Research of INS/CNS/SMN Adaptive Integrated Navigation Algorithm for Sea Area

• Published in: Chinese Control Conference pp. 3368 - 3373
• Main Authors: Tian, Zhaoxu, Cheng, Yongmei, Liu, Nan, Yao, Shun, Bai, Weijin, Zhuang, Ruowang, Dai, Li
• Format: Conference Proceeding
• Language: English
• Published: Technical Committee on Control Theory, Chinese Association of Automation 26.07.2021
• Subjects: Adaptation models; Adaptive systems; automatic classification model; Classification algorithms; cloud and fog model; Integrated navigation; Navigation; sea area landmarks; Simulation; Support vector machines; Trajectory
• ISSN: 1934-1768
• DOI: 10.23919/CCC52363.2021.9549635

In this paper, a novel INS/CNS/SMN adaptive integrated navigation algorithm is proposed for long term and high precision navigation in sea area. The structure of INS/CNS/SMN integrated navigation system is established in the algorithm. The cloud and fog model in the Nanhai Sea area is constructed for CNS availability. The three types of sea area landmarks are defined, and the corresponding matching methods and strategies of these landmarks are given. At the same time, an automatic classification model of sea area landmarks based on SVM is also designed. The INS/CNS/SMN adaptive integrated navigation algorithm in sea area is simulated and verified in different altitudes and trajectories. The results show that CNS and SMN can adaptively help INS for long term and high precision navigation.