TY - JOUR
T1 - Gravity Matching Algorithm Based on Correlation Filter
AU - Zhao, Shengwu
AU - Xiao, Xuan
AU - Deng, Zhihong
AU - Shi, Lei
N1 - Publisher Copyright:
© 2001-2012 IEEE.
PY - 2023/2/1
Y1 - 2023/2/1
N2 - The gravity-matching algorithm is one of the key technologies in the gravity-aided inertial navigation system (GAINS). The matching accuracy determines the correction accuracy of the inertial navigation system (INS). However, the initial position error of the INS and gravity measurement error lead to a decrease in matching accuracy. In this article, the characteristics of gravity measurement error and inertial navigation information are made full use of to reduce the impact on matching. A gravity-matching algorithm based on a correlation filter (CF) is proposed, which includes preprocessing, CF, and mismatch detection. Meanwhile, the shape of the INS trajectory is used as a constraint to reduce the mismatch caused by the measurement error to improve the matching accuracy. Moreover, two matching strategies are given, including normal matching and sliding window matching. Experimental results show that the proposed method can effectively improve the matching accuracy under initial position error and gravity measurement error.
AB - The gravity-matching algorithm is one of the key technologies in the gravity-aided inertial navigation system (GAINS). The matching accuracy determines the correction accuracy of the inertial navigation system (INS). However, the initial position error of the INS and gravity measurement error lead to a decrease in matching accuracy. In this article, the characteristics of gravity measurement error and inertial navigation information are made full use of to reduce the impact on matching. A gravity-matching algorithm based on a correlation filter (CF) is proposed, which includes preprocessing, CF, and mismatch detection. Meanwhile, the shape of the INS trajectory is used as a constraint to reduce the mismatch caused by the measurement error to improve the matching accuracy. Moreover, two matching strategies are given, including normal matching and sliding window matching. Experimental results show that the proposed method can effectively improve the matching accuracy under initial position error and gravity measurement error.
KW - Correlation filter (CF)
KW - gravity-aided navigation
KW - inertial navigation system (INS) error
KW - matching algorithm
UR - http://www.scopus.com/inward/record.url?scp=85146257320&partnerID=8YFLogxK
U2 - 10.1109/JSEN.2022.3228559
DO - 10.1109/JSEN.2022.3228559
M3 - Article
AN - SCOPUS:85146257320
SN - 1530-437X
VL - 23
SP - 2618
EP - 2629
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 3
ER -