The randomly deployed nodes will lead to the insufficient coverage in Wireless Sensor Networks (WSNs). To solve this problem, an improved sparrow search algorithm - increment of coverage ratio (ISSA-ICR) was proposed. Firstly, to solve the problem that the producer converging to the origin, ISSA modified the location update method of the producer to avoid the algorithm falling into the local optimal solution; Secondly, to balance the global and local search ability of the algorithm, t-distribution disturbance with the number of iterations as the degree of freedom parameter and the dynamic adjustment strategy of the number of producers- scroungers were proposed; Thirdly, random regression cross-border processing strategy was adopted to solve the problem of individual cross-border relocation, and the candidate location of nodes to be deployed was determined; Finally, the node scheduling optimization model was constructed based on ICR strategy to determine the final deployment location. The simulation results show that compared with sparrow search algorithm, standard particle swarm optimization and adaptive virtual force disturbance sparrow search algorithm, ISSA-ICR can respectively improve 4.96%, 8.81% and 3.84% coverage ratio compared with the three algorithms, meanwhile reducing the nodes moving distance.