Research on Temperature Compensation Technology of Micro-Electro-Mechanical Systems Gyroscope in Strap-Down Inertial Measurement Unit

2018 ◽  
pp. 10-16
Author(s):  
Ying Liu ◽  
Cong Liu ◽  
Jintao Xu ◽  
Xiaodong Zhao
Keyword(s):  
Inertial Measurement Unit ◽  
Temperature Compensation ◽  
Mechanical Systems ◽  
Measurement Unit ◽  
Micro Electro Mechanical Systems ◽  
Inertial Measurement

scholarly journals A Novel Fault-Tolerant Navigation and Positioning Method with Stereo-Camera/Micro Electro Mechanical Systems Inertial Measurement Unit (MEMS-IMU) in Hostile Environment

Micromachines ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 626 ◽  
Author(s):  
Cheng Yuan ◽  
Jizhou Lai ◽  
Pin Lyu ◽  
Peng Shi ◽  
Wei Zhao ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Fault Tolerant ◽  
Mechanical Systems ◽  
Measurement Unit ◽  
Hostile Environment ◽  
Micro Electro Mechanical Systems ◽  
Inertial Measurement ◽  
Stereo Camera ◽  
Positioning Method ◽  
Mems Imu

Visual odometry (VO) is a new navigation and positioning method that estimates the ego-motion of vehicles from images. However, VO with unsatisfactory performance can fail severely in hostile environment because of the less feature, fast angular motions, or illumination change. Thus, enhancing the robustness of VO in hostile environment has become a popular research topic. In this paper, a novel fault-tolerant visual-inertial odometry (VIO) navigation and positioning method framework is presented. The micro electro mechanical systems inertial measurement unit (MEMS-IMU) is used to aid the stereo-camera, for a robust pose estimation in hostile environment. In the algorithm, the MEMS-IMU pre-integration is deployed to improve the motion estimation accuracy and robustness in the cases of similar or few feature points. Besides, a dramatic change detector and an adaptive observation noise factor are introduced, tolerating and decreasing the estimation error that is caused by large angular motion or wrong matching. Experiments in hostile environment showing that the presented method can achieve better position estimation when compared with the traditional VO and VIO method.

New Drift Reset Method for Pedestrian Tracking with a Low-Cost IMU

2013 ◽  
Vol 284-287 ◽  
pp. 2176-2180 ◽  
Author(s):  
Yao Tung Chuang ◽  
Cheng Ta Shen ◽  
Yi Lin Hsu ◽  
Sheng Wen Shih
Keyword(s):  
Inertial Measurement Unit ◽  
Temperature Compensation ◽  
Tracking System ◽  
Low Cost ◽  
Measurement Unit ◽  
Position Tracking ◽  
Pedestrian Tracking ◽  
Inertial Measurement ◽  
Rate Gyro ◽  
Global Reference Frame

In this work, we study the pedestrian position tracking problem using a foot-mounted inertial measurement unit (IMU). The IMU consists of a tri-axis rate-gyro, a tri-axis accelerometer and a tri-axis magnetometer. The magnetometer is used for constructing a global reference frame at the initial phase. The pedestrian orientation and position are estimated by integrating signals of the rate-gyro and the accelerometer. Since the integration operation usually introduces unbounded drift errors, a new drift reset method derived from a constant-ground-normal condition is proposed to compensate for the accumulated drift error. Furthermore, a temperature compensation (TC) method is described which can alleviate the rate-gyro error due to temperature variation. Real experiments have been conducted with six subjects to test the performance of the proposed method and the results show the promising performance of the proposed tracking system.

Research on the Temperature Compensation Method for Micro Inertial Measurement Unit

2013 ◽  
Vol 823 ◽  
pp. 228-231
Author(s):  
Dan Wang ◽  
Guo Wei Gao ◽  
Fang Wei Cui ◽  
Zhen Song
Keyword(s):  
Kalman Filtering ◽  
Inertial Measurement Unit ◽  
Temperature Compensation ◽  
Stepwise Regression ◽  
Measurement Accuracy ◽  
Measurement Unit ◽  
Zero Bias ◽  
Inertial Measurement ◽  
Temperature Characteristics ◽  
Multiple Variables

In this paper, the temperature characteristics of Micro Inertial Measurement Unit (MIMU) were studied for improving its stability. The temperature error model was built on the basis of analyzing its temperature characteristics. The model combined zero bias and calibration factors for MEMS accelerometers and gyros with multiple variables and it was optimized by the stepwise regression method. Meanwhile, combined with Kalman filtering theory, using Kalman filtering to reduce the noise of the temperature measurement could further improve the compensation accuracy and measurement accuracy.

MEMS Gyroscope Null Drift and Compensation Based on Neural Network

2011 ◽  
Vol 255-260 ◽  
pp. 2077-2081 ◽  
Author(s):  
Jaw Kuen Shiau ◽  
Der Ming Ma ◽  
Chen Xuan Huang ◽  
Ming Yu Chang
Keyword(s):  
Neural Network ◽  
Inertial Measurement Unit ◽  
Temperature Compensation ◽  
Micro Electro Mechanical System ◽  
Measurement Unit ◽  
Temperature Calibration ◽  
Inertial Measurement ◽  
Mems Gyroscope ◽  
Measurement Units ◽  
Effects Of Temperature

This study investigates the effects of temperature on micro-electro mechanical system (MEMS) gyroscope null drift and methods and efficiency of temperature compensation. First, this study uses in-house-designed inertial measurement units (IMUs) to perform temperature effect testing. The inertial measurement unit is placed into the temperature control chamber. Then, the temperature is gradually increased from 25 °C to 80 °C at approximately 0.8 degrees per minute. After that, the temperature is decreased to -40 °C and then returning to 25 °C. During these temperature variations, the temperature and static gyroscope output observes the gyroscope null drift phenomenon. The results clearly demonstrate the effects of temperature on gyroscope null voltage. A temperature calibration mechanism is established by using a neural network model. With the temperature calibration, the attitude computation problem due to gyro drifts can be improved significantly.

scholarly journals Comparison of Seismocardiography Based Heart Rate Measurement Method

2020 ◽  
Vol 55 (6) ◽  
Author(s):  
Bayu Erfianto ◽  
Achmad Rizal ◽  
Vera Suryani
Keyword(s):  
Heart Rate ◽  
Inertial Measurement Unit ◽  
Digital Signal ◽  
Measurement Unit ◽  
Fiducial Point ◽  
Micro Electro Mechanical Systems ◽  
Inertial Measurement ◽  
Packet Filter ◽  
Mode Decomposition ◽  
Time Period

The article describes a new alternative method of detecting the Aorta Open fiducial point based on digital signal processing formulated from the average seismocardiogram cycle obtained from the 6-degree-of-freedom Micro Electro-Mechanical Systems Inertial Measurement Unit, enabling estimation of heartbeat during heart muscle contraction without reference to electrocardiogram time period. Using the seismocardiography data obtained from the Inertial Measurement Unit, the authors then process the data using two methods: 1) Empirical Mode Decomposition and 2) Jerk signal, which is extracted as a first derivative of the Inertial Measurement Unit signal. As an example, we compare the two proposed methods to the existing method. Our Method 2 allows us to detect Aorta Open-Aorta Open value between 400ms and 450ms using Berkeley Packet Filter 5-15 Hz with dynamic peak threshold from the Hilbert envelope. Thus, the evaluation of the new method’s effectiveness is confirmed by the estimation of the Aorta Open-Aorta Open fiducial point as closer to the reference. Therefore, the result of our research, especially using jerk signal, can be considered a more accurate alternative for estimating heart rate or heartbeat based on seismocardiogram.

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