雷达低角跟踪环境下的最大似然波达方向估计方法

在时空级联最大似然算法的基础上,本文结合雷达低角跟踪的特点,提出一种新的目标仰角估计算法.该算法利用事先得到的目标距离信息和天线高度信息来得到目标直达波信号和多径信号之间的仰角关系,然后再对时空级联最大似然算法的似然函数进行一维搜索.与时空级联最大似然算法相比,新算法不仅运算量大大下降,而且还具有较好的性能.理论分析和计算机仿真结果都证实了新算法的优越性.

Maximum Likelihood DOA Estimation in Radar Low-Angle Tracking Environment

Based on the temporal-spatial sequential Maximum Likelihood(ML) algorithm,a new algorithm for estimating the elevation angle of a target in radar low-angle tracking environment is presented.According to the range of the target and the height of the antenna,the new algorithm first gets the relation of the direct and specular signals in elevation.Then a one-dimensional search are done on the likelihood function.Compared to the temporal-spatial sequential ML algorithm,the new algorithm not only has a low computation complexity,but also has a good performance.The theoretical analysis and computer simulation results demonstrate the merits of the new algorithm.