Study on attitude determination based on discrete particle swarm optimization  

作　　者：VU Khuong 

机构地区：[1]Department of Computer Science, University of Houston

出　　处：《Science China(Technological Sciences)》2010年第12期3397-3403,共7页中国科学（技术科学英文版）

基　　金：supported by the National Research Foundation for the Doctoral Program of Higher Education New Teacher of China (Grant No. 20070359029);the Natural Science Foundation of Anhui Province of China (Grant No. 070412035)

摘　　要：Attitude determination is a key technology in aerospace, sailing and land-navigation etc. In the method of double difference phase measurement, it is a crucial topic to solve the carrier phase integer ambiguity, which is shown to be a combination optimization problem, and thus efficient heuristic algorithms are needed. In this paper, we propose a discrete particle swarm optimization (DPSO)-based solution which aims at searching for the optimal integer ambiguity directly without decorrelation of ambiguity, and computing the baseline vector consequently. A novel flat binary particle encoding approach and corresponding revision operation are presented. Furthermore, domain knowledge is incorporated to significantly improve the convergence rate. Through extensive experiments, we demonstrate that the proposed algorithm outperforms a classic algorithm by up to 80% in time efficiency with solution quality guaranteed. The experiment results show that this algorithm is efficient, robust, and suitable for dynamic attitude determination.Attitude determination is a key technology in aerospace, sailing and land-navigation etc. In the method of double difference phase measurement, it is a crucial topic to solve the carrier phase integer ambiguity, which is shown to be a combination optimization problem, and thus efficient heuristic algorithms are needed. In this paper, we propose a discrete particle swarm optimization (DPSO)-based solution which aims at searching for the optimal integer ambiguity directly without decorrelation of ambiguity, and computing the baseline vector consequently. A novel flat binary particle encoding approach and corresponding revision operation are presented. Furthermore, domain knowledge is incorporated to significantly improve the convergence rate. Through extensive experiments, we demonstrate that the proposed algorithm outperforms a classic algorithm by up to 80% in time efficiency with solution quality guaranteed. The experiment results show that this algorithm is efficient, robust, and suitable for dynamic attitude determination.

关 键 词：ATTITUDE determination DISCRETE particle SWARM optimization (DPSO) INTEGER AMBIGUITY 

分 类 号：V249.1[航空宇航科学与技术—飞行器设计]