Adaptive Fuzzy Kalman Filter Based on INS/RADAR Integrated Navigation System

DOI

10.2991/icacie-17.2017.2How to use a DOI?

Keywords

fuzzy logic; integrated navigation; adaptive Kalman filter; Analytic Hierarchy Process

Abstract

This paper presents a novel INS/RADAR integrated navigation algorithm based on Fuzzy Adaptive Kalman Filtering. The method is mainly used in INS/RADAR integrated navigation system to deal with time varied statistic of measurement noise in different working conditions. By monitoring the relation between status from INS and status from RADAR, the algorithm recursively modifies the gain coefficients of the filter so as to adaptively control the Kalman filter, and finally the optimal estimation is achieved. Through monitoring RMSE, in the case of similar accuracy, running time of the fuzzy filtering algorithm compared to the traditional Kalman filter algorithm is reduced by 32.73% the experimentation results of the INS/RADAR integrated navigation system indicate that the algorithm is effective and practical.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Pengzhan Cheng
AU  - Shuwen Dang
AU  - Fajiang He
AU  - Kangle Wang
PY  - 2017/08
DA  - 2017/08
TI  - Adaptive Fuzzy Kalman Filter Based on INS/RADAR Integrated Navigation System
BT  - Proceedings of the 2017 2nd International Conference on Automatic Control and Information Engineering (ICACIE 2017)
PB  - Atlantis Press
SP  - 5
EP  - 9
SN  - 2352-5401
UR  - https://doi.org/10.2991/icacie-17.2017.2
DO  - 10.2991/icacie-17.2017.2
ID  - Cheng2017/08
ER  -