Radar coherent detection for Doppler-ambiguous maneuvering target based on product scaled periodic Lv's distribution

•Doppler ambiguity and acceleration reduce the integration gain of conventional coherent detection methods.•The frequency scope of DFT is extended by reintroducing its redundant period to estimate the under-sampled Doppler frequency.•The scaling and product operations are used to eliminate the coupl...

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Veröffentlicht in:Signal processing 2020-09, Vol.174, p.107617, Article 107617
Hauptverfasser: Jin, Ke, Lai, Tao, Wang, Yubing, Li, Gongquan, Zhao, Yongjun
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Sprache:eng
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Zusammenfassung:•Doppler ambiguity and acceleration reduce the integration gain of conventional coherent detection methods.•The frequency scope of DFT is extended by reintroducing its redundant period to estimate the under-sampled Doppler frequency.•The scaling and product operations are used to eliminate the couplings and suppress the grating lobes.•A good balance is achieved between computational complexity and detection performance. This paper considers the coherent integration problem for Doppler-ambiguous maneuvering target. A novel method based on the product scaled periodic Lv's distribution (PSPLVD) is proposed. To be specific, the acceleration could be accurately estimated via Lv's distribution (LVD). Then, the periodic discrete Fourier transform (DFT), which periodically extends the frequency scope of DFT, is introduced to modify the LVD to estimate the unambiguous centroid frequency. Thereafter, scaling and product operations are respectively employed to eliminate the coupling and suppress the grating lobes. Finally, coherent integration is achieved after compensating off the range migration and Doppler frequency migration. Cross term analysis indicates the applicability in the scenario of multiple targets. Efficient implementation based on chirp-z transform is also presented to alleviate the computational burden and eliminate the brute force searching procedure. Detailed comparisons with several representative methods lead us to conclude that the proposed method could strike a good balance between computational cost and detection probability. Extensive simulations and real data processing results are provided to verify the proposed method.
ISSN:0165-1684
1872-7557
DOI:10.1016/j.sigpro.2020.107617