Sequence CLEAN technique using BGA for contiguous radar target images with high sidelobes

High resolution range profiles usually suffer from range sidelobe artifacts which cause reduction in the dynamic range. The sidelobes can be greatly reduced by a deconvolution technique called Coherent CLEAN. The Coherent CLEAN algorithm is based on the assumption that the scene consists of isolated and independent targets. However, many real-life targets are contiguous. The sidelobes and the mainlobes of these closely spaced point sources interact constructively and destructively causing spurious peaks and peak mislocations. A technique called Sequence CLEAN uses the highest m peaks at a time to determine the best sequence of target subtraction. This involves searching an m-ary tree, which is computationally expensive. We propose the use of the breeder genetic algorithm (BGA) to determine the optimal sequence of target cancellation for Sequence CLEAN. This results in a substantial decrease in the computational complexity. The parameters required for the genetic algorithm have been analytically derived. An expression for the number of generations required to reach convergence by BGA is also derived. It is found that the BGA is able to determine the best sequence of subtraction without performing the exhaustive tree search. Analytical results have been verified by simulations.