Sensor placement of multistatic radar system by using genetic algorithm

Inspired by recent advances in multistatic radar systems, the problem of sensor placement is investigated. Our study is motivated by the fact that it is not always clear what the placement of the radars giving the best performance for the targets of interest might be. To account for the issue, we derive the multistatic Cramér-Rao lower bounds (CRLBs) for range and velocity estimation as the fitness function. Then we use genetic algorithms (GAs) to perform the optimized sensor placement as one of global optimization. The simulation example indicates that our proposed approach is a flexible and effective tool and is capable of suggesting optimal sensor placement strategies to meet required radar performance goals.