一種基于稀疏分解的窄帶信號(hào)頻率估計(jì)算法
doi: 10.11999/JEIT140878
基金項(xiàng)目:
國(guó)家部委基金，中央高?；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)基金(JB140203)和國(guó)家973計(jì)劃項(xiàng)目(613181)資助課題
A Frequency Estimation Algorithm of Narrow-band Signal Based on Sparse Decomposition
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摘要: 針對(duì)窄帶多分量信號(hào)頻率估計(jì)問題，該文提出一種基于稀疏分解的頻率估計(jì)算法，能夠同時(shí)對(duì)多個(gè)窄帶信號(hào)的頻率進(jìn)行估計(jì)。首先利用傳統(tǒng)方法進(jìn)行頻率預(yù)估計(jì)，然后根據(jù)頻率預(yù)估計(jì)的結(jié)果建立冗余字典，對(duì)信號(hào)進(jìn)行稀疏表示，最后通過匹配追蹤算法得到精確的頻率估計(jì)。該算法極大地減小了字典的長(zhǎng)度和稀疏分解的運(yùn)算量，而且在迭代過程中利用了全局信息更新殘差向量，估計(jì)結(jié)果更為精確，在低信噪比情況下性能也較為穩(wěn)健。仿真結(jié)果驗(yàn)證該算法的有效性和正確性。Abstract: 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.
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