JOURNAL ARTICLE

Adaptive filter of non‐linear systems with generalised unknown disturbances

Yuemei QinYan LiangYanbo YangZengfu WangFeng Yang

Year: 2013 Journal:   IET Radar Sonar & Navigation Vol: 8 (4)Pages: 307-317   Publisher: Institution of Engineering and Technology

Abstract

This study presents the state estimation problem of discrete‐time non‐linear stochastic system with generalised unknown disturbance (GUD) in the measurements. To the best of our knowledge, there is no research result on the filter design dealing with such estimation problem. Here, an upper‐bound filter is designed for the linear time‐varying system with the GUD existing in the measurement equation, and optimal parameters are derived so that the minimum upper‐bounds filter is obtained. The result is further extended to the non‐linear case via the iterative optimisation of joint state estimation and parameter identification (the linearised measurement matrix). The simulation about tracking a target via one biased radar and one biased electronic support measure (ESM) shows the effectiveness and robustness of the proposed filter.

Keywords:
Control theory (sociology) Robustness (evolution) Filter (signal processing) Upper and lower bounds Adaptive filter Filter design Linear system Kernel adaptive filter Computer science Mathematics Measure (data warehouse) Linear filter Mathematical optimization Algorithm

Metrics

10
Cited By
1.41
FWCI (Field Weighted Citation Impact)
29
Refs
0.87
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Fault Detection and Control Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Distributed Sensor Networks and Detection Algorithms
Physical Sciences →  Computer Science →  Computer Networks and Communications

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