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- Title
面向组网雷达干扰任务的多机伴随式编队航迹预规划方法.
- Authors
邹玮琦; 牛朝阳; 刘 伟; 王艳云; 湛嘉祺
- Abstract
For the multi-target penetrating netted radar system scenario, in order to effectively improve the interference effect and penetration success rate, formation trajectory planning is particularly important Therefore, this paper firstly builds a trajectory planning model. Starting from the four aspects of the aircraft's own constraints, trajectory safety, constraints among aircrafts, and task completion effect, combined with the characteristics of the multi-syndrome jammers formation and its environment, a relatively complete trajectory planning criterion is proposed to form a new overall objective function. Secondly, in order to effectively describe the maneuver properties of each aircraft and the connection between the accompanying jammer and the target aircraft, and improve the algorithm search ability, a multi-spherical vector-based (MS) method is proposed. At the same time, in order to further improve the exploration and development capabilities of the proposed algorithm, a hybrid particle swarm optimization with track point by track point learning (TLIIPSO) algorithm is proposed, and the two algorithms are combined to form MS-TLIIPSO trajectory planning method. Finally,the simulation scenarios are constructed for ver让icalion. The comparison results show that the MS method and the TLIIPSO optimization algorithm have obvious advantages in the ability to find the optimal value. The proposed algorithm in this paper is superior to other algorithms in terms of the average value of the optimal solution in different initial scenarios, which fully shows that the algorithm in this paper can plan formation tracks with higher reliability under the premise of ensuring stability.
- Subjects
OPTIMIZATION algorithms; SEARCH algorithms; CONSTRUCTION planning; PARTICLE swarm optimization; RADAR; ALGORITHMS
- Publication
Systems Engineering & Electronics, 2024, Vol 46, Issue 8, p2807
- ISSN
1001-506X
- Publication type
Article
- DOI
10.12305/j.issn.1001506X.2024.08.28