Optimization of Station Deployment Based on AHP-PSO Strategy

In this article, the problem of station deployment in passive localization system is studied with the aim of guaranteeing the performance of both specific and general areas. A set of metrics is first proposed to give a comprehensive assessment of the system performance, after which analytic hierarchy process (AHP) is employed to acquire the fitness value. Subsequently, a station deployment optimization scheme is proposed exploiting particle swarm optimization (PSO) techniques. Furthermore, chaotic disturbance and adaptive population particle swarm optimization (CD-AP-PSO) and dynamic adaptive population particle swarm optimization (DAP-PSO) are introduced in the process, which greatly benefit the reduction of computational complexity, as well as the avoidance of the local optima. Simulation results demonstrate that the system performance reaches a balance between specific and general areas, and that a higher convergence speed is achieved with lower complexity compared to the traditional PSO.