Next Article in Journal
Recent Surface Water Extent of Lake Chad from Multispectral Sensors and GRACE
Next Article in Special Issue
Multiple Fusion Based on the CCD and MEMS Accelerometer for the Low-Cost Multi-Loop Optoelectronic System Control
Previous Article in Journal
Robust Face Recognition Using the Deep C2D-CNN Model Based on Decision-Level Fusion
Previous Article in Special Issue
Error Analysis of Magnetohydrodynamic Angular Rate Sensor Combing with Coriolis Effect at Low Frequency
Open AccessArticle

An Optimization-Based Initial Alignment and Calibration Algorithm of Land-Vehicle SINS In-Motion

Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150080, China
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(7), 2081; https://doi.org/10.3390/s18072081
Received: 18 April 2018 / Revised: 23 June 2018 / Accepted: 24 June 2018 / Published: 28 June 2018
(This article belongs to the Special Issue Inertial Sensors and Systems 2018)
For a running freely land-vehicle strapdown inertial navigation system (SINS), the problems of self-calibration and attitude alignment need to be solved simultaneously. This paper proposes a complete alignment algorithm for the land vehicle navigation using Inertial Measurement Units (IMUs) and an odometer. A self-calibration algorithm is proposed based on the global observability analysis to calibrate the odometer scale factor and IMU misalignment angle, and the initial alignment and calibration method based on optimal algorithm is established to estimate the attitude and other system parameters. This new algorithm has the capability of self-initialization and calibration without any prior attitude and sensor noise information. Computer simulation results show that the performance of the proposed algorithm is superior to the extended Kalman filter (EKF) method during the oscillating attitude motions, and the vehicle test validates its advantages. View Full-Text
Keywords: strapdown inertial navigation system (SINS); initial alignment; odometer; optimized estimate; extended Kalman filter (EKF) strapdown inertial navigation system (SINS); initial alignment; odometer; optimized estimate; extended Kalman filter (EKF)
Show Figures

Figure 1

MDPI and ACS Style

Gao, K.; Ren, S.; Chen, X.; Wang, Z. An Optimization-Based Initial Alignment and Calibration Algorithm of Land-Vehicle SINS In-Motion. Sensors 2018, 18, 2081.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop