TY - GEN
T1 - Tightly-coupled INS/CNS/PNS integrated navigation based on adaptive multi-model fusion
AU - Chen, Taihang
AU - Zhao, Qian
AU - Xu, Lidan
AU - Zhang, Teng
AU - Hu, Pengwei
AU - Zhang, Xiao
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Reliable navigation in GNSS-denied nighttime environments remains a significant challenge for unmanned systems. Measurement uncertainty and environmental disturbances can degrade navigation accuracy. To mitigate these issues, a tightly coupled integrated navigation method is proposed, combining inertial navigation systems (INS), polarization navigation systems (PNS), and celestial navigation systems (CNS). A measurement model is developed utilizing raw vector measurements from the star sensor and the polarization sensor. Furthermore, an adaptive multi-model fusion architecture based on an interactive multiple-model (IMM) framework is introduced. The measurement noise covariance matrices and adaptive weights are dynamically updated through measurement innovations. Field experiment results demonstrate that the proposed method significantly enhances navigation accuracy, robustness, and adaptability.
AB - Reliable navigation in GNSS-denied nighttime environments remains a significant challenge for unmanned systems. Measurement uncertainty and environmental disturbances can degrade navigation accuracy. To mitigate these issues, a tightly coupled integrated navigation method is proposed, combining inertial navigation systems (INS), polarization navigation systems (PNS), and celestial navigation systems (CNS). A measurement model is developed utilizing raw vector measurements from the star sensor and the polarization sensor. Furthermore, an adaptive multi-model fusion architecture based on an interactive multiple-model (IMM) framework is introduced. The measurement noise covariance matrices and adaptive weights are dynamically updated through measurement innovations. Field experiment results demonstrate that the proposed method significantly enhances navigation accuracy, robustness, and adaptability.
KW - CNS
KW - PNS
KW - adaptive multi-model fusion
KW - integrated navigation
KW - sensor disturbances
UR - https://www.scopus.com/pages/publications/105024675817
U2 - 10.1109/IECON58223.2025.11221233
DO - 10.1109/IECON58223.2025.11221233
M3 - 会议稿件
AN - SCOPUS:105024675817
T3 - IECON Proceedings (Industrial Electronics Conference)
BT - IECON 2025 - 51st Annual Conference of the IEEE Industrial Electronics Society
PB - IEEE Computer Society
T2 - 51st Annual Conference of the IEEE Industrial Electronics Society, IECON 2025
Y2 - 14 October 2025 through 17 October 2025
ER -