Flower Pollination Heuristics for Parameter Estimation of Electromagnetic Plane Waves

For the last few decades, the parameter estimation of electromagnetic plane waves i.e., far field sources, impinging on antenna array geometries has attracted a lot of researchers due to their use in radar, sonar and under water acoustic environments. In this work, nature inspired heuristics based on the flower pollination algorithm (FPA) is designed for the estimation problem of amplitude and direction of arrival of far field sources impinging on uniform linear array (ULA). Using the approximation in mean squared error sense, a fitness function of the problem is developed and the strength of the FPA is utilized for optimization of the cost function representing scenarios for various number of sources non-coherent located in the far field. The worth of the proposed FPA based nature inspired computing heuristic is established through assessment studies on fitness, histograms, cumulative distribution function and box plots analysis. The other worthy perks of the proposed scheme include simplicity of concept, ease in the implementation, extendibility and wide range of applicability to solve complex optimization problems. These salient features make the proposed approach as an attractive alternative to be exploited for solving different parameter estimation problems arising in nonlinear systems, power signal modelling, image processing and fault diagnosis.