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

作　　者：Yingxiao ZHAO Zengping CHEN Yue ZHANG Jie CHEN Jiong YANG Yunsheng XIONG 

机构地区：[1]National Key L aboratory of Science and Technology on ATR,National University of Defense Technology,Changsha 410073,China [2]School of Electronic and Communication Engineering,Sun Yat-sen University,Shenzhen 518107,China

出　　处：《Chinese Journal of Aeronautics》2020年第6期1717-1730,共14页中国航空学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(No.6157010118)。

摘　　要：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 motion.Additionally, 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 

分 类 号：TN957.51[电子电信—信号与信息处理]