In through-the-wall detection scenarios with low signal-to-noise ratio(SNR)and strong clutter,existing target detection methods generally suffer from inaccuracies,poor real-time performance,and the limitation of detec...In through-the-wall detection scenarios with low signal-to-noise ratio(SNR)and strong clutter,existing target detection methods generally suffer from inaccuracies,poor real-time performance,and the limitation of detecting only moving or stationary targets.To address these challenges,this paper proposes a throughthe-wall radar(TWR)target detection method based on cross-correlation adaptive robust principal component analysis(CCARPCA)capable of simultaneously detecting multiple moving and stationary targets.First,pulse compression is applied to original echo signals using the inverse fast Fourier transform,resulting in high-resolution one-dimensional range profiles.Second,the principal component analysis algorithm suppresses strong clutter interferences,thereby improving the SNR.Next,the back projection algorithm is employed for multi-channel coherent imaging,enabling the extraction of 2-dimensional information and enhancing the sparsity of cross-correlation data.Lastly,considering the drawbacks of the robust principal component analysis(RPCA),such as long detection time and poor robustness,this paper introduces the cross-correlation coefficient and proposes the CCARPCA algorithm,which completely separates the target from the background noise.The experimental results based on a series of simulated and measured data demonstrate the effectiveness of the proposed method in detecting both moving and stationary targets behind walls.Compared to generalized likelihood ratio test,constant false alarm rate,and RPCA,our method achieves a substantial improvement of over 16.4%in detection accuracy based on measured data while maintaining real-time detection capability.Additionally,its detection performance is less sensitive to changes in initial parameters,indicating its superior robustness.展开更多
针对宽带正交低截获概率(low probability of intercept,LPI)雷达波形簇设计,利用频率编码捷变和调频斜率捷变的复合波形编码技术,在波形正交约束的基础上构造了一种复合频率编码的非线性代价目标函数,提出了基于频率编码捷变或调频斜...针对宽带正交低截获概率(low probability of intercept,LPI)雷达波形簇设计,利用频率编码捷变和调频斜率捷变的复合波形编码技术,在波形正交约束的基础上构造了一种复合频率编码的非线性代价目标函数,提出了基于频率编码捷变或调频斜率捷变的复合波形簇优化设计方法。利用模式搜索算法获得了具有良好自相关和互相关旁瓣特性的宽带正交LPI波形簇。仿真结果表明,所设计的波形能够获得低自相关旁瓣和低互相关旁瓣,可为LPI雷达发射波形与多输入多输出雷达波形的设计提供参考。展开更多
基金supported by the National Key R&D Program of China(2021YFC3090402-03)the National Natural Science Foundation(62171475).
文摘In through-the-wall detection scenarios with low signal-to-noise ratio(SNR)and strong clutter,existing target detection methods generally suffer from inaccuracies,poor real-time performance,and the limitation of detecting only moving or stationary targets.To address these challenges,this paper proposes a throughthe-wall radar(TWR)target detection method based on cross-correlation adaptive robust principal component analysis(CCARPCA)capable of simultaneously detecting multiple moving and stationary targets.First,pulse compression is applied to original echo signals using the inverse fast Fourier transform,resulting in high-resolution one-dimensional range profiles.Second,the principal component analysis algorithm suppresses strong clutter interferences,thereby improving the SNR.Next,the back projection algorithm is employed for multi-channel coherent imaging,enabling the extraction of 2-dimensional information and enhancing the sparsity of cross-correlation data.Lastly,considering the drawbacks of the robust principal component analysis(RPCA),such as long detection time and poor robustness,this paper introduces the cross-correlation coefficient and proposes the CCARPCA algorithm,which completely separates the target from the background noise.The experimental results based on a series of simulated and measured data demonstrate the effectiveness of the proposed method in detecting both moving and stationary targets behind walls.Compared to generalized likelihood ratio test,constant false alarm rate,and RPCA,our method achieves a substantial improvement of over 16.4%in detection accuracy based on measured data while maintaining real-time detection capability.Additionally,its detection performance is less sensitive to changes in initial parameters,indicating its superior robustness.
文摘针对宽带正交低截获概率(low probability of intercept,LPI)雷达波形簇设计,利用频率编码捷变和调频斜率捷变的复合波形编码技术,在波形正交约束的基础上构造了一种复合频率编码的非线性代价目标函数,提出了基于频率编码捷变或调频斜率捷变的复合波形簇优化设计方法。利用模式搜索算法获得了具有良好自相关和互相关旁瓣特性的宽带正交LPI波形簇。仿真结果表明,所设计的波形能够获得低自相关旁瓣和低互相关旁瓣,可为LPI雷达发射波形与多输入多输出雷达波形的设计提供参考。
