A Four-Position Calibration Method of Inconsistent Angles between Units of TRUSINS

Liu, Jinyuan; Chen, Gang

doi:10.1109/cisce.2019.00123

Cited by 1 publication

(1 citation statement)

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“…However, with structures such as TRUSINS and URMINS, installation errors between modules have a detrimental effect on the system’s accuracy and must be compensated for [ 24 ]. The proposed methods used to calibrate errors of SINS are generally divided into direct and indirect methods.…”

Section: Introductionmentioning

confidence: 99%

A New Self-Calibration and Compensation Method for Installation Errors of Uniaxial Rotation Module Inertial Navigation System

Niu

Sun

et al. 2022

Sensors

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Calibration and compensation techniques are essential to improve the accuracy of the strap-down inertial navigation system. Especially for the new uniaxial rotation module inertial navigation system (URMINS), replacing faulty uniaxial rotation modules introduces installation errors between modules and reduces navigation accuracy. Therefore, it is necessary to calibrate these systems effectively and compensate for the installation error between modules. This paper proposes a new self-calibration and compensation method for installation errors without additional information and equipment. Using the attitude, velocity, and position differences between the two sets of navigation information output from URMINS as measurements, a Kalman filter is constructed and the installation error is estimated. After URMINS is compensated for the installation error, the average of the demodulated redundant information is taken to calculate the carrier’s navigation information. The simulation results show that the proposed method can effectively assess the installation error between modules with an estimation accuracy better than 5”. Experimental results for static navigation show that the accuracy of heading angle and positioning can be improved by 73.12% and 81.19% after the URMINS has compensated for the estimated installation errors. Simulation and experimental results further validate the effectiveness of the proposed self-calibration and compensation method.

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Section: Introductionmentioning

confidence: 99%