基于RELAX的空中多机动目标检测与参数估计

 针对机载雷达空中多机动目标的检测问题,提出了一种基于RELAX算法的空中多机动目标检测与参数估计方法。该方法将重构时间采样技术与RELAX算法相结合,有效地抑制了检测过程中强信号分量对弱信号分量的影响,在待测单元内存在多个目标时,能够获得很好的参数估计结果,并且在脉冲点数有限的情况下,该方法得到的参数估计精度依然很高。同时,本文还推导了空中多机动目标参数估值的克拉美罗界(CRB),为估计结果提供了理论下限。仿真结果证明了该方法的有效性。

Detection and Parameter Estimation of Multicomponent Air Maneuvering Targets via RELAX

In this paper, a method based on RELAX is presented for detecting the multicomponent air maneuvering targets with the strong clutter background. This method combines the technique of reconstructing time samples with RELAX and effectively suppresses the interferences by stronger targets on the detection of weak targetsr. Therefore, the detection performance and parameter estimation precision of the multicomponent targets are enhanced at the same time. The method can provide an accurate estimate of the parameters even when the data sample is limited. At the same time, the Cramer-Rao bounds (CRBs) for the multicomponent maneuvering targets in airborne radar are derived. The effectiveness of the method is verified via simulated data.