基于稀疏重构的窄带弱信号时延估计算法
发布时间：2019-02-23 10:41
【摘要】：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.
[Abstract]:A time delay estimation algorithm for narrow band weak signals based on sparse reconstruction is proposed. The data matrix is constructed from the cross-correlation spectrum of the signal, and then the redundant dictionary of the delay parameters is established. Finally, the high precision time delay estimation is obtained by using the orthogonal matching tracking algorithm in the signal subspace by the singular value decomposition of the matrix. Theoretical analysis and simulation results show that the algorithm is correct and effective. Compared with the traditional method, this algorithm can improve the accuracy of time delay estimation of narrowband weak signal by about twice.
【作者单位】： 盲信号处理重点实验室;信息工程大学信息系统工程学院;
【基金】：国家自然科学基金项目(61304264)
【分类号】：TN911.23
，
本文编号：2428741
[Abstract]:A time delay estimation algorithm for narrow band weak signals based on sparse reconstruction is proposed. The data matrix is constructed from the cross-correlation spectrum of the signal, and then the redundant dictionary of the delay parameters is established. Finally, the high precision time delay estimation is obtained by using the orthogonal matching tracking algorithm in the signal subspace by the singular value decomposition of the matrix. Theoretical analysis and simulation results show that the algorithm is correct and effective. Compared with the traditional method, this algorithm can improve the accuracy of time delay estimation of narrowband weak signal by about twice.
【作者单位】： 盲信号处理重点实验室;信息工程大学信息系统工程学院;
【基金】：国家自然科学基金项目(61304264)
【分类号】：TN911.23
，
本文编号：2428741
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