Intelligent M-Robust Extended Kalman Filtering for Mobile Tracking

被引：0
|
作者：
Ho, Tan-Jan [1 ]
机构：
[1] Chung Yuan Christian Univ, Dept Elect Engn, Taoyuan 32023, Taiwan
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC) | 2019年
关键词：
WIRELESS LOCALIZATION;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents new M-estimation based robust extended Kalman filter (M-REKF) and fuzzy M-REKF (F-M-REKF) for mobile location estimation in smart urban macro-cells. Both filters can effectively counter the effects of non-Gaussian observation noises owing to the incorporation of measurement screening and enhanced robust regression. They can meet the FCC requirements and achieve satisfactory tracking performance. In general, the F-M-REKF performs better than the M-REKF due to fuzzy tuning of measurement noise covariances. Simulations demonstrate their advantages.
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页码：2332 / 2337
页数：6
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