关键词: 脉冲多普勒雷达, 贝叶斯推理, 检测聚焦, 匹配滤波, 距离徒动, 多普勒徒动

Abstract: It has been understood from both radar theory and practice that the coherent integration is an effective method for moving target de-tection. Unfortunately, its performance is seriously damaged by the unknown range and/or Doppler frequency migrations in a coherent processing interval. To handle such a problem, a moving target detector with the coherent integration of Bayesian inferred motion trajectories is proposed in this paper. The analyses show that by flipping the range-frequency of the pulse compressed echo signal, the time-frequency signal describing the motion trajectories of the detected targets in the slow-time domain is got by the inverse Fourier transform of the product of the original echo signal and the flipped one. When the time-frequency signal is taken as the observation and its phases describing the detected moving target trajectories are regarded as the state variables, a state space model for infer-ring the motion trajectories of multiple targets is given. Based on the inferred target trajectories, the range-frequency-slow-time 2D matched filters used to compensate the unknown range and/or Doppler frequency migrations in an echo signal are constructed. As a result, it provides a new method for coherent integration detection of moving targets with high-energy concentration. Compared with the methods reported in the literature, the proposed one does not require any multi-dimensional search and can be applied to high speed/maneuvering targets with unknown complex motion form. Numerical simulation results verify the effectiveness of the analytical results and the superior performance of the proposed method.

Key words: pulse-Doppler radar, Bayesian inference, detection focus, matched filter, range migration, Doppler frequency migration