Cued search algorithm with uncertain detection performance for phased array radars

Abstract

A cued search algorithm with uncertain detection performance is proposed for phased array radars.Firstly,a target search model based on the information gain criterion is presented with known detection performance,and the statistical characteristic of the detection probability is calculated by using the fluctuant model of the target radar cross section (RCS).Secondly,when the detection probability is completely unknown,its probability density function is modeled with a beta distribution,and its posterior probability distribution with the radar observation is derived based on the Bayesian theory.Finally simulation results show that the cued search algorithm with a known RCS fluctuant model can achieve the best performance,and the algorithm with the detection probability modeled as a beta distribution is better than that with a random selected detection probability because the model parameters can be updated by the radar observation to approach to the real value of the detection probability.