LAUSR

In this article, a new position loci-based in-motion initial alignment method is proposed for a low-cost attitude and heading reference system (AHRS). A new sliding-window-based position integration method is proposed to construct the position vector observations, which weakens the accumulated errors induced by the inertial measurement unit (IMU) bias errors in vector observations. Also, a new closed-loop method is proposed to jointly estimate the time-varying body attitude matrix and the unknown IMU biases and global position system (GPS) lever-arm based on the Kalman filter. The estimates of the time-varying body attitude matrix, IMU biases, and GPS lever-arm are all used to construct and compensate for the position vector observations, which improves the alignment accuracy. Both the simulation and car-mounted test results illustrate that the proposed alignment method can achieve better alignment accuracy than these existing methods for a position loci-aided low-cost AHRS.