Research on Automatic Joint Calibration Method of Multi 3D-LIDARs and Inertial Measurement Unit

2021 ◽  
Author(s):  
Jinghua Zhang ◽  
Rui He ◽  
Jian Wu ◽  
Shuai Li ◽  
Xuesong Chen ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Calibration Method ◽  
Measurement Unit ◽  
Inertial Measurement

Systematic Calibration Method for FOG Inertial Measurement Units

2013 ◽  
Vol 662 ◽  
pp. 717-720 ◽  
Author(s):  
Zhen Yu Zheng ◽  
Yan Bin Gao ◽  
Kun Peng He
Keyword(s):  
Inertial Measurement Unit ◽  
Inertial Sensors ◽  
Calibration Method ◽  
State Equation ◽  
Measurement Unit ◽  
Observation System ◽  
Body Frame ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Error Coefficients

As an inertial sensors assembly, the FOG inertial measurement unit (FIMU) must be calibrated before being used. The paper presents a one-time systematic IMU calibration method only using two-axis low precision turntable. First, the detail error model of inertial sensors using defined body frame is established. Then, only velocity taken as observation, system 33 state equation is established including the lever arm effects and nonlinear terms of scale factor error. The turntable experiments verify that the method can identify all the error coefficients of FIMU on low-precision two-axis turntable, after calibration the accuracy of navigation is improved.

scholarly journals Scalar Method of Fault Diagnosis of Inertial Measurement Unit

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Vadym Avrutov
Keyword(s):  
Fault Diagnosis ◽  
Inertial Measurement Unit ◽  
Calibration Method ◽  
Quality Monitoring ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Working Capacity ◽  
Element Determination ◽  
Inertial Measurement ◽  
Algorithm Verification

The scalar method of fault diagnosis systems of the inertial measurement unit (IMU) is described. All inertial navigation systems consist of such IMU. The scalar calibration method is a base of the scalar method for quality monitoring and diagnostics. In accordance with scalar calibration method algorithms of fault diagnosis systems are developed. As a result of quality monitoring algorithm verification is implemented in the working capacity monitoring of IMU. A failure element determination is based on diagnostics algorithm verification and after that the reason for such failure is cleared. The process of verifications consists of comparison of the calculated estimations of biases, scale factor errors, and misalignments angles of sensors to their data sheet certificate, kept in internal memory of computer. As a result of such comparison the conclusion for working capacity of each IMU sensor can be made and also the failure sensor can be determined.

A Rapid Field Calibrating Method for MIMU

2011 ◽  
Vol 80-81 ◽  
pp. 1140-1144
Author(s):  
Yu Bao Fan ◽  
Jie Li ◽  
Bo Wang ◽  
Xiao Chun Tian ◽  
Jun Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Operation Time ◽  
Calibration Method ◽  
Least Square ◽  
Measurement Unit ◽  
Calibration Model ◽  
Time Saving ◽  
Inertial Measurement ◽  
Field Calibration ◽  
Calibration Program

When the Micro Inertial Measurement Unit is been placed randomly in the case of stationary, the sum vectors that measured by the inertial devices configured orthogonally along three axis, are constant vectors. In view of the above objective facts, a field calibration method of micro inertial measurement unit was proposed. On the base of the establishment and optimization of calibration model, all parameters to be calibrated can be obtained through the least square by the ellipsoid fitting, with the result of high-precision field calibration for micro inertial measurement unit. Finally, a filed calibration program for micro inertial measurement unit is scheduled reasonably. The experiment results show that the method has such characteristics such as easily-operation, time-saving, higher calibration accuracy, and not depending on the baseline direction and datum offered by precision instruments. Especially, it fits for inertial measurement systems which work short time and ask for high accuracy. In addition, it can also significantly increase the measurement accuracy of micro inertial measurement system in practical application.

scholarly journals Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment

2019 ◽  
Vol 11 (4) ◽  
pp. 442 ◽  
Author(s):  
Zhen Li ◽  
Junxiang Tan ◽  
Hua Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Point Clouds ◽  
Calibration Method ◽  
Satellite System ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Self Calibration ◽  
Global Navigation Satellite ◽  
Mean Square Errors ◽  
Scanning Systems

Mobile LiDAR Scanning (MLS) systems and UAV LiDAR Scanning (ULS) systems equipped with precise Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) positioning units and LiDAR sensors are used at an increasing rate for the acquisition of high density and high accuracy point clouds because of their safety and efficiency. Without careful calibration of the boresight angles of the MLS systems and ULS systems, the accuracy of data acquired would degrade severely. This paper proposes an automatic boresight self-calibration method for the MLS systems and ULS systems using acquired multi-strip point clouds. The boresight angles of MLS systems and ULS systems are expressed in the direct geo-referencing equation and corrected by minimizing the misalignments between points scanned from different directions and different strips. Two datasets scanned by MLS systems and two datasets scanned by ULS systems were used to verify the proposed boresight calibration method. The experimental results show that the root mean square errors (RMSE) of misalignments between point correspondences of the four datasets after boresight calibration are 2.1 cm, 3.4 cm, 5.4 cm, and 6.1 cm, respectively, which are reduced by 59.6%, 75.4%, 78.0%, and 94.8% compared with those before boresight calibration.

scholarly journals A Separated Calibration Method for Inertial Measurement Units Mounted on Three-Axis Turntables

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2846 ◽  
Author(s):  
Chun-mei Dong ◽  
Shun-qing Ren ◽  
Xi-jun Chen ◽  
Zhen-huan Wang
Keyword(s):  
Inertial Measurement Unit ◽  
Functional Relationship ◽  
Calibration Method ◽  
Measurement Unit ◽  
Model Parameters ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Suboptimal Design ◽  
Calibration Accuracy ◽  
Simulation Results

Inertial Measurement Unit (IMU) calibration accuracy is easily affected by turntable errors, so the primary aim of this study is to reduce the dependence on the turntable’s precision during the calibration process. Firstly, the indicated-output of the IMU considering turntable errors is constructed and with the introduction of turntable errors, the functional relationship between turntable errors and the indicated-output was derived. Then, based on a D-suboptimal design, a calibration method for simultaneously identifying the IMU error model parameters and the turntable errors was proposed. Simulation results showed that some turntable errors could thus be effectively calibrated and automatically compensated. Finally, the theoretical validity was verified through experiments. Compared with the traditional method, the method proposed in this paper can significantly reduce the influence of the turntable errors on the IMU calibration accuracy.

scholarly journals Research on the Calibration Method of Micro Inertial Measurement Unit for Engineering Application

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Yun Xu ◽  
Yu Wang ◽  
Yan Su ◽  
Xinhua Zhu
Keyword(s):  
Inertial Measurement Unit ◽  
Compensation Effect ◽  
Rapid Development ◽  
Engineering Application ◽  
Calibration Method ◽  
Measurement Precision ◽  
Parameters Estimation ◽  
Measurement Unit ◽  
Calibration Model ◽  
Inertial Measurement

With rapid development of micro fabrication technology, the production level of micro inertial devices has increased, which promoted the performance improvement of Micro Inertial Measurement Unit (MIMU). Measurement precision of MIMU is one of the most significant indexes, especially for the application of the guided spinning projectiles. In order to improve the measurement precision of MIMU, this paper presents a novel calibration method. The calibration model is established and the derivation for parameters estimation has been introduced. By the multirate tests and multiposition tests, all the parameters in the calibration model can be well estimated. Verification experiment shows that the proposed method has the same compensation effect as the traditional method, but it can alleviate the computing burden for the system. Thus the proposed method will have a wide application prospect for the future engineering calibration.

scholarly journals A Novel Calibration Method for Gyro-Accelerometer Asynchronous Time in Foot-Mounted Pedestrian Navigation System

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 209
Author(s):  
Tianyu Chen ◽  
Gongliu Yang ◽  
Qingzhong Cai ◽  
Zeyang Wen ◽  
Wenlong Zhang
Keyword(s):  
Attitude Change ◽  
Navigation System ◽  
Inertial Measurement Unit ◽  
Detection Method ◽  
Calibration Method ◽  
Sampling Time ◽  
Measurement Unit ◽  
Positioning Accuracy ◽  
Inertial Measurement ◽  
Pedestrian Navigation

Pedestrian Navigation System (PNS) is one of the research focuses of indoor positioning in GNSS-denied environments based on the MEMS Inertial Measurement Unit (MIMU). However, in the foot-mounted pedestrian navigation system with MIMU or mobile phone as the main carrier, it is difficult to make the sampling time of gyros and accelerometers completely synchronous. The gyro-accelerometer asynchronous time affects the positioning of PNS. To solve this problem, a new error model of gyro-accelerometer asynchronous time is built. The effect of gyro-accelerometer asynchronous time on pedestrian navigation is analyzed. A filtering model is designed to calibrate the gyro-accelerometer asynchronous time, and a zero-velocity detection method based on the rate of attitude change is proposed. The indoor experiment shows that the gyro-accelerometer asynchronous time is estimated effectively, and the positioning accuracy of PNS is improved by the proposed method after compensating for the errors caused by gyro-accelerometer asynchronous time.

scholarly journals Automatic Data Selection and Boresight Adjustment of LiDAR Systems

2019 ◽  
Vol 11 (9) ◽  
pp. 1087 ◽  
Author(s):  
Rabine Keyetieu ◽  
Nicolas Seube
Keyword(s):  
Inertial Measurement Unit ◽  
Calibration Method ◽  
Data Selection ◽  
Measurement Unit ◽  
Automatic Calibration ◽  
Selection Algorithm ◽  
Lidar System ◽  
Automatic Data ◽  
Inertial Measurement ◽  
Line Patterns

This paper details a new automatic calibration method for the boresight angles between a LiDAR (Light Detection and Ranging) and an inertial measurement unit (IMU), based on a data selection algorithm, followed by the adjustment of boresight angles. This method, called LiDAR-IMU boresight automatic calibration (LIBAC), takes in input overlapping survey strips following simple line patterns over regular slopes. We first construct a boresight error observability criterion, used to select automatically the most sensitive points to boresight errors. From these points, we adjust the boresight angles. From a statistical analysis of the adjustment results, we derive the boresight angle precision. Results obtained with LIBAC on several LiDAR system integrated within drones are presented. We also give results about the reproducibility of the method.

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