基于小波分析的雷达/红外模糊自适应融合算法

Fuzzy Adaptive Fusion Algorithm for Radar/Infrared Based on Wavelet Analysis

在多传感器融合算法的基础上,提出一种基于小波分析的雷达/红外模糊自适应融合算法。因为小波分析对测量数据具有多分辨率分析的去噪能力,将小波分析与模糊自适应卡尔曼滤波器相结合构成一个多分辨率跟踪滤波器,该算法可以对来自主动雷达和红外成像传感器的信息加以充分利用,选择适合的小波函数对测量数据进行过滤优化,把干扰负荷转移到小波分析上,在改善跟踪性能的同时又具有很强的处理非平稳信号的能力,而且又保证了该融合算法简单、实用的特点。仿真结果表明,提出的融合算法有很好的跟踪精度,通过对比表明该算法优于传统的多传感器融合算法。

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.