Posterior Cramer-Rao Lower Bound for Angle-only Filtering in 3D

被引：0
|
作者：
Mallick, Mahendra
Arulampalam, Sanjeev [1 ]
Yan, Yanjun [2 ]
机构：
[1] Dept Def, Def Sci & Technol Grp, Edinburgh, SA, Australia
[2] Western Carolina Univ, Sch Engn & Technol, Cullowhee, NC 28723 USA
来源：
2018 INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND INFORMATION SCIENCES (ICCAIS) | 2018年
关键词：
Angle-only filtering (AGE) in 3D; modified spherical coordinates (MSC); extended Kalman filter (EKE); unscented Kalman filter (UKF); and posterior Cramer-Rao lower bound (PCRLB);
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In our previous work, we compared the performance of a number of nonlinear filters for the angle-only filtering (AOF) problem in 3D using bearing and elevation measurements from a single maneuvering sensor. These fillers used Cartesian coordinates and modified spherical coordinates for the state vector and were based on discrete-time dynamic and measurement. models. The target followed a nearly constant velocity motion. In this paper, we compute the posterior Cramer-Rao lower bound (PCRLB) for the problem so that the performance of the nonlinear filters can be judged relative to the best possible performance. Results from Monte Carlo simulations show that. as the measurement accuracy decreases, the difference between root mean square position and velocity errors and corresponding PCRLBs increases.
引用
收藏
页码：349 / 354
页数：6
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