雷达目标方位估计:移动窗口与AML估计器

M. Greco, F. Gini, A. Farina, L. Timmoneri
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引用次数: 3

摘要

本文比较了两种雷达目标到达方向(DOA)估计算法,即经典的移动窗口(MW)估计算法和渐近极大似然(AML)估计算法。第一种方位角估计技术利用了同一时间内的多次探测,第二种技术利用了雷达天线机械扫描对目标后向散射信号进行幅度调制的特性。通过蒙特卡罗模拟对估计器的性能进行了数值研究,包括均方根误差(RMSE)、固定概率的虚警检测概率和“分裂”概率。结果表明,渐近极大似然估计量总体上优于经典的移动窗估计量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Radar target doa estimation: Moving window VS AML estimator
In this paper we compare two radar target direction-of-arrival (DOA) estimation algorithms, the classical moving window (MW) and the asymptotic maximum likelihood (AML) estimators. The first technique for azimuth DOA estimation exploits multiple detections in the same time-on-target and the second one exploits the fact that the radar antenna mechanical scanning impresses an amplitude modulation on the signals backscattered by the target. Performances of the estimators are numerically investigated through Monte Carlo simulation in terms of root-mean-square-error (RMSE), probability of detection for a fixed probability of false alarm, and probability of "splitting". The obtained results show that the asymptotic maximum likelihood estimator generally outperforms the classical moving window estimator.
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