Litcius/Paper detail

A High-Accuracy GPS-Aided Coarse Alignment Method for MEMS-Based SINS

Yulong Huang, Zheng Zhang, Siyuan Du, Youfu Li, Yonggang Zhang

2020IEEE Transactions on Instrumentation and Measurement78 citationsDOI

Abstract

In order to improve the computational efficiency and alignment accuracy of a microelectromechanical system (MEMS)-based strap-down inertial navigation system (SINS), this article proposes a high-accuracy global positioning system (GPS)-aided coarse alignment method. The attitude matrix between current and initial body frames and the unknown gyro bias, accelerometer bias, and lever arm are jointly estimated based on the proposed closed-loop approach, where the attitude error and unknown parameters are jointly inferred based on the derived linear state-space model using the Kalman filter. Simulation and experimental results illustrate that the proposed GPS-aided coarse alignment method can achieve better accuracy than existing state-of-the-art coarse alignment methods for MEMS-based SINS.

Topics & Concepts

Global Positioning SystemInertial navigation systemKalman filterAccelerometerComputer scienceMicroelectromechanical systemsGPS/INSControl theory (sociology)Inertial measurement unitComputer visionInertial frame of referenceArtificial intelligenceAssisted GPSPhysicsQuantum mechanicsControl (management)Operating systemTelecommunicationsInertial Sensor and NavigationIndoor and Outdoor Localization TechnologiesTarget Tracking and Data Fusion in Sensor Networks