Radar Target Recognition Using One-Dimensional Evolutionary Programming–Based Clean

In this work, we present a method for radar target recognition using an one-dimensional (1-D) evolutionary programmingbased CLEAN. This 1-D scattering center extraction method relies upon evolutionary programming and an undamped exponential model. It is accurate, robust and fast. Moreover, it is free from the resolution problems that arise in FFT-based CLEAN. Unlike with model-based techniques, the accuracy of extracted parameters is unaffected by false estimation of the number of scattering centers. Experimental results show that the 1-D evolutionary programming-based CLEAN algorithm can be successfully applied to radar target recognition with correlation-based approaches to reduce data storage, as well as with neural network-based approaches to efficiently extract feature vectors.