• Journal of Navigation and Port Research
• /
• v.35 no.10
• /
• pp.785-791
• /
• 2011

This paper describes the evaluation and selection of MEMS(Micro-Elect Mechanical System) based inertial sensor to fit to implement the Inertial Measurement Unit(IMU) for a small-sized vessel at sea. At first, the error model and the noise model of the inertial sensors are defined with Euler's equations and then, the inertial sensor evaluation is carried out with Allan Variance techniques and Monte Carlo simulation. As evaluation results for the five sensors, ADIS16405, SAR10Z, SAR100Grade100, LIS344ALH and ADXL103, the combination of gyroscope and accelerometer of ADIS16405 is shown minimum error having around 160 m/s standard deviation of velocity error and around 35 km standard deviation of position error after 600 seconds. Thus, we select the ADIS16405 inertial sensor as a MEMS-based inertial sensor to implement IMU and, the error reducing method is also considered with the search for reference papers.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.47 no.6
• /
• pp.438-445
• /
• 2019

In this paper, we present a new approach to extract the g-sensitivity scale-factor error for a MEMS gyroscope. MEMS gyroscopes, based on the use of both angular momentum and the Coriolis effect, have a g-sensitivity error due to mass unbalance. Generally, the g-sensitivity error is not considered in general use of gyroscopes, but it deserves our attention if we are to develop for tactical class performance and reliability. The g-sensitivity error during vehicle flight increases navigation error; so it must be analyzed and compensated for the use of MEMS IMU for high dynamics vehicle systems. Therefore, we analyzed how to extract the g-sensitivity scale-factor error from the inertial sensor error model. Furthermore we propose a new method to extract the g-sensitivity error using flight motion simulator. We verified our proposed method with experimental results.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2011.11a
• /
• pp.191-192
• /
• 2011

MEMS 기반 관성 센서를 이용한 항법장치를 개발하는 경우, 칼만 필터(Kalman Filter, KF) 구축 여부에 따라 그 성능이 결정된다. 특히 해상에서 이러한 MEMS 기반 관성항법 장치를 사용하는 경우에는, 육상과 달리 다양한 제약조건이 따르게 된다. KF는 선형과 비선형으로 구분되고, 비선형은 다시 확장 KF와 Unscented KF, Particle KF 등 다양한 것이 연구 개발되어 있는데, 해상에 적용하기 위해서는 이러한 다양한 필터들의 특징과 추가 요청사항 등을 사전 조사할 필요가 있다. 본 연구에서는 기존 개발된 KF를 조사하여 해상용 MEMS 기반 관성 항법장치를 개발하는 경우 필요한 필터 구성 방법을 조사하여 문제점을 살펴보고, 이 문제 해결을 위한 방안을 검토하였다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.10
• /
• pp.1822-1829
• /
• 2008

Calibration of an MEMS inertial measurement unit is very important process for obtaining precise navigation performance. In this paper, one method is proposed to overcome a limitations on cost and efficiency using a relatively higher grade sensor and a rate table. The same dynamic input is applied to both the reference and the target sensors during and after calibration process, then the results are analyzed. The experimental results show that the proposed method is very effective and useful in practice.

• Current Research on Agriculture and Life Sciences
• /
• v.32 no.2
• /
• pp.79-84
• /
• 2014

The precision aerial application of agricultural unmanned helicopters has become a new paradigm for small farms with orchards, paddy, and upland fields. The needs of agricultural applications require easy and affordable control systems. Recent developments of MEMS technology based on inertial sensors and high speed DSP have enabled the fabrication of low-cost attitude system. Therefore, this study evaluates inertial MEMS sensors for estimating the attitude of an agricultural unmanned helicopter. The accuracies and errors of gyro and acceleration sensors were verified using a pendulum system. The true motion values were calculated using a theoretical estimation and absolute encoder measurement of the pendulum, and then the sensor output was compared with reference values. When comparing the sensor measurements and true values, the errors were determined to be 4.32~5.72%, 3.53~6.74%, and 3.91~4.16% for the gyro rate and x-, z- accelerations, respectively. Thus, the measurement results confirmed that the inertial sensors are effective for establishing an attitude and heading reference system (AHRES). The sensors would be constructed in gimbals for the estimating and proving attitude measurements in the following paper.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.1
• /
• pp.177-186
• /
• 2017

Recently, Autonomous vehicles are getting hot attention. Amazon, the biggest online shopping service provider is developing a delivery system that uses drones. This kinds of platforms are need accurate attitude information for navigation. In this paper, a structure design of AHRS using low-cost inertia sensor is proposed. To estimate attitudes a Kalman filter which uses a quaternion based dynamic model, bias-removed measurements from MEMS Gyro, raw measurements from MEMS accelerometer and magnetometer, is designed. To remove bias from MEMS Gyro, an additional Kalman filter which uses raw Gyro measurements and attitude estimates, is designed. The performance of implemented AHRS is compared with high price off-the-shelf 3DM-GX3-25 AHRS from Microstrain. The Gyro bias was estimated within 0.0001[deg/s]. And from the estimated attitude, roll and pitch angle error is smaller than 0.2 and 0.3 degree. Yaw angle error is smaller than 6 degree.

• 한국HCI학회:학술대회논문집
• /
• 2007.02a
• /
• pp.379-385
• /
• 2007

관성 센서는 외부 장치의 도움 없이 3차원 공간상에서 움직임 측정이 가능하다. 최근 MEMS 기술의 발달로 소형 저가 관성 센서(가속도 센서 혹은 각속도 센서) 제작이 가능해져 관성 센서를 소형 휴대 기기에 내장하여 사용자의 움직임을 감지하거나 의도 파악하는 연구가 진행되고 있다. 본 연구에서는 관성 센서가 내장된 휴대 기기를 이용하여 3차원 공간상에서 6가지 위치에 따라서 각기 다른 6가지 소리를 발생하는 가상의 멀티 타악기 시스템을 제안한다. 즉, 휴대 기기를 상/하로 흔들면 가상 타악기의 타점 위치에 왔을 때 비트 음을 발생하고, 6개의 다른 위치를 구분하여 다른 타점의 위치에서 휴대 기기를 흔들면 각각 그 위치와 미리 지정된 소리가 발생하도록 하였다. 이러한 가상의 멀티 타악기 시스템을 위해서 3차원 공간상에서 실시간으로 사용자의 움직임을 감지하고 휴대 기기의 위치를 파악하는 것이 필요하다. 저가의 관성 센서를 이용하여 사용자가 휴대 기기를 움직이는 동작이 있는 상황에서 실시간으로 휴대 기기의 위치를 추정하는 것은 쉽지 않지만 본 연구에서는 다양한 사용자의 움직임 동작 분석을 통하여 사용자가 가상의 멀티 타악기를 상/하로 흔드는 동작을 감지하고 다른 위치로 이동하는 동작을 구분하였다. 개발된 동작 감지 알고리즘과 위치 구분 알고리즘을 휴대 기기에 적용되어 실제로 가상의 타악기 시스템을 구현하였다.

• The Magazine of the IEIE
• /
• v.31 no.1
• /
• pp.28-37
• /
• 2004

• Electrical & Electronic Materials
• /
• v.21 no.8
• /
• pp.11-17
• /
• 2008

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.46 no.3
• /
• pp.22-30
• /
• 2009

GPS and INS integrated systems are expected to become commonly available as a result of low cost Micro-Electro-Mechanical Sensor (MEMS) technology. However, the current performance achieved by low cost sensors is still relatively poor due to the large inertial sensor errors. This is particularly prevalent in the urban environment where there are significant periods of restricted sky view. To reduce the inertial sensor error, GPS and low cost INS are integrated using a Loosely Coupled Kalman Filter architecture which is appropriate in most applications where there is good satellite availability. In this paper, we present the GPS/INS sensor Integration using Loosely Coupled Kalman Filter approach. We also compare the simulation results of Wander Azimuth Strapdown Mechanization Scheme with the reference values generated by the ZH35C trajectory simulator that is describe mathematically either by the geometry of the path, or as the position of the object over time.