Open Access

ARTICLE

Complementary Kalman Filter as a Baseline Vector Estimator for GPS-Based Attitude Determination

Dah-Jing Jwo^{1, *}

1 Department of Communications, Navigation and Control Engineering, National Taiwan Ocean University, Keelung, 202-24, Taiwan.

* Corresponding Author: Dah-Jing Jwo. Email: .

Computers, Materials & Continua 2020, 65(2), 993-1014. https://doi.org/10.32604/cmc.2020.011592

Received 18 May 2020; Accepted 03 June 2020; Issue published 20 August 2020

Abstract

The Global Positioning System (GPS) offers the interferometer for attitude determination by processing the carrier phase observables. By using carrier phase observables, the relative positioning is obtained in centimeter level. GPS interferometry has been firstly used in precise static relative positioning, and thereafter in kinematic positioning. The carrier phase differential GPS based on interferometer principles can solve for the antenna baseline vector, defined as the vector between the antenna designated master and one of the slave antennas, connected to a rigid body. Determining the unknown baseline vectors between the antennas sits at the heart of GPS-based attitude determination. The conventional solution of the baseline vectors based on least-squares approach is inherently noisy, which results in the noisy attitude solutions. In this article, the complementary Kalman filter (CKF) is employed for solving the baseline vector in the attitude determination mechanism to improve the performance, where the receiversatellite double differenced observable was utilized as the measurement. By using the carrier phase observables, the relative positioning is obtained in centimeter level. Employing the CKF provides several advantages, such as accuracy improvement, reliability enhancement, and real-time assurance. Simulation results based on the conventional method where the least-squares approach is involved, and the proposed method where the CKF is involved are compared and discussed.

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Keywords

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