基于Keystone变换的多目标距离走动校正

摘要

微弱目标检测中,高速运动目标的跨距离单元走动会影响长时间相参积累的效果,需要预先加以校正.针对以往Keystone变换法在校正走动时,不能同时校正模糊数不同的多目标走动的不足,提出了一种改进的Keystone变换算法,在无模糊的Keystone变换之后,通过单元最大模糊数搜索快速得到多个目标的模糊数,使各目标根据自身运动特性得到校正,从而延长相参积累时间、提高积累增益.仿真结果验证了算法的有效性.%In weak target detection, migration through range cells(MTRC) of high-speed targets would affect the performance of long time coherent accumulation and thus should be corrected first. For the deficiency of the usual Keystone algorithm on correcting multi-target MTRCs with different ambiguity factors, an improved algorithm is proposed in this paper. After the basic Keystone transform without considering the velocity ambiguity, a fast method is applied to find out all targets' ambiguity factors. In this way, each target's migration is corrected respectively to its motion, so the coherent time can be increased and the coherent accumulation gain can be improved. Performance of simulations verified the value of the proposed algorithm.