Mainlobe interference suppression based on independent component analysis in passive bistatic radar

Mainlobe interference suppression based on independent component analysis in passive bistatic radar

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The mainlobe interference is a noticeable issue in the passive bistatic radar (PBR). Because the direction of arrival of interference is close to the target echo, the mainlobe interference can hardly be suppressed effectively by the conventional method. The mainlobe interference will mask the low-level targets of interest, and the blind area of detection will be formed in the direction of the interference source. The mainlobe interference signals, which come from the unrelated transmitters can be assumed to be mutually independent on the statistics. In this study, the method based on the independent component analysis (ICA) is proposed to suppress the mainlobe interference. The method exploits the principal components analysis to extract the mainlobe interference components which are whitened and compressed. Then, the ICA based on the negentropy is applied to separate the mainlobe interference components for the samples in the time domain. The mainlobe interference can be suppressed by the extensive cancellation algorithm with the separated interference sample as the reference. The proposed method based on the ICA is able to suppress the multiple mainlobe interferences and improve the performance of detection in the PBR. The simulation results prove the feasibility of the method proposed in this study.

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