Target recognition algorithm based on RCS observation sequence — Set-valued identification method

In this paper, we study the problem of target recognition based on RCS observation sequence. First, we use discrete wavelet transform of RCS observation sequence and extract five valid statistical features in the transform domain. Second, we establish the model and apply the method of set-valued identification to determine the relationship between these five characteristics and the target, thus giving recognition criteria. Finally, simulate the situation that the true target is frustum and the false target with normally distributed RCS. Comparing the results to the ones of fuzzy classification method and evidential reasoning method, the result shows that the set-valued identification method has a higher recognition rate.