Kalman filtering in non-Gaussian environment using efficient score function approximation

Wen-Rong Wu*, Amlan Kundu

*此作品的通信作者

研究成果: Conference article同行評審

9 引文 斯高帕斯(Scopus)

摘要

The authors consider the problem of Kalman filtering in a non-Gaussian environment. It has been shown that a state estimate with a linear prediction corrected by a weighted score function can solve this problem, and the results are nearly optimal. However, the calculation of the score function requires a convolution of two density functions, which is difficult to implement except for simple cases. The authors propose an adaptive normal-expansion-based-distribution approximation for the efficient evaluation of the score function. It is shown that this method is simple and practically feasible. Simulations are also provided to demonstrate the success of the algorithm.

原文English
頁(從 - 到)413-416
頁數4
期刊Proceedings - IEEE International Symposium on Circuits and Systems
1
DOIs
出版狀態Published - 8 五月 1989
事件IEEE International Symposium on Circuits and Systems 1989, the 22nd ISCAS. Part 1 - Portland, OR, USA
持續時間: 8 五月 198911 五月 1989

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