贝叶斯推理运动轨迹相干累积的动目标检测方法
收稿日期: 2021-12-16
修回日期: 2021-12-30
录用日期: 2022-03-21
网络出版日期: 2022-03-30
基金资助
国家自然科学基金(11974082)
A moving target detector with coherent integration of Bayesian-inferred motion trajectories
Received date: 2021-12-16
Revised date: 2021-12-30
Accepted date: 2022-03-21
Online published: 2022-03-30
Supported by
National Natural Science Foundation of China(11974082)
雷达理论和实践都表明相干累积是机动目标探测行之有效的方法，但其性能会因脉冲回波处理间隔内未知距离和/或多普勒的徒动而降低。为解决这个问题，提出了一种贝叶斯推理运动轨迹相干累积的动目标检测方法。首先，通过对脉冲压缩回波信号的距离频率进行翻转，就可从未翻转与翻转后的回波信号相乘的傅里叶逆变换中，提取出慢时间维描述待探测多目标运动轨迹的时频信号。视该时频信号中各目标运动轨迹为状态变量，获得的时频信号为观测，建立起多目标运动轨迹的状态空间模型。这样，据贝叶斯滤波推理出的目标运动轨迹，构建出快-慢时间维联合的二维匹配滤波器，就能补偿目标高速/机动带来的未知距离和/或多普勒徒动。理论分析和仿真实验均证明：所提算法适用具有复杂且未知运动状态的目标，且呈现出了优于文献报道方法的性能。
杨文彬 , 王悦斌 , 李旦 , 张建秋 . 贝叶斯推理运动轨迹相干累积的动目标检测方法[J]. 航空学报, 2023 , 44(6) : 326823 -326823 . DOI: 10.7527/S1000-6893.2022.26823
It has been shown theoretically and practically that coherent integration is an effective method for moving target detection. 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. 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 observed and its phases describing the detected moving target trajectories are regarded as state variables， a state space model for inferring the motion trajectories of multiple targets is given. Based on the inferred target trajectories， the range-frequency-slow-time 2D matched filters are constructed to compensate the unknown range and/or Doppler frequency migrations in an echo signal. Numerical simulation results verify that the proposed method can be applied to high speed/maneuvering targets with unknown complex motion form， and has superior performance than the methods reported in the literature.
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