Deployment Optimization for Integrated Search and Tracking Tasks in Netted Radar System Based on Pareto Theory
IEEE Transactions on Aerospace and Electronic Systems(2024)
摘要
This paper proposes a joint deployment optimization method for integrated search and tracking (ISAT) tasks in netted radar systems. The bi-objective optimization model is developed with the aim to improve the integrated performance of the two tasks by optimizing the positions of radars. The first objective function aims to maximize the integrated sensing area for the search task. The second objective function aims to minimize the weighted sum of the localization errors w.r.t. multiple sampling points when the tracking task is simulated by localizing some sampling points from a potential trajectory in this paper. A modified Non-dominated Sorting Genetic Algorithm (NSGA) method based on the Pareto theory is proposed in this paper to solve the bi-objective optimization problem and get the Pareto optimal curve. With the Pareto optimal curve, we can choose an optimized deployment scheme conveniently by the Table Look-up method and find a suitable tradeoff between ISAT tasks. Finally, simulation results are given to demonstrate the effectiveness and practicality of the joint deployment optimization method.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要