Litcius/Paper detail

Analysis and Improvement of Attitude Output Accuracy in Tri-Axis Rotational Inertial Navigation System

Zengjun Liu, Lei Wang, Kui Li, Hao Han

2020IEEE Sensors Journal28 citationsDOI

Abstract

Rotating modulation technique is a mature method which has been widely used in the rotational inertial navigation system (RINS). Inertial Measurement Unit (IMU) can be driven to rotate to modulate the inertial devices' errors, in this way the position accuracy of RINS can be greatly improved. However, the outputs of attitude are easily affected for the existence of rotation mechanism. The rotation mechanism of tri-axis RINS consists of three pairs of motors and photoelectric encoders. The errors of the rotation mechanism mainly contain the installation errors of the gimbals, the installation errors of photoelectric encoder and the zeroposition errors of the system; they have different effects on the outputs of the attitude. This paper researches the principle of attitude output accuracy loss in tri-axis RINS, the effects of different errors on attitude are analyzed and a self-calibration method based on recursive least squares (RLS) is proposed to calibrate these errors. Simulation and experiment results prove that the analyses is right and experiment results show that the proposed attitude compensation method can improve short-term attitude accuracy greatly, after the compensation, the attitude accuracy of the rotation direction is less than 12", and the attitude accuracy of the other direction is less than 8".

Topics & Concepts

GimbalControl theory (sociology)Inertial measurement unitRotation (mathematics)Compensation (psychology)EncoderComputer scienceRotary encoderInertial frame of referenceAttitude controlMechanism (biology)Inertial navigation systemAccelerometerSimulationEngineeringControl engineeringComputer visionPhysicsArtificial intelligenceAerospace engineeringPsychoanalysisQuantum mechanicsPsychologyControl (management)Operating systemInertial Sensor and NavigationTarget Tracking and Data Fusion in Sensor NetworksIndoor and Outdoor Localization Technologies