Abstract: As a core area of military struggle,the border defense region can achieve all-weather situation awareness by deploying multi-source heterogeneous sensor networks(WSNs).For large-scale multi-source heterogeneous sensor deployment applications,sensor deployment needs to comprehensively balance the overall performance of the sensor network and the cost of sensor deployment.To address this issue,this paper proposes a multi-source heterogeneous sensor deployment framework based on double-layeroptimization,constructing an upper layer with the objective of minimizing manufacturing cost,deployment cost,and maintenance cost,and a lower layer with a multi-objective optimization model that integrates network coverage,reliability,and life cycle.Moreover,a two-population improved NSGA-II algorithm is designed to solve the double-layer optimization model,optimizing the Pareto front distribution through a population divide-and-conquer strategy and an interquartile range resolution mechanism,thereby solving the difficulty in solving the nested structure of the double-layer optimization model.Finally,to verify the application of the model,simulation experiments are conducted to demonstrate the effectiveness of the model and the superiority of the algorithm.

Key words: Sensor optimal deployment, Network coverage rate, Improved NSGA-II algorithm, Two-layer optimization