一种基于稀疏分解的窄带信号频率估计算法

A Frequency Estimation Algorithm of Narrow-band Signal Based on Sparse Decomposition

针对窄带多分量信号频率估计问题,该文提出一种基于稀疏分解的频率估计算法,能够同时对多个窄带信号的频率进行估计。首先利用传统方法进行频率预估计,然后根据频率预估计的结果建立冗余字典,对信号进行稀疏表示,最后通过匹配追踪算法得到精确的频率估计。该算法极大地减小了字典的长度和稀疏分解的运算量,而且在迭代过程中利用了全局信息更新残差向量,估计结果更为精确,在低信噪比情况下性能也较为稳健。仿真结果验证该算法的有效性和正确性。

For the frequency estimation problem of narrow-band multi-component signal, a frequency estimation algorithm based on the sparse decomposition is proposed, which simultaneously estimates the frequency of multiple narrow-band signal. Firstly, the pre-estimation is used to get the pre-estimating frequency by using the traditional method. Then the redundant dictionary is established by using the pre-estimating frequency to obtain a sparse representation of the signal. Finally, the precise frequency estimation is achieved by the matching pursuit algorithm. The algorithm can greatly reduce the length of dictionary and the computational complexity of sparse decomposition. The proposed algorithm can provide more accurate estimation results when updating residual vector by using the global information in an iterative process, and the performance is robust in lower SNR. The simulation results verify the effectiveness and correctness of the proposed algorithm.