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Hybrid integration method for highly maneuvering radar target detection based on a Markov motion model

Chinese Journal of Aeronautics 2020年第6期33卷 1717-1730页

作者： Yingxiao ZHAO Zengping CHEN Yue ZHANG Jie CHEN Jiong YANG Yunsheng XIONG National Key L aboratory of Science and Technology on ATR National University of Defense TechnologyChangsha 410073China School of Electronic and Communication Engineering Sun Yat-sen UniversityShenzhen 518107China

To detect highly maneuvering radar targets in low signal-to-noise ratio conditions, a hybrid long-time integration method is proposed, which combines Radon-Fourier Transform(RFT), Dynamic Programming(DP), and Binary Integration(BI), named RFT-DP-BI. A Markov model with unified range-velocity quantification is formulated to describe the maneuvering target’s motion. Based on this model, long-time hybrid integration is performed. Firstly, the whole integration time is divided into multiple time segments and coherent integration is performed in each segment via RFT. Secondly, non-coherent integration is performed in all segments via DP. Thirdly, 2/4 binary integration is performed to further improve the detection performance. Finally, the detection results are exported together with target range and velocity trajectories. The proposed method can perform the long-time integration of highly maneuvering targets with arbitrary forms of ***, it has a low computational cost that is linear to the integration time. Both simulated and real radar data demonstrate that it offers good detection and estimation performances.

关键词： Binary integration Dynamic programming Long-time integration Maneuvering targets Markov motion model radar target detection Radon-Fourier transform

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