收稿日期: 2009-12-16
修回日期: 2010-01-12
网络出版日期: 2010-07-15
Cramer-Rao bound analysis for target parameter estimation in adaptive radar
Received date: 2009-12-16
Revised date: 2010-01-12
Online published: 2010-07-15
在窄带信号和窄带阵列假设下,分析了均匀面阵(UPA)自适应雷达中目标参数的最大似然估计.首先分析了UPA信号模型,随后给出了目标参数的最大似然估计和相应的CR下界.通过Jacobian矩阵给出了目标俯仰角、方位角、径向速度、模和相位的CRB.分析结果是1-D均匀线性阵列(ULA)到2-D(UPA)的推广,可用于空中运动目标参数估计的性能分析.
关键词： 均匀面阵; Cramer-Rao下界; 最大似然估计
尚秀芹 , 宋红军 , 郑经波 , 吴勇 . 自适应雷达目标参数估计的Cramer-Rao下界[J]. 中国科学院大学学报, 2010 , 27(4) : 492 -498 . DOI: 10.7523/j.issn.2095-6134.2010.4.009
Under narrowband signal and array assumptions, the maximum likelihood estimations (MLE) for target parameters in the adaptive radar with uniform planar array (UPA)weve analyzed. The UPA model was analyzed, and then the ML estimators for target parameters and the corresponding CRB were given. By means of Jacobian matrix, the CRBs for target elevation, azimuth, velocity, and magnitude, and phase were derived. The results are an extension from 1-D ULA to 2-D UPA, which can be applied to the performance evaluation for parameter estimation of airborne moving target.
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