Optimum subarray configuration using genetic algorithms

Subarray configuration is not a trivial problem in array signal processing. A proper subarray configuration is important to improve the detectability of an array. A new searching algorithm, which is based on genetic algorithms (GA), for the optimum subarray configuration is proposed. Our preliminary application to a seismic array has indicated that the new algorithm can search a population of subarrays in a more efficient and robust way. The beamforming gain of the optimum subarray derived by the GA is very close to the theoretical gain. Experimental results on signal detections have demonstrated that a beamforming recipe with optimum subarrays can provide further enhanced signal-to-noise ratio (SNR), compared to a recipe without a subarray configuration. The approach proposed here can be easily extended to the weight determination problem for the weighted beamforming process by using multi-bit instead of 1-bit representation for each sensor in the chromosome model