基于稀疏重构的窄带弱信号时延估计算法

提出了一种基于稀疏重构的窄带弱信号时延估计算法.利用信号的互相关谱构造数据矩阵,然后建立时延参数的冗余字典,最后通过矩阵奇异值分解在信号子空间中利用正交匹配追踪算法得到高精度时延估计.理论分析和仿真实验验证了算法的正确性和有效性.相比于传统方法,该算法可将窄带弱信号时延估计精度提高约1倍.

Time Delay Estimation Algorithm for Weak Narrowband Signals Based on Sparse Reconstructive

A new time delay estimation algorithm for weak narrowband signals based on sparse reconstruc-tive was presented. Firstly, the data matrix was constructed by the cross-correlation spectrum of signals, secondly, the over-complete dictionary for time delay was established, finally, the high precision time de-lay was estimated in the signal subspace by using orthogonal matching pursuit ( OMP) algorithm, and the subspace is obtained by singular value decomposition ( SVD) of the data matrix. Analysis and simulation verify the correctness and effectiveness of the algorithm. Compared with conventional time delay estima-tion algorithm, the presented algorithm can improve the estimation accuracy by about 1 time.