字典奇异值分解加权压缩感知多径信号参数估计
Estimation of multipath parameters of underwater acoustic signals based on weighted compressed sensing with dictionary singular value decomposition
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摘要: 为提高水声信道多径参数估计的分辨率,提出了一种基于字典奇异值分解的加权压缩感知算法。对于有源声呐,根据发射信号构造字典,对字典进行奇异值分解,利用大特征值对应的特征向量构造信号子空间,然后使用信号子空间对接收信号进行滤波。对滤波结果进行加权压缩感知参数估计,得出最终时延估计结果。仿真实验表明,所提方法能够对水声多径参数进行超分辨估计,适用于任何脉冲信号。湖试处理结果显示,混响背景下该方法也有较好的多径参数估计性能,能够降低接收数据的噪声成分,提高对水声信道的多径时延、个数和幅度的估计精度。Abstract: In order to improve the estimated parameter resolution of the underwater channels,a method using weighted compressed sensing based on singular value decomposition,is proposed.For active sonar,the proposed algorithm applies singular value decomposition on dictionary which is created based on transmit signal,and then,constructs signal subspace by eigenvectors corresponding to big eigenvalues.To obtain the multipath parameter estimation,the proposed algorithm performs weighted compressed sensing convex optimization on received data filtered by signal subspace.The simulation and lake experiment show that the created signal subspace could filter noise mixed into received data.The proposed algorithm could estimate the underwater acoustic multipath time delay,number and amplitude more accurately.The proposed method is suitable for any pulse signal.