低截获概率(low probability of intercept,LPI)雷达信号凭借其卓越的抗截获能力,在现代电子战中得到了广泛应用。但LPI雷达信号的低峰值功率使其极易被加性白高斯噪声(additive white Gaussian noise,AWGN)淹没,导致信噪比(signal-to-n...低截获概率(low probability of intercept,LPI)雷达信号凭借其卓越的抗截获能力,在现代电子战中得到了广泛应用。但LPI雷达信号的低峰值功率使其极易被加性白高斯噪声(additive white Gaussian noise,AWGN)淹没,导致信噪比(signal-to-noise ratio,SNR)较低,给信号的检测和识别带来了极大的挑战。为了从AWGN背景中提取原始LPI雷达信号,本文提出了一种名为LPI-U-Net的深度神经网络(deep neural network,DNN),用于端到端的时域LPI雷达信号增强。该网络由特征提取模块(feature extract module,FEM)、特征聚焦模块(feature focus module,FFM)和信号恢复模块(signal recover module,SRM)组成。首先FEM通过卷积操作提取信号的特征,然后FFM利用卷积和通道间注意力进一步关注对信号增强任务有利的特征,最后SRM利用反卷积操作从特征中重构信号,从而完成LPI雷达信号增强。仿真实验表明LPI-U-Net在低SNR下的LPI雷达信号增强性能优于传统信号处理中典型的降噪方法,验证了其可行性和有效性。展开更多
In this paper,we present a novel unimodular sequence design algorithm based on the coordinate descent(CD)algorithm,aimed at countering electronic surveillance(ES)systems based on cyclostationary analysis.Our algorithm...In this paper,we present a novel unimodular sequence design algorithm based on the coordinate descent(CD)algorithm,aimed at countering electronic surveillance(ES)systems based on cyclostationary analysis.Our algorithm not only provides resistance against cyclostationary analysis(CSA)but also maintains low integrated sidelobe(ISL)characteristics.Initially,we derive the expression of the cyclostationary feature(CSF)detector and simplify it into an iterative quadratic form.Additionally,we derive a quadratic form to ensure the similarity of the autocorrelation sidelobes.To balance the minimization of the detection probability and the ISL values,we introduce a Pareto scalar that transforms the multiobjective optimization problem into a convex combination of objective functions.This approach allows us to find an optimal trade-off between the two objectives.Finally,we propose a monotonic algorithm based on the CD algorithm to counter CSA analysis.This algorithm efficiently solves the optimization problem mentioned earlier.Numerical experiments are conducted to validate the correctness and effectiveness of our proposed algorithm.展开更多
文章结合多输入多输出(Multiple Input Multiple Output,MIMO)技术,提出针对低截获概率(Low Probability of Intercept,LPI)通信的传输模式优化、波束成形、功率控制与信道估计等方法,旨在提高系统的抗干扰能力和信号传输效率。仿真结...文章结合多输入多输出(Multiple Input Multiple Output,MIMO)技术,提出针对低截获概率(Low Probability of Intercept,LPI)通信的传输模式优化、波束成形、功率控制与信道估计等方法,旨在提高系统的抗干扰能力和信号传输效率。仿真结果表明,相较于传统单天线LPI系统,基于MIMO的LPI通信系统在复杂信道环境下实现了显著的性能提升,尤其在高信噪比条件下展现出更好的抗衰落能力和吞吐量。该研究为LPI通信技术的发展提供了新的思路,为未来的无线安全通信等领域提供了技术支持和理论依据。展开更多
针对LPI信号分类识别问题中,时频图像受噪声干扰严重的问题,提出了一种基于二维快速经验模式分解(FBEMD)的图像降噪算法,并利用该算法实现对LPI信号的分类。首先利用时频分析方法,获得待分类信号的时频分布图像;使用二维EMD分解算法对...针对LPI信号分类识别问题中,时频图像受噪声干扰严重的问题,提出了一种基于二维快速经验模式分解(FBEMD)的图像降噪算法,并利用该算法实现对LPI信号的分类。首先利用时频分析方法,获得待分类信号的时频分布图像;使用二维EMD分解算法对图像降噪;截取包含时频信息的图像部分,通过主分量分析法提取特征矢量;最后采用RBF神经网络完成信号的分类识别任务。对常见的LPI雷达信号进行仿真,结果表明较低信噪比情况下,该方法仍能获得较好的分类结果。当信噪比为-2 d B时,采用二维EMD降噪算法,平均正确识别率能够达到93%。展开更多
基金support of the National Natural Science Foundation of China under grant numbers 62101570 and 61901494financial support has played a crucial role in the successful completion of this research.
文摘In this paper,we present a novel unimodular sequence design algorithm based on the coordinate descent(CD)algorithm,aimed at countering electronic surveillance(ES)systems based on cyclostationary analysis.Our algorithm not only provides resistance against cyclostationary analysis(CSA)but also maintains low integrated sidelobe(ISL)characteristics.Initially,we derive the expression of the cyclostationary feature(CSF)detector and simplify it into an iterative quadratic form.Additionally,we derive a quadratic form to ensure the similarity of the autocorrelation sidelobes.To balance the minimization of the detection probability and the ISL values,we introduce a Pareto scalar that transforms the multiobjective optimization problem into a convex combination of objective functions.This approach allows us to find an optimal trade-off between the two objectives.Finally,we propose a monotonic algorithm based on the CD algorithm to counter CSA analysis.This algorithm efficiently solves the optimization problem mentioned earlier.Numerical experiments are conducted to validate the correctness and effectiveness of our proposed algorithm.
文摘文章结合多输入多输出(Multiple Input Multiple Output,MIMO)技术,提出针对低截获概率(Low Probability of Intercept,LPI)通信的传输模式优化、波束成形、功率控制与信道估计等方法,旨在提高系统的抗干扰能力和信号传输效率。仿真结果表明,相较于传统单天线LPI系统,基于MIMO的LPI通信系统在复杂信道环境下实现了显著的性能提升,尤其在高信噪比条件下展现出更好的抗衰落能力和吞吐量。该研究为LPI通信技术的发展提供了新的思路,为未来的无线安全通信等领域提供了技术支持和理论依据。
文摘针对LPI信号分类识别问题中,时频图像受噪声干扰严重的问题,提出了一种基于二维快速经验模式分解(FBEMD)的图像降噪算法,并利用该算法实现对LPI信号的分类。首先利用时频分析方法,获得待分类信号的时频分布图像;使用二维EMD分解算法对图像降噪;截取包含时频信息的图像部分,通过主分量分析法提取特征矢量;最后采用RBF神经网络完成信号的分类识别任务。对常见的LPI雷达信号进行仿真,结果表明较低信噪比情况下,该方法仍能获得较好的分类结果。当信噪比为-2 d B时,采用二维EMD降噪算法,平均正确识别率能够达到93%。
