An application of hybrid computing to estimate jointly the amplitude and Direction of Arrival with single snapshot

In this paper, utilization of hybrid computational approach is evaluated for the joint estimation of amplitude and Direction of Arrival of far field sources impinging on a uniform linear array. In this hybrid approach, swarm intelligence based on Particle swarm optimization is exploited as a global optimizer assisted with pattern search technique as a rapid local search technique. The optimization of adaptive parameters depending upon the amplitudes and direction of arrival is performed using the fitness function based on Mean Square Error that defines an error between desired response and estimated response. The interest in this function is due to its ease in implementation, efficiency and simplicity of concept. It is derived from Maximum Likelihood and requires only single snapshot to converge. The proposed algorithm is robust enough to produce fairly good results even in the presence of low signal-to-Noise Ratio and requires relatively less number of antenna elements in the array. The results of hybrid technique are much better as compared to Particle Swarm Optimization and pattern search alone. A number of test cases are discussed on the basis of different number of sources impinging on the array with different number of sensors in the array. The accuracy and reliability of the proposed scheme is tested on the basis of Monte-Carlo simulations and its superior statistical analysis.