An Optimization Algorithm for Forward-Scatter Radar Network Node Deployment Based on BFGS and Improved NSGA-II
Open Access
- 2 April 2025
- journal article
- research article
- Published by MDPI AG in Remote Sensing
- Vol. 17 (7) , 1263
Abstract
Recently, forward-scatter radars (FSRs) utilizing the Global Navigation Satellite System (GNSS) as a radiation source have gained increasing attention. The radar system enables aerial target surveillance by deploying multiple receiving nodes on the ground. It offers a low-cost and easily deployable solution. Therefore, how to deploy the receiving nodes to achieve efficient utilization of node resources is an urgent problem to be addressed. In this paper, a deployment method was proposed for receiving nodes in a single-transmitter and multiple-receiver configuration. First, the problem was reformulated as an optimal equal-circle covering problem via geometric approximation. A multi-objective optimization model was subsequently established with the objective functions of minimizing node cost and maximizing spatial detection area. Second, a method based on the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm was introduced to obtain the sub-optimal solution of node cost, thereby reducing the computational complexity of the optimization process. Finally, an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) was proposed to derive the deployment schemes. Then, these schemes were ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based on the Entropy Weight Method (EWM). The results indicate that the proposed method can obtain the optimal deployment scheme compared to the existing method and enhance the diversity of the solutions.Keywords
Funding Information
- National Natural Science Foundation of China (62171447, 62401580, ZK24-13)
- Scientific Research Program of National University of Defense Technology (62171447, 62401580, ZK24-13)
This publication has 38 references indexed in Scilit:
- A Multi-Objective Optimization Method for Radar Deployment Based on an Improved NSGA-II Algorithm2023
- Many-objective evolutionary algorithm based agricultural mobile robot route planningComputers and Electronics in Agriculture, 2022
- Observation scheduling for a state-of-the-art SAREOS: Two adaptive multi-objective evolutionary algorithmsComputers & Industrial Engineering, 2022
- Coverage area maximization with parallel simulated annealingExpert Systems with Applications, 2022
- Optimal gravitational-wave follow-up tiling strategies using a genetic algorithmPhysical Review D, 2020
- Multi-type multi-objective imaging scheduling method based on improved NSGA-III for satellite formation systemAdvances In Space Research, 2019
- A multi-objective approach to weather radar network architectureSoft Computing, 2018
- Survey on Coverage Problems in Wireless Sensor NetworksWireless Personal Communications, 2014
- Ant colony optimization with greedy migration mechanism for node deployment in wireless sensor networksJournal of Network and Computer Applications, 2014
- Covering a compact polygonal set by identical circlesComputational Optimization and Applications, 2008