Inertial measurement unit based indoor localization for construction applications

A rotational inertial navigation system (RINS) has been wildly used in long term marine navigation. In a dual-axis RINS, with all constant biases averaged out, the errors which can not be averaged out become the main error source. In this paper, the gyro geomagnetic biases of a dual-axis RINS are modelled, analysed and calibrated. The gyro geomagnetic biases are proved unable to be averaged out, but can be modulated to be a constant value in the navigation frame. A slope error term of longitude error is found to be caused by gyro geomagnetic biases in north and upward directions, which increases linearly with time and is remarkable in long term navigation. Thus, a calibration method based on least square regression is proposed to compensate the slope error term. Laboratory and sailing experimental results show that the divergence speed of longitude error can be effectively slowed down by the compensation of gyro geomagnetic biases. In long term independent navigation, the position accuracy of dual-axis RINS is improved about 50% by the calibration method proposed in this paper.

https://iopscience.iop.org/article/10.1088/0957-0233/27/10/105001/pdf

Analysis and calibration of the gyro bias caused by geomagnetic field in a dual-axis rotational inertial navigation system

In the dual-axis rotation inertial navigation system (INS), besides the gyro error, accelerometer error, rolling misalignment angle error, and the gimbal angle error, the shaft swing angle and the axis non-orthogonal angle also affect the attitude accuracy. Through the analysis of the structure, we can see that the shaft swing angle and axis non-orthogonal angle will produce coning errors which cause the fluctuation of the attitude. According to the analysis of the rotation vector, it can be seen that the coning error will generate additional drift velocity along the rotating shaft, which can reduce the navigation precision of the system. In this paper, based on the establishment of the modulation average frame, the vector projection is carried out, and then the attitude conversion matrix and the attitude error matrix mainly including the shaft swing angle and axis non-orthogonal are obtained. Because the attitude angles are given under the static condition, the shaft swing angle and the axis non-orthogonal angle are estimated by the static Kalman filter (KF). This kind of KF method has been widely recognized as the standard optimal estimation tool for estimating the parameters such as coning angles (α1 , α2), initial phase angles (ϕ1,ϕ2), and the non-perpendicular angle (η). In order to carry out the system level verification, a dual axis rotation INS is designed. Through simulation and experiments, the results show that the amplitudes of the attitude angles’ variation are reduced by about 20%–30% when the shaft rotates. The attitude error equation is reasonably simplified and the calibration method is accurate enough. The attitude accuracy is further improved.

https://www.mdpi.com/1424-8220/17/3/615/pdf

Accurate Compensation of Attitude Angle Error in a Dual-Axis Rotation Inertial Navigation System

An inertial device biases on-line monitoring method in the applications of two rotational inertial navigation systems redundant configuration

This paper proposes a novel gyro drift estimation method for the inertial navigation system (INS), which introduces the particle swarm optimization (PSO) algorithm into the error estimation problem. PSO-based estimation model is established. The position error and velocity error of INS are considered as the performance criterions of the PSO fitness function. Compared with the traditional gyro drift estimation methods, the advantages or contributions of the proposed method can be summarized as follows: 1) the proposed method does not require any prior information about inertial sensor error or observation noise; 2) particular motion for the carrier of INS is not needed, and; 3) the external information provided by other navigation systems could be discontinuous. The simulation experiments and field tests are performed, which validate the efficacy of the proposed method.

/pdf/particle-swarm-optimization-based-gyro-drift-estimation-4mfj6sy0m9.pdf

Particle Swarm Optimization-Based Gyro Drift Estimation Method for Inertial Navigation System

A dual-axis rotational Inertial Navigation System (INS) has received wide attention in recent years because of high performance and low cost. However, some errors of inertial sensors such as stochastic errors are not averaged out automatically during navigation. Therefore a Twice Position-fix Reset (TPR) method is provided to enhance accuracy of a dual-axis rotational INS by compensating stochastic errors. According to characteristics of an azimuth error introduced by stochastic errors of an inertial sensor in the dual-axis rotational INS, both an azimuth error and a radial-position error are much better corrected by the TPR method based on an optimised error propagation equation. As a result, accuracy of the dual-axis rotational INS is prominently enhanced by the TPR method, as is verified by simulations and field tests.

/pdf/compensation-for-stochastic-error-of-gyros-in-a-dual-axis-2txvimkez7.pdf

Jin Yue

Papers

Compensation for Stochastic Error of Gyros in a Dual-axis Rotational Inertial Navigation System