先进信号处理与通信技术在防御系统优化中的应用
本专题聚焦于信号处理和通信技术在提高现代防御系统性能方面的最新进展。包括无线网络的安全性增强、遥感图像的智能化分析、雷达信号的精确处理、车载网络的资源优化，以及红外目标检测技术的提升。这些研究成果对于构建更加可靠、高效和智能的防御通信系统至关重要。
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2024, 46(2):174-181.
DOI: 10.11887/j.cn.202402018
Abstract:
The transponder deception jamming with DRFM(digital radio frequency memory) is highly coherent with real radar echoes, which makes it difficult for radar to distinguish real radar echoes and jamming. To address this issue, a DRFM-based deception jamming detection method based on Hough transform was proposed. The jamming signal model based on linear frequency modulation was established and the spectrum of the jamming harmonics was analyzed subsequently. Then, the short-time Fourier transform and two-dimensional constant false alarm rate detector were used to extract the features of the jamming signal. The Hough transform was used to complete deception jamming detection. The proposed method is based on the characteristics of DRFM deception jamming itself, and does not depend on prior information and application scenario. Moreover, it has low computational complexity and good detection performance under the condition of low signal-to-noise. The effectiveness of the proposed method is verified through simulations.
The transponder deception jamming with DRFM(digital radio frequency memory) is highly coherent with real radar echoes, which makes it difficult for radar to distinguish real radar echoes and jamming. To address this issue, a DRFM-based deception jamming detection method based on Hough transform was proposed. The jamming signal model based on linear frequency modulation was established and the spectrum of the jamming harmonics was analyzed subsequently. Then, the short-time Fourier transform and two-dimensional constant false alarm rate detector were used to extract the features of the jamming signal. The Hough transform was used to complete deception jamming detection. The proposed method is based on the characteristics of DRFM deception jamming itself, and does not depend on prior information and application scenario. Moreover, it has low computational complexity and good detection performance under the condition of low signal-to-noise. The effectiveness of the proposed method is verified through simulations.
2024, 46(2):139-145.
DOI: 10.11887/j.cn.202402014
Abstract:
Joint design of transmit beamforming and receiving filter for airborne MIMO(multiple-input multiple-output) radar in the background of signal-dependent clutter was studied. Airborne MIMO radar transmit beamspace STAP(space-time adaptive processing) signal model was established. In order to ensure the target detection performance in clutter environment, the SINR(signal-to-interference-plus-noise ratio) was maximized and a new iterative optimization algorithm based on the MM(maximization-minimization) framework was designed to solve the joint design problem. By properly finding the lower bound of the objective function, the convergence speed of the proposed algorithm was effectively improved and the running time of the proposed algorithm was reduced. In addition, compared with the traditional phased array radar and MIMO radar, the optimized transmit beamforming and receive filter can significantly improve the output SINR. Simulation results demonstrate the effectiveness of the proposed method.
Joint design of transmit beamforming and receiving filter for airborne MIMO(multiple-input multiple-output) radar in the background of signal-dependent clutter was studied. Airborne MIMO radar transmit beamspace STAP(space-time adaptive processing) signal model was established. In order to ensure the target detection performance in clutter environment, the SINR(signal-to-interference-plus-noise ratio) was maximized and a new iterative optimization algorithm based on the MM(maximization-minimization) framework was designed to solve the joint design problem. By properly finding the lower bound of the objective function, the convergence speed of the proposed algorithm was effectively improved and the running time of the proposed algorithm was reduced. In addition, compared with the traditional phased array radar and MIMO radar, the optimized transmit beamforming and receive filter can significantly improve the output SINR. Simulation results demonstrate the effectiveness of the proposed method.
2023, 45(2):87-94.
DOI: 10.11887/j.cn.202302010
Abstract:
In order to analyze the anti-spoofing performance of the GNSS multi-beam anti-jamming receiver under spoofing interference scenario, a performance metric named deception suppression ratio was put forward. The theoretical formula for the power of the authentic and spoofed signal was deduced considering the anti-jamming receiver using the MVDR (minimum variance distortionless response) algorithm with limited number of snapshots. And the influence of the power of the spoofed signal arriving at the antenna array on the output power of the authentic and spoofed signal was analyzed in detail. The analysis shows that even if the power of the spoofed signal is below the noise level, the multi-beam anti-jamming receiver using the MVDR algorithm can still suppress the spoofing interference. And when the spoofed signal-to-noise ratio is high, the suppression is more effective. The conclusion was verified by simulation and hardware platform test.
In order to analyze the anti-spoofing performance of the GNSS multi-beam anti-jamming receiver under spoofing interference scenario, a performance metric named deception suppression ratio was put forward. The theoretical formula for the power of the authentic and spoofed signal was deduced considering the anti-jamming receiver using the MVDR (minimum variance distortionless response) algorithm with limited number of snapshots. And the influence of the power of the spoofed signal arriving at the antenna array on the output power of the authentic and spoofed signal was analyzed in detail. The analysis shows that even if the power of the spoofed signal is below the noise level, the multi-beam anti-jamming receiver using the MVDR algorithm can still suppress the spoofing interference. And when the spoofed signal-to-noise ratio is high, the suppression is more effective. The conclusion was verified by simulation and hardware platform test.
2023, 45(1):25-34.
DOI: 10.11887/j.cn.202301003
Abstract:
Because of the high correlation between the forward jamming and the radar transmitting waveform, it is easy to cause serious jamming to the radar after being received by the radar main lobe. In order to solve the main lobe interference problem, the forward interference signal model of OFDM-MIMO (orthogonal frequency division multiplexing-multiple input multiple output) radar main lobe was established, and the interference mechanism of OFDM-MIMO radar was analyzed. At the same time, based on the adaptive method processing theory, the analytical formula of OFDM-MIMO radar adaptive processing weight vector was derived, and an OFDM-MIMO radar forward main lobe interference adaptive suppression method based on range-dependent beam was proposed. Theoretical research and simulation results show that the proposed method can improve the output signal to interference plus noise ratio and effectively suppress the forward main lobe interference.
Because of the high correlation between the forward jamming and the radar transmitting waveform, it is easy to cause serious jamming to the radar after being received by the radar main lobe. In order to solve the main lobe interference problem, the forward interference signal model of OFDM-MIMO (orthogonal frequency division multiplexing-multiple input multiple output) radar main lobe was established, and the interference mechanism of OFDM-MIMO radar was analyzed. At the same time, based on the adaptive method processing theory, the analytical formula of OFDM-MIMO radar adaptive processing weight vector was derived, and an OFDM-MIMO radar forward main lobe interference adaptive suppression method based on range-dependent beam was proposed. Theoretical research and simulation results show that the proposed method can improve the output signal to interference plus noise ratio and effectively suppress the forward main lobe interference.
2022, 44(4):158-163.
DOI: 10.11887/j.cn.202204017
Abstract:
For the problem of the performance of many existing efficient sorting algorithms depends heavily on the parameters from external input, such as clustering number and clustering tolerance, the parameterless clustering algorithm DSets-DBSCAN was applied to the radar signal sorting, and a parameterless radar signal pulse clustering algorithm was presented. The proposed algorithm could automatically cluster without relying on any parameter settings. Firstly, the algorithm input was the pairwise similarity matrix processed by histogram equalization, which made the Dsets(dominant sets) algorithm independent of any parameters. Then, the input parameters of DBSCAN were given adaptively according to the obtained ultra-small cluster. Finally, the cluster was extended by DBSCAN. Simulation results show that the proposed method is effective in sorting radar pulse descriptors without parameters. And the clustering accuracy of radar signals is higher than 97.56% in the case of the false pulse ratio (false pulse/radar pulse) is lower than 80%.
For the problem of the performance of many existing efficient sorting algorithms depends heavily on the parameters from external input, such as clustering number and clustering tolerance, the parameterless clustering algorithm DSets-DBSCAN was applied to the radar signal sorting, and a parameterless radar signal pulse clustering algorithm was presented. The proposed algorithm could automatically cluster without relying on any parameter settings. Firstly, the algorithm input was the pairwise similarity matrix processed by histogram equalization, which made the Dsets(dominant sets) algorithm independent of any parameters. Then, the input parameters of DBSCAN were given adaptively according to the obtained ultra-small cluster. Finally, the cluster was extended by DBSCAN. Simulation results show that the proposed method is effective in sorting radar pulse descriptors without parameters. And the clustering accuracy of radar signals is higher than 97.56% in the case of the false pulse ratio (false pulse/radar pulse) is lower than 80%.
2022, 44(1):114-121.
DOI: 10.11887/j.cn.202201017
Abstract:
Compared with single-layer attacks, cross-layer attacks in wireless ad hoc networks can better conceal attack behavior, achieve better attack effects, or reduce the cost of attack. In order to detect cross-layer attacks in wireless ad hoc networks, a detection model based on game theory was proposed. As the attack will inevitably affect the parameters of each protocol layer, the corresponding strategy matrix and payoff matrix was built from the aspect of attack-defense game of protocol layer, and the mixed strategy Nash equilibrium solution was obtained by equilibrium analysis. Simulation experiments results show that the detection system adopting mixed strategy can achieve a better detection performance and save the energy consumption significantly, compared with the traditional detection system.
Compared with single-layer attacks, cross-layer attacks in wireless ad hoc networks can better conceal attack behavior, achieve better attack effects, or reduce the cost of attack. In order to detect cross-layer attacks in wireless ad hoc networks, a detection model based on game theory was proposed. As the attack will inevitably affect the parameters of each protocol layer, the corresponding strategy matrix and payoff matrix was built from the aspect of attack-defense game of protocol layer, and the mixed strategy Nash equilibrium solution was obtained by equilibrium analysis. Simulation experiments results show that the detection system adopting mixed strategy can achieve a better detection performance and save the energy consumption significantly, compared with the traditional detection system.
2024, 46(3):180-194.
DOI: 10.11887/j.cn.202403018
Abstract:
Aiming at infrared dim and small targets detection in complex background, a new kernel norm estimation method was proposed based on the non-convex tensor low-rank approximation algorithm with asymmetric spatial-temporal total variation regularization, replacing the original estimation method in the algorithm. An adaptive weight tensor based on structure tensor and multi-structure element Top-Hat filtering was proposed to constrain the target tensor, which had enhanced the sparsity and suppressed the remaining strong edge structures of the target tensor. Experimental results show that the proposed improved algorithm can better eliminate the influence of strong edge structure on the detection results, and has a lower false alarm rate than the original algorithm under the condition of ensuring the detection rate.
Aiming at infrared dim and small targets detection in complex background, a new kernel norm estimation method was proposed based on the non-convex tensor low-rank approximation algorithm with asymmetric spatial-temporal total variation regularization, replacing the original estimation method in the algorithm. An adaptive weight tensor based on structure tensor and multi-structure element Top-Hat filtering was proposed to constrain the target tensor, which had enhanced the sparsity and suppressed the remaining strong edge structures of the target tensor. Experimental results show that the proposed improved algorithm can better eliminate the influence of strong edge structure on the detection results, and has a lower false alarm rate than the original algorithm under the condition of ensuring the detection rate.
