Fuzzy adaptive fusion algorithm for radar/infrared based on wavelet analysis

被引：0

作者：

Yuan, Quan ^{[1
]}

Dong, Chao-Yang ^{[1
]}

Xia, Lian-Cui ^{[1
]}

Wang, Qing ^{[1
]}

机构：

[1] School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China

来源：

Xitong Fangzhen Xuebao / Journal of System Simulation | 2008年 / 20卷 / 05期

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摘要：

In order to improve tracking ability, a fuzzy adaptive fusion algorithm based on wavelet analysis for radar/infrared was proposed, which combined the merits of fuzzy logic and wavelet analysis. Fuzzy adaptive fusion algorithm is a powerful tool to make the actual value of the residual covariance consistent with its theoretical value. To overcome the defect of the dependence on the knowledge of the process and measurement noise statistics of Kalman filter, wavelet analysis was introduced, which needed no prior knowledge of the process and measurement noise. And fuzzy inference system was applied for its simplicity of the approach and its capability of processing imprecise information. The simulation experiments with the novel adaptive fusion algorithm were performed. The computational results show that the proposed algorithm can effectively strengthen the system robustness and improve the tracking precision.

引用

页码：1255 / 1258