Aiming at the problem of low network coverage caused by uneven deployment and distribution of Wireless Sensor Network nodes, with the goal of maximizing wireless sensor network coverage, a network coverage optimization strategy based on Improved Firefly Algorithm(IFA) is proposed. This method uses the good point set method to initialize the population, improve the diversity of the population and lay the foundation for the global search. Simultaneously, it uses the sigmoid function with non-linear exponential decline as the inertia weight to balance the global and local search capabilities of the algorithm. Then, Gaussian disturbance strategy is employed to perturb individual position update and avoid the premature of the algorithm. The simulation results indicate that compared with Artificial Fish Swarm Algorithm(AFSA), seed Hybrid Particle Swarm Optimization(HSPSO) and Chaotic Glowworm Swarm Optimization(CGSO), this algorithm effectively enhance the network coverage rate and make the WSN more evenly distributed.