Gravity Matching Algorithm Based on Correlation Filter

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.

Automated summary

The article proposes a gravity-matching algorithm based on a correlation filter to reduce the impact of gravity measurement error and initial position error on matching accuracy. The trajectory shape of the inertial navigation system is used as a constraint to improve matching accuracy. Experimental results demonstrate the effectiveness of the method in improving matching accuracy under initial position error and gravity measurement error.