offset; construct a dynamic multipath channel model based on the multipath propagation parameters; in an electronic warfare environment, signal propagation will be affected by multiple factors such as terrain, buildings, atmosphere, etc., forming multiple propagation paths, and the multipath propagation parameters are obtained through electromagnetic field strength measurement equipment combined with a geographic information system. Propagation paths include direct paths (minimal delay, minimal attenuation), reflection paths (caused by terrain and buildings, etc., with different time delays, attenuation characteristics and phase offsets) and scattering paths, etc. The dynamic multipath channel model can be represented by a discrete time-varying channel transfer function, that is, , where the attenuation coefficient Indicates The signal path is The amplitude decays at the moment; Indicates The path signal at time Arriving at the receiving end, describing the delay characteristics of the signal; Indicates The signal path is Phase change at a certain moment, phase shift It will affect the synthesis effect of the signal; it can reflect the changes of channel characteristics over time and is more in line with the actual electromagnetic environment characteristics.

[0040] S2. Generate an interference signal corresponding to the interference target according to the preset interference strategy, and simulate the time domain superposition process of the interference signal and the real signal at the receiving end according to the dynamic multipath channel model to obtain the receiving end synthetic signal; the interference strategy includes noise interference (such as white noise, Gaussian noise), deception interference (such as false target echo) or suppression interference (such as sweep frequency signal), etc. The parameters of the interference signal (such as center frequency, bandwidth, modulation mode, etc.) are pre-set according to the working characteristics of the interference target, aiming to destroy or interfere with the normal operation of the enemy communication system. Generate the real signal of its normal operation according to the working mode of the enemy equipment (such as radar transmission signal, communication data stream). Using the constructed dynamic multipath channel model, the interference signal and the real signal are propagated and calculated according to their respective multipath characteristics, and the receiving end synthetic signal is obtained by time domain superposition at the receiving end, which can be realized by discrete convolution and numerical addition. By considering the influence of multipath propagation, the simulated synthetic signal of the receiving end is closer to the actual situation. The receiving end refers to the signal receiving end of the enemy's electronic equipment (such as radar, communication system, etc.). The purpose is to simulate the synthetic signal received by the enemy equipment in the actual battlefield environment, which contains the interference signal emitted by us and the enemy's own real signal (such as radar echo or communication signal).

[0041] S3. Perform multi-dimensional feature analysis on the synthetic signal at the receiving end to extract signal feature parameters, wherein the signal feature parameters include signal-to-noise ratio deterioration value, phase distortion value and target detection false alarm rate increment; the signal-to-noise ratio deterioration value, phase distortion value and target detection false alarm rate increment respectively comprehensively evaluate the interference effect from three dimensions of energy suppression, phase destruction and false alarm generation, and are the core basis for evaluating the interference effect: if the signal-to-noise ratio deterioration value of the interference signal in the synthetic signal is high, that is, the energy significantly suppresses the real signal, then the interference is effective; if the synthetic signal has serious phase distortion, the enemy may not be able to correctly demodulate the signal; if the synthetic signal causes a surge in the false alarm rate, then the enemy's target detection logic is successfully disrupted.

[0042] S4. Obtain the dynamic interference effectiveness value of the interference target through weighted fusion of the signal characteristic parameters; adjust the transmission parameters of the corresponding interference target according to the comparison relationship between the dynamic interference effectiveness value and the preset interference effectiveness threshold; until the dynamic interference effectiveness value of the interference target is greater than or equal to the preset interference effectiveness threshold, the transmission parameters are output as interference strategy parameters. During the weighted fusion process, each signal characteristic parameter is normalized and converted into a value between 0 and 1. According to the comparison result between the dynamic interference effectiveness value and the preset interference effectiveness threshold, it is determined whether the transmission parameters of the interference target need to be adjusted. The interference strategy parameters include the interference signal frequency, transmission power and beam pointing angle of each interference target.

[0043] The method of generating an interference signal corresponding to an interference target according to a preset interference strategy, simulating a time domain superposition process of the interference signal and a real signal at a receiving end according to the dynamic multipath channel model, and obtaining a synthetic signal at a receiving end includes: According to the multipath propagation parameters in the dynamic multipath channel model, time delay compensation, attenuation coefficient weighting and phase offset correction are performed on each path component of the interference signal and the real signal to obtain a multipath signal component set; the multipath signal component set includes the interference signal multipath component and the real signal multipath component; time delay compensation is achieved by shifting the signal sampling point so that each path signal is correctly aligned in time; attenuation coefficient weighting is achieved by multiplying the corresponding attenuation coefficient to simulate the energy loss of the signal during the propagation process; phase offset correction is achieved by complex phase rotation to reflect the phase change in multipath propagation.

[0044] The multipath components of the interference signal and the multipath components of the real signal are aligned in the time domain according to the sampling points and superimposed point by point to obtain the synthetic signal at the receiving end; the time domain superposition process includes time domain waveform alignment and point-by-point superposition of each path component of the interference signal and the real signal, and point-by-point superposition means adding the corresponding sampling values ​​of all path components at each sampling moment to form a sampling value sequence of the synthetic signal. It is necessary to ensure that the sampling rate is high enough to accurately reflect the time domain characteristics of the signal, and the sampling rate is not less than twice the signal bandwidth to meet the Nyquist sampling theorem.

[0045] Monitor the dynamic changes of multipath propagation parameters in the current electromagnetic environment in real time. If the change in the number of paths, delay or phase offset is detected to exceed the preset tolerance threshold, the dynamic multipath channel model is updated; since the actual electromagnetic environment is dynamically changing, it is necessary to monitor the changes in multipath propagation parameters in real time. If the change in the number of paths, delay or phase offset is detected to exceed the preset tolerance threshold, it means that the current multipath channel model can no longer accurately reflect the actual propagation environment. Parameters such as the number of paths, delay and phase offset in the current electromagnetic environment are measured regularly (such as every second or higher frequency) and compared with the parameters in the multipath channel model. When the change is detected to exceed the preset tolerance threshold (such as the change in the number of paths, the delay change exceeds 0.1μs or the phase change exceeds 10°), the dynamic multipath channel model is updated. This real-time update mechanism ensures that the dynamic multipath channel model is consistent with the actual environment and improves the accuracy of interference effect analysis.

[0046] Spectrum analysis is used to verify whether the synthesized signal at the receiving end meets the preset bandwidth constraint. If it exceeds the preset bandwidth constraint range, the weight distribution of the path attenuation coefficient in the dynamic multipath channel model is adjusted until the spectrum of the synthesized signal at the receiving end converges to the preset bandwidth constraint range. In order to ensure that the interference signal does not interfere with other frequency bands, it is necessary to perform spectrum analysis on the synthesized signal at the receiving end to verify whether it meets the preset bandwidth constraint. Spectrum analysis can be achieved through fast Fourier transform (FFT). If it is found that the signal bandwidth exceeds the constraint range (such as exceeding the target receiving frequency band or exceeding the maximum allowed bandwidth), the weight distribution of the path attenuation coefficient in the dynamic multipath channel model will be adjusted to optimize the spectrum characteristics of the synthesized signal at the receiving end.

[0047] The method for adjusting the weight distribution of path attenuation coefficients in a dynamic multipath channel model comprises: The contribution of each path component of the synthetic signal at the receiving end to the condition exceeding the preset bandwidth constraint is obtained; the attenuation coefficient weights of the first N path components with the highest contribution are proportionally reduced according to the contribution, and the attenuation coefficient weights of the remaining path components are simultaneously increased while the total attenuation coefficient weight remains constant; N is the minimum positive integer that satisfies that the sum of the contributions of the first N path components is greater than or equal to a preset contribution threshold.

[0048] According to the adjusted attenuation coefficient weight, the multipath signal component set is regenerated, and the time domain superposition is performed to obtain the updated receiving end synthetic signal. The contribution of each path component to the exceeding of the preset bandwidth constraint condition is analyzed by performing spectrum analysis on each path component separately and calculating its energy proportion in the over-limit frequency band. Then, the attenuation coefficient weights of the first N path components with the highest contribution are reduced proportionally, while the weights of other path components are increased to keep the total attenuation unchanged. The adjustment ratio is determined according to the size of the contribution. The basis for determining N is to select the minimum number of paths so that the sum of their contributions reaches the preset contribution threshold. Using the adjusted path attenuation coefficient weight, the original interference signal waveform and the real signal waveform are subjected to delay compensation, attenuation coefficient weighting and phase offset correction to obtain a new multipath signal component set, and the new multipath signal component set is aligned in the time domain according to the sampling points and superimposed point by point. In this way, the signal strength at each sampling point is the superposition result of the new interference signal and the real signal at that sampling point.

[0049] The method for obtaining the contribution of each path component of the receiving end composite signal to the condition exceeding the preset bandwidth constraint comprises: Determine, based on the spectrum analysis result of the synthetic signal at the receiving end, a frequency band range where the signal energy exceeds a preset bandwidth constraint condition; An independent spectrum analysis is performed on the signal waveform of each path component in the dynamic multi-path channel model, and the energy integral value of each path component within the over-limit frequency band is extracted respectively.

[0050] Calculate the energy integral ratio of the energy integral value of each path component to the total energy integral value of all path components within the over-limit frequency band, and use the energy integral ratio as the contribution of the corresponding path component to exceeding the preset bandwidth constraint. Determine the over-limit frequency band range where the signal energy exceeds the preset bandwidth constraint by performing spectrum analysis on the synthetic signal at the receiving end. For example, if the preset bandwidth constraint is 100MHz, but the synthetic signal has obvious energy within the range of 120MHz, the over-limit frequency band is 100-120MHz. Perform independent spectrum analysis on the signal waveform of each path component in the dynamic multi-path channel model, and calculate the energy integral value of each path component in the over-limit frequency band respectively. The energy integral value is obtained by Fourier transforming the signal waveform of each path component to obtain its spectrum distribution, and then performing integration operation within the over-limit frequency band. Divide the energy integral value of each path component by the total energy integral value of all path components in the over-limit frequency band to obtain the energy integral ratio and use it as the contribution of the corresponding path component. The larger the ratio, the higher the contribution of the path component to the spectrum over-limit. By accurately quantifying the impact of each path on bandwidth excess, a scientific basis is provided for subsequent weight adjustments.

[0051] The method for performing multi-dimensional feature analysis on the receiving end synthetic signal to extract signal feature parameters comprises: The synthetic signal at the receiving end is analyzed in the time domain, and the difference between the average power of the synthetic signal and the baseline power is calculated to obtain the signal-to-noise ratio deterioration value; the synthetic signal at the receiving end is phase demodulated, and the instantaneous phase deviation root mean square value of the synthetic signal waveform is extracted to obtain the phase distortion; the synthetic signal at the receiving end is statistically analyzed for false alarm rate, and the increment of the current detection false alarm rate and the baseline false alarm rate is calculated to obtain the target detection false alarm rate increment. The average power can be obtained by averaging the square values ​​of the signal sampling points. The calculated average power is compared with the pre-measured baseline power, and the difference is calculated to obtain the signal-to-noise ratio deterioration value. The baseline power can be obtained by measuring or theoretically calculating the interference-free signal under the same conditions. The instantaneous phase deviation of the synthetic signal waveform is extracted by phase demodulation, and the instantaneous phase deviation root mean square value can quantify the phase distortion degree of the signal waveform. Phase demodulation can be achieved by Hilbert transform or orthogonal demodulation, and the instantaneous phase sequence of the signal is obtained. The actual phase sequence is compared with the ideal phase sequence (phase sequence without interference), and the instantaneous phase deviation root mean square value is calculated to obtain the phase distortion. By simulating the interference target detection process (such as the CFAR detection algorithm), the detection results under a given false alarm probability are counted, and the increment of the current detection false alarm rate and the baseline false alarm rate (the false alarm rate when there is no interference) is calculated to obtain the false alarm rate increment of the interference target detection.

[0052] The method of adjusting the transmission parameters of the corresponding interference target according to the comparison relationship between the dynamic interference effectiveness value and the preset interference effectiveness threshold comprises: The transmission parameters include interference signal frequency, transmission power and beam pointing angle; if the dynamic interference efficiency value of the current interference target is less than the preset interference efficiency threshold, the adjustment amount of the interference signal frequency, transmission power and beam pointing angle is calculated respectively according to the efficiency difference between the dynamic interference efficiency value and the preset interference efficiency threshold.

[0053] The adjustment amount of the interference signal frequency is determined by a frequency deviation compensation algorithm, and the compensation direction is to offset the center frequency of the interference target receiving frequency band; the adjustment amount of the transmission power is linearly amplified according to the proportional coefficient of the efficiency difference, and the maximum transmission power does not exceed the preset safe transmission power threshold; the adjustment amount of the beam pointing angle dynamically optimizes the beam pointing angle weight according to the deviation value between the interference target azimuth and the current beam pointing angle.

[0054] The adjusted interference signal frequency, transmit power and beam pointing angle are used to generate an updated interference signal through data analysis. The adjustment amount of the interference signal frequency is determined by the frequency deviation compensation algorithm, and the compensation direction is to offset the center frequency of the receiving frequency band of the interference target to ensure that the interference signal can more effectively cover the receiving frequency band of the interference target. According to the proportional coefficient of the efficiency difference, the adjustment amount of the transmit power is obtained. The adjusted transmit power shall not exceed the preset safe transmit power threshold to prevent equipment damage or excessive energy consumption. The proportional coefficient is a numerical factor used to quantify the relationship between the efficiency difference and the transmit power adjustment amount, reflecting the sensitivity of the efficiency difference change to the transmit power adjustment. The efficiency difference can be converted into the actual transmit power adjustment amount through the proportional coefficient, so as to achieve precise control of the transmit power, match the transmit power adjustment with the change of the efficiency difference, and thus optimize the interference effect. The adjustment amount of the beam pointing angle is obtained by dynamically optimizing the beam pointing angle weight according to the deviation value between the azimuth of the interference target and the current beam pointing angle. By adjusting the beam pointing angle, the interference signal can be more accurately pointed to the interference target, thereby improving the interference effect.

[0055] The method of generating an updated interference signal by analyzing the adjusted interference signal frequency, transmission power and beam pointing angle includes: A baseband modulation signal is generated according to the adjusted interference signal frequency, the baseband modulation signal is up-converted to the adjusted interference signal frequency and a radio frequency modulation signal is generated; the adjusted transmission power is used as the amplitude gain coefficient, the radio frequency modulation signal is power amplified, and the amplified radio frequency modulation signal is limited; according to the adjusted beam pointing angle weight, the limited radio frequency modulation signal is multi-channel weighted processed to obtain a multi-channel spatial signal set, and the multi-channel spatial signal set is synthesized by an array antenna model to form a beam signal pointing to the interference target direction.

[0056] If the bandwidth of the beam signal is greater than or equal to the preset bandwidth tolerance, the compensation direction of the interference signal frequency or the beam pointing angle weight is readjusted until the bandwidth of the beam signal is less than the preset bandwidth tolerance. The compensation direction of the interference signal frequency or the beam pointing angle weight is adjusted until the bandwidth of the beam signal is less than the preset bandwidth tolerance. A baseband modulation signal is generated according to the interference type. The interference types include noise interference, deception interference, etc., which can be achieved through digital signal processing technology, such as direct digital synthesis (DDS) or software-based waveform generation. The baseband modulated signal is up-converted to the adjusted interference signal frequency to generate an RF modulated signal. The up-conversion process is usually implemented through a mixer to multiply the baseband signal with the local oscillator signal to generate a frequency of The RF signal is the local oscillator frequency, is the baseband signal frequency. Power amplification is achieved through a variable gain amplifier, and the gain value is set according to the adjusted transmit power. The amplified RF modulated signal is limited to prevent the signal amplitude from being too large, causing nonlinear distortion or damaging the transmitting equipment. The limiter ensures that the signal is transmitted within a safe amplitude range by limiting the maximum amplitude of the signal. According to the adjusted beam pointing angle weight, the limited RF modulated signal is multi-channel weighted to obtain a multi-channel spatial signal set. The signal of each channel is adjusted in amplitude and phase according to its corresponding beam pointing angle weight to form a beam pointing in a specific direction. The multi-channel weighted signal is synthesized through an array antenna model to form a beam signal pointing to the direction of the interference target. The array antenna model adjusts the amplitude and phase of each antenna unit to form a beam pointing in a specific direction. The weight calculation can use a classic beamforming algorithm, such as the delay-sum method or the minimum variance distortionless response (MVDR) algorithm. The bandwidth of the beam signal is less than the preset bandwidth tolerance to prevent the interference signal from occupying too much spectrum resources, affecting other legal communications or causing spectrum conflicts. By adjusting the compensation direction of the interference signal frequency, the center frequency of the signal can be changed, thereby affecting the signal bandwidth. By adjusting the beam pointing angle weight, the direction and shape of the beam can be changed, thereby affecting the distribution of the signal on the spectrum.

[0057] The method of obtaining the dynamic interference effectiveness value of the interference target by weighted fusion of the signal characteristic parameters includes: According to the dynamic parameters of the current electromagnetic environment, the weight coefficients corresponding to the signal-to-noise ratio degradation value, phase distortion variable and false alarm rate increment are obtained from the pre-trained interference effect evaluation model.

[0058] According to the weight coefficient, the signal-to-noise ratio deterioration value, phase distortion value and false alarm rate increment are normalized to obtain the characteristic parameter value; the characteristic parameter value is linearly superimposed according to the weight coefficient to obtain the dynamic interference effectiveness value. The weight coefficients corresponding to the signal-to-noise ratio deterioration value, phase distortion value and false alarm rate increment are obtained from the pre-trained interference effect evaluation model. After obtaining the weight coefficient, each characteristic parameter is normalized to convert parameters of different dimensions and numerical ranges into a unified standard scale (a value between 0-1). Normalization can be performed by maximum and minimum value normalization or Z-score standardization. The normalized characteristic parameters are linearly combined according to the weight coefficient to calculate the dynamic interference effectiveness value, that is, the dynamic interference effectiveness value = weight coefficient 1 × normalized signal-to-noise ratio deterioration value + weight coefficient 2 × normalized phase distortion value + weight coefficient 3 × normalized false alarm rate increment. Among them, the weight coefficients 1.2.3 are the weight coefficients of the three characteristic parameters respectively, and the sum of the weight coefficients 1.2.3 is 1.

[0059] The method of obtaining the weight coefficients corresponding to the signal-to-noise ratio degradation value, the phase distortion variable and the false alarm rate increment from the pre-trained interference effect evaluation model according to the current electromagnetic environment dynamic parameters includes: The electromagnetic environment characteristic parameters of each historical interference scene and the corresponding interference effectiveness measured values ​​are obtained to construct a pre-trained interference effect evaluation model; the electromagnetic environment characteristic parameters include the number of signal propagation paths, the standard deviation of path delay and the power spectrum density of environmental noise.

[0060] The dynamic parameters of the current electromagnetic environment are collected in real time, and the cosine similarity between the dynamic parameters of the electromagnetic environment and the characteristic parameters of the electromagnetic environment is calculated, and the historical interference scene with the highest similarity is matched as the benchmark interference scene; the initial weight coefficient corresponding to the benchmark interference scene is obtained from the pre-trained interference effect evaluation model.

[0061] Obtain the deviation value between the current electromagnetic environment dynamic parameters and the electromagnetic environment characteristic parameters of the benchmark interference scenario, dynamically correct the initial weight coefficient by linear interpolation method to obtain the weight coefficient adapted to the current electromagnetic environment and use it as the weight coefficient corresponding to the signal-to-noise ratio deterioration value, phase distortion variable and false alarm rate increment. Historical data can be obtained through experimental tests or actual combat records, including interference effect data of different scenarios and different target types. The pre-trained interference effect evaluation model is trained using machine learning algorithms (such as neural networks, support vector machines, etc.) to learn the mapping relationship between electromagnetic environment characteristic parameters and interference effectiveness. The current electromagnetic environment dynamic parameters reflect the electromagnetic propagation characteristics and background interference conditions of the current environment, which directly affect the interference effect. Calculate the cosine similarity between the current electromagnetic environment dynamic parameters and the electromagnetic environment characteristic parameters of the historical scenario. The closer the cosine similarity value is to 1, the more similar the two environments are. Further calculate and obtain the deviation value between the current electromagnetic environment dynamic parameters and the electromagnetic environment characteristic parameters of the benchmark interference scenario. The deviation value reflects the degree of difference between the current electromagnetic environment and the benchmark interference scenario, and dynamically correct the initial weight coefficient by linear interpolation method. Linear interpolation is a method of estimating based on known data points. The initial weight coefficient can be adjusted according to the size of the deviation value to make it more suitable for the current electromagnetic environment.

[0062] Based on the same inventive concept, Figure 2 As shown, this embodiment also provides a real-time analysis system for multi-target interference effects in electronic warfare simulation, the system comprising: a data processing module, a synthetic signal analysis module, a signal characteristic parameter acquisition module, and an interference analysis management module, and each module is sequentially connected in communication; A data processing module is used to obtain multipath propagation parameters corresponding to each interference target in the target area, wherein the multipath propagation parameters include time delay, path attenuation coefficient and phase offset; and construct a dynamic multipath channel model according to the multipath propagation parameters; A synthetic signal analysis module, used to generate an interference signal corresponding to an interference target according to a preset interference strategy, and simulate the time domain superposition process of the interference signal and the real signal at the receiving end according to the dynamic multipath channel model to obtain a synthetic signal at the receiving end; A signal characteristic parameter acquisition module is used to perform multi-dimensional feature analysis on the synthetic signal of the receiving end to extract signal characteristic parameters, wherein the signal characteristic parameters include a signal-to-noise ratio degradation value, a phase distortion variable, and a target detection false alarm rate increment; The interference analysis management module is used to obtain the dynamic interference effectiveness value of the interference target by weighted fusion of the signal characteristic parameters; adjust the transmission parameters of the corresponding interference target according to the comparison relationship between the dynamic interference effectiveness value and the preset interference effectiveness threshold; until the dynamic interference effectiveness value of the interference target is greater than or equal to the preset interference effectiveness threshold, the transmission parameters are output as interference strategy parameters.

[0063] It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0064] Finally, it should be noted that: Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A real-time analysis method for multi-target interference effects in electronic warfare simulation, characterized in that: The method comprises: Acquire multipath propagation parameters corresponding to each interference target in the target area, wherein the multipath propagation parameters include time delay, path attenuation coefficient and phase offset; construct a dynamic multipath channel model according to the multipath propagation parameters; Generate an interference signal corresponding to the interference target according to a preset interference strategy, simulate the time domain superposition process of the interference signal and the real signal at the receiving end according to the dynamic multipath channel model, and obtain a receiving end synthetic signal; Performing multi-dimensional feature analysis on the synthetic signal at the receiving end to extract signal feature parameters, wherein the signal feature parameters include a signal-to-noise ratio deterioration value, a phase distortion variable, and a target detection false alarm rate increment; The signal characteristic parameters are weightedly fused to obtain the dynamic interference effectiveness value of the interference target; according to the comparison relationship between the dynamic interference effectiveness value and the preset interference effectiveness threshold, the transmission parameters of the corresponding interference target are adjusted; until the dynamic interference effectiveness value of the interference target is greater than or equal to the preset interference effectiveness threshold, the transmission parameters are output as interference strategy parameters.

2. The method for real-time analysis of multi-target interference effects in electronic warfare simulation according to claim 1, characterized in that: The method of generating an interference signal corresponding to an interference target according to a preset interference strategy, simulating a time domain superposition process of the interference signal and a real signal at a receiving end according to the dynamic multipath channel model, and obtaining a synthetic signal at a receiving end includes: According to the multipath propagation parameters in the dynamic multipath channel model, delay compensation, attenuation coefficient weighting and phase offset correction are performed on each path component of the interference signal and the real signal to obtain a multipath signal component set; the multipath signal component set includes the interference signal multipath component and the real signal multipath component; Align the multipath components of the interference signal with the multipath components of the real signal in the time domain according to the sampling points and superimpose them point by point to obtain a synthetic signal at the receiving end; Monitor the dynamic changes of multipath propagation parameters in the current electromagnetic environment in real time, and update the dynamic multipath channel model if the detected change in the number of paths, delay or phase offset exceeds a preset tolerance threshold; Spectrum analysis is used to verify whether the synthesized signal at the receiving end meets the preset bandwidth constraint conditions. If it exceeds the preset bandwidth constraint range, the weight distribution of the path attenuation coefficient in the dynamic multipath channel model is adjusted until the spectrum of the synthesized signal at the receiving end converges to the preset bandwidth constraint range.

3. The method for real-time analysis of multi-target interference effects in electronic warfare simulation according to claim 2, characterized in that: The method for adjusting the weight distribution of path attenuation coefficients in a dynamic multipath channel model comprises: The contribution of each path component of the synthetic signal at the receiving end to the condition exceeding the preset bandwidth constraint is obtained; the attenuation coefficient weights of the first N path components with the highest contribution are proportionally reduced according to the contribution, and the attenuation coefficient weights of the remaining path components are simultaneously increased while the total attenuation coefficient weight remains constant; N is the minimum positive integer that satisfies that the sum of the contributions of the first N path components is greater than or equal to a preset contribution threshold.

4. The method for real-time analysis of multi-target interference effects in electronic warfare simulation according to claim 3 is characterized in that: The method for obtaining the contribution of each path component of the receiving end composite signal to the condition exceeding the preset bandwidth constraint comprises: Determine, based on the spectrum analysis result of the synthetic signal at the receiving end, a frequency band range where the signal energy exceeds a preset bandwidth constraint condition; Performing independent spectrum analysis on the signal waveform of each path component in the dynamic multipath channel model, and extracting the energy integral value of each path component within the over-limit frequency band; An energy integral ratio of the energy integral value of each path component to the total energy integral value of all path components within the out-of-limit frequency band is calculated, and the energy integral ratio is used as the contribution of the corresponding path component to exceeding the preset bandwidth constraint condition.

5. The method for real-time analysis of multi-target interference effects in electronic warfare simulation according to claim 1, characterized in that: The method for performing multi-dimensional feature analysis on the receiving end synthetic signal to extract signal feature parameters comprises: The synthetic signal at the receiving end is subjected to time domain analysis, and the difference between the average power of the synthetic signal and the baseline power is calculated to obtain the signal-to-noise ratio deterioration value; the synthetic signal at the receiving end is subjected to phase demodulation, and the instantaneous phase deviation root mean square value of the synthetic signal waveform is extracted to obtain the phase distortion; the synthetic signal at the receiving end is subjected to false alarm rate statistical analysis, and the increment of the current detection false alarm rate and the baseline false alarm rate is calculated to obtain the target detection false alarm rate increment.

6. The method for real-time analysis of multi-target interference effects in electronic warfare simulation according to claim 1, characterized in that: The method of adjusting the transmission parameters of the corresponding interference target according to the comparison relationship between the dynamic interference effectiveness value and the preset interference effectiveness threshold comprises: The transmission parameters include interference signal frequency, transmission power and beam pointing angle; if the dynamic interference efficiency value of the current interference target is less than the preset interference efficiency threshold, then according to the efficiency difference between the dynamic interference efficiency value and the preset interference efficiency threshold, the adjustment amount of the interference signal frequency, transmission power and beam pointing angle is calculated respectively; The adjustment amount of the interference signal frequency is determined by a frequency offset compensation algorithm, and the compensation direction is to offset the center frequency of the interference target receiving frequency band; the adjustment amount of the transmission power is linearly amplified according to the proportional coefficient of the efficiency difference, and the maximum transmission power does not exceed the preset safe transmission power threshold; the adjustment amount of the beam pointing angle dynamically optimizes the beam pointing angle weight according to the deviation value between the interference target azimuth angle and the current beam pointing angle; The adjusted interference signal frequency, transmission power and beam pointing angle are used to generate an updated interference signal through data analysis.

7. The method for real-time analysis of multi-target interference effects in electronic warfare simulation according to claim 6 is characterized in that: The method of generating an updated interference signal by analyzing the adjusted interference signal frequency, transmission power and beam pointing angle comprises: Generate a baseband modulation signal according to the adjusted interference signal frequency, up-convert the baseband modulation signal to the adjusted interference signal frequency and generate a radio frequency modulation signal; use the adjusted transmission power as the amplitude gain coefficient to power amplify the radio frequency modulation signal, and perform limiting processing on the amplified radio frequency modulation signal; perform multi-channel weighted processing on the limited radio frequency modulation signal according to the adjusted beam pointing angle weight to obtain a multi-channel spatial signal set, and the multi-channel spatial signal set is synthesized into a beam signal pointing to the interference target direction through an array antenna model; If the bandwidth of the beam signal is greater than or equal to the preset bandwidth tolerance, the compensation direction of the interference signal frequency or the beam pointing angle weight is readjusted until the bandwidth of the beam signal is less than the preset bandwidth tolerance. The compensation direction of the interference signal frequency or the beam pointing angle weight is readjusted until the bandwidth of the beam signal is less than the preset bandwidth tolerance.

8. The method for real-time analysis of multi-target interference effects in electronic warfare simulation according to claim 1, characterized in that: The method of obtaining the dynamic interference effectiveness value of the interference target by weighted fusion of the signal characteristic parameters includes: According to the dynamic parameters of the current electromagnetic environment, the weight coefficients corresponding to the signal-to-noise ratio degradation value, the phase distortion variable and the false alarm rate increment are obtained from the pre-trained interference effect evaluation model; The signal-to-noise ratio deterioration value, phase distortion value and false alarm rate increment are normalized according to the weight coefficient to obtain characteristic parameter values; the characteristic parameter values ​​are linearly superimposed according to the weight coefficient to obtain a dynamic interference effectiveness value.

9. The method for real-time analysis of multi-target interference effects in electronic warfare simulation according to claim 8, characterized in that: The method of obtaining the weight coefficients corresponding to the signal-to-noise ratio degradation value, the phase distortion variable and the false alarm rate increment from the pre-trained interference effect evaluation model according to the current electromagnetic environment dynamic parameters includes: Obtain the electromagnetic environment characteristic parameters of each historical interference scene and the corresponding interference effectiveness measured values ​​to build a pre-trained interference effect evaluation model; the electromagnetic environment characteristic parameters include the number of signal propagation paths, the path delay standard deviation and the environmental noise power spectrum density; Collect the current electromagnetic environment dynamic parameters in real time and calculate the cosine similarity between the electromagnetic environment dynamic parameters and the electromagnetic environment characteristic parameters, match the historical interference scene with the highest similarity as the benchmark interference scene; obtain the initial weight coefficient corresponding to the benchmark interference scene from the pre-trained interference effect evaluation model; The deviation value between the dynamic parameters of the current electromagnetic environment and the characteristic parameters of the electromagnetic environment of the benchmark interference scenario is obtained, and the initial weight coefficient is dynamically corrected by linear interpolation to obtain the weight coefficient adapted to the current electromagnetic environment and used as the weight coefficient corresponding to the signal-to-noise ratio degradation value, phase distortion value and false alarm rate increment.

10. A real-time analysis system for multi-target interference effects in electronic warfare simulation, characterized in that: The system comprises: a data processing module, a synthetic signal analysis module, a signal characteristic parameter acquisition module, and an interference analysis management module, and each module is sequentially connected in communication; A data processing module is used to obtain multipath propagation parameters corresponding to each interference target in the target area, wherein the multipath propagation parameters include time delay, path attenuation coefficient and phase offset; and construct a dynamic multipath channel model according to the multipath propagation parameters; A synthetic signal analysis module, used to generate an interference signal corresponding to an interference target according to a preset interference strategy, and simulate the time domain superposition process of the interference signal and the real signal at the receiving end according to the dynamic multipath channel model to obtain a synthetic signal at the receiving end; A signal characteristic parameter acquisition module is used to perform multi-dimensional feature analysis on the synthetic signal of the receiving end to extract signal characteristic parameters, wherein the signal characteristic parameters include a signal-to-noise ratio degradation value, a phase distortion variable, and a target detection false alarm rate increment; The interference analysis management module is used to obtain the dynamic interference effectiveness value of the interference target by weighted fusion of the signal characteristic parameters; adjust the transmission parameters of the corresponding interference target according to the comparison relationship between the dynamic interference effectiveness value and the preset interference effectiveness threshold; until the dynamic interference effectiveness value of the interference target is greater than or equal to the preset interference effectiveness threshold, the transmission parameters are output as interference strategy parameters.

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