Weak harmonic signal detection method in chaotic interference based on extended Kalman filter
Author(s) -
Chengye Lu,
Sheng Wu,
Chunxiao Jiang,
Jinfeng Hu
Publication year - 2018
Publication title -
digital communications and networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.082
H-Index - 26
eISSN - 2468-5925
pISSN - 2352-8648
DOI - 10.1016/j.dcan.2018.10.004
Subject(s) - computer science , robustness (evolution) , computational complexity theory , kalman filter , chaotic , extended kalman filter , algorithm , control theory (sociology) , signal (programming language) , artificial intelligence , biochemistry , chemistry , control (management) , gene , programming language
The traditional methods of weak harmonic signal detection under strong chaotic interference often suffer from high computational complexity and poor performance. In this paper, an Extended Kalman Filter (EKF) based detection method is proposed for the detection of weak harmonic signal. The EKF method avoids matrix inversion by iterating measurement equation and state equation, which simultaneously improves the robustness and reduces the complexity. Compared with the existing detection methods, the proposed method has the following advantages: 1) it has better performance than the neural network method; 2) it has similar performance with the optimal filtering method, but with lower computational complexity; 3) it is more robust compared with the optimal filtering method.
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