Hybrid Cramer-Rao Lower Bound on Tracking Ground Moving Extended Target

被引：0
作者：
Xu, Linfeng [1 ]
Li, X. Rong [2 ]
机构：
[1] Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian 710049, Peoples R China
[2] Univ New Orleans, Dept Elect Engn, New Orleans, LA 70148 USA
来源：
FUSION: 2009 12TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4 | 2009年
关键词：
Cramer-Rao lower bound; hybrid estimation; ground moving target tracking; extended target;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper deals with the problem of performance bound for ground moving extended target tracking with high range resolution ground moving target indicator (HRRGMTI). The system model is constructed for our proposed rectangular target tracking. On performance bounds for state and deterministic shape parameter estimation, a hybrid Cramer-Rao lower bound (CRLB) is proposed and its recursive form is derived. By comparison of root CRLB curves for different accuracies of measurement of down-range-extent, the effect of this additional measurement on state and parameter estimation is analyzed.
引用
收藏
页码：1037 / +
页数：3
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