TY - JOUR
T1 - Moonlit polarized skylight-aided INS/CNS
T2 - An enhanced attitude determination method
AU - Yang, Yueting
AU - Wang, Yan
AU - Yu, Xiang
AU - Huang, Panpan
AU - Liu, Xin
AU - Dou, Qingfeng
AU - Yang, Jian
AU - Guo, Lei
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2023/3
Y1 - 2023/3
N2 - Autonomous navigation in complex environments (e.g., global navigation satellite system denied and unknown environments) is paramountly important for unmanned systems. Inspired by nocturnal insects’ navigation mechanism, an integrated navigation method combining the information of polarization navigation system (PNS), inertial navigation system (INS), and celestial navigation system (CNS) is presented for attitude determination at night. In order to improve the robustness of attitude estimation, a two-mode attitude determination system is designed, which includes the PNS/INS/CNS (PIC) mode and PNS/INS (PI) mode. With respect to the PIC mode, the bias in moon azimuth calculated by polarized skylight is modeled as a system state and subsequently estimated according to the precise starlight information. By detecting the CNS fault, the PIC mode is switched out. Focusing on PI mode, the estimated moon azimuth bias is applicable to improve the accuracy of the polarization information. A series of simulations and field tests are conducted to evaluate the performance of the presented method. The experimental data indicates that the presented method is able to achieve accurate and stable attitude estimation, which may offer valuable insight into the navigation of complex night environments.
AB - Autonomous navigation in complex environments (e.g., global navigation satellite system denied and unknown environments) is paramountly important for unmanned systems. Inspired by nocturnal insects’ navigation mechanism, an integrated navigation method combining the information of polarization navigation system (PNS), inertial navigation system (INS), and celestial navigation system (CNS) is presented for attitude determination at night. In order to improve the robustness of attitude estimation, a two-mode attitude determination system is designed, which includes the PNS/INS/CNS (PIC) mode and PNS/INS (PI) mode. With respect to the PIC mode, the bias in moon azimuth calculated by polarized skylight is modeled as a system state and subsequently estimated according to the precise starlight information. By detecting the CNS fault, the PIC mode is switched out. Focusing on PI mode, the estimated moon azimuth bias is applicable to improve the accuracy of the polarization information. A series of simulations and field tests are conducted to evaluate the performance of the presented method. The experimental data indicates that the presented method is able to achieve accurate and stable attitude estimation, which may offer valuable insight into the navigation of complex night environments.
KW - Attitude determination
KW - Autonomous navigation
KW - Bio-inspired optical navigation
KW - Moonlit polarized skylight
KW - Night navigation
UR - https://www.scopus.com/pages/publications/85144546668
U2 - 10.1016/j.conengprac.2022.105408
DO - 10.1016/j.conengprac.2022.105408
M3 - 文章
AN - SCOPUS:85144546668
SN - 0967-0661
VL - 132
JO - Control Engineering Practice
JF - Control Engineering Practice
M1 - 105408
ER -