TY - JOUR
T1 - An Improved Particle Filter Based on Gravity Measurement Feature in Gravity-Aided Inertial Navigation System
AU - Zhao, Shengwu
AU - Xiao, Xuan
AU - Wang, Yu
AU - Deng, Zhihong
N1 - Publisher Copyright:
© 2001-2012 IEEE.
PY - 2023/1/15
Y1 - 2023/1/15
N2 - The existing gravity matching algorithms are affected by the initial position error of the inertial navigation system (INS), the gravity measurement error, and the similarity of the gravity background map. Aiming at the above problems, an improved particle filter based on the gravity measurement feature (IPFBGMF) is proposed in this article. In the IPFBGMF, both the value and change characteristic of gravity measurements are considered, and a novel position acquisition method based on the gravity measurement feature is proposed, which can reduce the influence of the initial position error of INS. In addition, a new concept called direction measurement using the heading angle of INS is proposed to optimize the weight of particles in the PF. The PF with direction measurement can reduce the influence of the gravity measurement error and the similarity of the gravity background map. Furthermore, the robustness of the improved PF with the precise position is proven. Finally, a navigation strategy is designed to apply the proposed algorithms. Simulations show that IPFBGMF has the highest positioning accuracy compared with the traditional gravity matching algorithms.
AB - The existing gravity matching algorithms are affected by the initial position error of the inertial navigation system (INS), the gravity measurement error, and the similarity of the gravity background map. Aiming at the above problems, an improved particle filter based on the gravity measurement feature (IPFBGMF) is proposed in this article. In the IPFBGMF, both the value and change characteristic of gravity measurements are considered, and a novel position acquisition method based on the gravity measurement feature is proposed, which can reduce the influence of the initial position error of INS. In addition, a new concept called direction measurement using the heading angle of INS is proposed to optimize the weight of particles in the PF. The PF with direction measurement can reduce the influence of the gravity measurement error and the similarity of the gravity background map. Furthermore, the robustness of the improved PF with the precise position is proven. Finally, a navigation strategy is designed to apply the proposed algorithms. Simulations show that IPFBGMF has the highest positioning accuracy compared with the traditional gravity matching algorithms.
KW - Extreme value
KW - gravity measurement feature
KW - gravity-aided inertial navigation system (GAINS)
KW - particle filter (PF)
KW - underwater navigation
UR - http://www.scopus.com/inward/record.url?scp=85144777645&partnerID=8YFLogxK
U2 - 10.1109/JSEN.2022.3226747
DO - 10.1109/JSEN.2022.3226747
M3 - Article
AN - SCOPUS:85144777645
SN - 1530-437X
VL - 23
SP - 1423
EP - 1435
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 2
ER -