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Oh, S.M. (2007) Nonlinear Estimation Techniques for Vision-Based Air-to-Air Tracking. School of Aerospace Engineering, Georgia Institute of Technology, Atlanta.

has been cited by the following article:

• TITLE: A Quaternion Scaled Unscented Kalman Estimator for Inertial Navigation States Determination Using INS/GPS/Magnetometer Fusion

  AUTHORS: Wassim Khoder, Bassem Jida

  KEYWORDS: Inertial Navigation System, Inertial Sensor Model, GPS, Magnetometer, Quaternion Attitude Parameterization, Rotation Vector, Scaled Augmented Unscented Kalman Filter

  JOURNAL NAME: Journal of Sensor Technology, Vol.4 No.2, June 27, 2014

  ABSTRACT: This Inertial Navigation System (INS), Global Positioning System (GPS) and fluxgate magnetometer technologies have been widely used in a variety of positioning and navigation applications. In this paper, a low cost solid state INS/GPS/Magnetometer integrated navigation system has been developed that incorporates measurements from an Inertial Navigation System (INS), Global Positioning System (GPS) and fluxgate magnetometer (Mag.) to provide a reliable complete navigation solution at a high output rate. The body attitude estimates, especially the heading angle, are fundamental challenges in a navigation system. Therefore targeting accurate attitude estimation is considered a significant contribution to the overall navigation error. A better estimation of the body attitude estimates leads to more accurate position and velocity estimation. For that end, the aim of this research is to exploit the magnetometer and accelerometer data in the attitude estimation technique. In this paper, a Scaled Unscented Kalman Filter (SUKF) based on the quaternion concept is designed for the INS/GPS/Mag integrated navigation system under large attitude error conditions. Simulation and experimental results indicate a satisfactory performance of the newly developed model.