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Coherent Detection and Parameter Estimation for Radar High-Speed Maneuvering Target Based on FAF–LVD

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Abstract

Long-time coherent integration can remarkably improve the detection and motion parameter estimation ability of radar for maneuvering targets. Unfortunately, the linear range migration, quadratic range migration (QRM), and Doppler frequency migration (DFM) within the coherent processing interval seriously degrade the target detection and parameter estimation performance. In this regard, a novel coherent integration approach based on frequency autocorrelation function (FAF) and Lv’s distribution (LVD), i.e., FAF–LVD, is proposed in this paper. The QRM is firstly removed by the second-order keystone transform. Then, the FAF with a variable delay is introduced to remove the DFM, followed by the scaled Fourier transform to achieve coherent integration. Finally, the acceleration and velocity are estimated simultaneously by LVD. Analysis demonstrates that FAF–LVD could be efficiently implemented via complex multiplications, the fast Fourier transform (FFT) and inverse FFT. Detailed comparisons with several representative methods indicate that FAF–LVD achieves a better balance among computational complexity, detection ability, and parameter estimation performance. Extensive simulations are presented to validate the effectiveness of FAF–LVD method.

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Funding was provided by the National Natural Science Foundation of China (41301481).

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Correspondence to Ke Jin.

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Jin, K., Lai, T., Zhu, S. et al. Coherent Detection and Parameter Estimation for Radar High-Speed Maneuvering Target Based on FAF–LVD. Circuits Syst Signal Process 39, 2600–2622 (2020). https://doi.org/10.1007/s00034-019-01280-1

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