A comparison between the Extended Kalman Filter and a Minimum-Energy Filter in the TSE(2) case

被引：2
|
作者：
Rigo, Damiano [1 ]
Sansonetto, Nicola [1 ]
Muradore, Riccardo [1 ]
机构：
[1] Univ Verona, Dept Comp Sci, I-37134 Verona, Italy
来源：
2021 60TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2021年
关键词：
D O I：
10.1109/CDC45484.2021.9683631
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Attitude estimation is a core problem in many rigid body systems. The scientific literature proposed a lot of filters and algorithms to estimate pose and velocity of such rigid body systems. In this paper we compare the extended Kalman filter, that represents a generalization of the standard Kalman filter for non-linear systems, and a second-order-optimal minimum-energy filter on the matrix Lie group TSE(2). Optimality refers to a cost function in the unknown model error and measurement error. The measurement system consists of a GPS-like, that provides the position of two antennas on the vehicle, and an INS unit, that provides the linear and angular velocity.
引用
收藏
页码：6175 / 6180
页数：6
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