Traditional grid point-based area coverage methods are committed to algorithm optimization

causing coarse approximation and high complexity problems.In order to solve these problems

based on the probabilistic sensing model

we first study the sensing probabilities of two adjacent points and obtain the fundamental mathematical relationship between them.According to this relationship

we define the concept of feature point set (FPS) to character the area.Then

we transform the probabilistic area coverage into optimization problem of FPS.Further

we design an improved particle swarm optimization (IWPSO) algorithm to solve this optimization problem

which can effectively avoid the premature problems in the convergence of PSO algorithm.Finally

through extensive simulations

we demonstrate that our algorithm outperforms the proposed solutions significantly

and provides a new train of thought for area coverage problem.