Distorted target recognition based on improved MACH algorithm

Joint transform correlator(JTC) can make targets recognized and located accurately, but the bottleneck technique of JTC is how to recognize the distorted targets in cluttered scene. This has restricted the development of the pattern recognition for target image. In order to solve the problem, improved Maximum Average Correlation Height(MACH) filter algorithm was presented. The MACH algorithm has powerful capability of recognition for distorted targets(rotation and scale etc.). According to the analysis result of amounts of experiments, the control parameters of the synthesized filter were optimized, which makes the filter have higher distortion tolerance and can suppress cluttered noise effectively. When improved MACH filter algorithm in frequency domain was projected to space domain, the MACH reference template image can be obtained which includes various forms of distorted target image. MACH reference template can sharpen the correlation peaks and expand recognizing scope for distorted targets in cluttered scene. As practical examples, computer simulation experiments and optical experiments for warship in cluttered scene were carried out. The experimental results prove the feasibility and actual effect of the algorithm.