• Proceedings of the KIEE Conference
• /
• 2004.07d
• /
• pp.2218-2220
• /
• 2004

조종사 없이 사전에 입력된 프로그램 또는 인공지능에 의해 기체 스스로 판단하여 자율비행하는 비행체를 무인 항공기라 한다.[6] 이러한 비행을 위해서는 기체의 위치, 자세, 속도 등의 정보가 필요하다. 본 논문에서는 3축 가속도센서 1개 및 1축 자이로센서 3개를 서로 수직으로 구성하는 관성항법 시스템에 자기콤파스, 고도센서, GPS등의 비관성센서를 추가로 구성하여 시스템을 설계하였으며 칼만필터를 이용하여 시스템의 오차를 추정하고 이를 되먹임 시킴으로써 오차를 정정한다.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
• /
• 2003.05a
• /
• pp.149-156
• /
• 2003

This paper presents an underwater hybrid navigation system for a semi-autonomous underwater vehicle (SAUV). The navigation system consists of an inertial measurement unit (IMU), an ultra-short baseline (USBL) acoustic navigation sensor and a doppler velocity log (DVL) accompanying a magnetic compass. The errors of inertial measurement units increase with time due to the bias errors of gyros and accelerometers. A navigational system model is derived to include the error model of the USBL acoustic navigation sensor and the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 25 in the order. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors and correct the state equation when the measurements are available. Simulation was performed with the 6-d.o.f. equations of motion of SAUV in a lawn-mowing survey mode. The hybrid underwater navigation system shows good tracking performance by updating the error covariance and correcting the system's states with the measurement errors from a DVL, a magnetic compass and a depth senor. The error of the estimated position still slowly drifts in horizontal plane about 3.5m for 500 seconds, which could be eliminated with the help of additional USBL information.

• Journal of Advanced Navigation Technology
• /
• v.20 no.4
• /
• pp.314-320
• /
• 2016

Inertial navigation system (INS) has used aided systems and sensors to compensate navigation error. Global navigation satellite system (GNSS), velocity measurement sensor (VMS), and radar are commonly used to aid INS. Land navigation system (LNS) also mainly uses VMS when GNSS cannot be used such as at tunnel or on jammed scenario. A straight drive is required when VMS-aided navigation is used, because there is only speed of straight direction whereas no crossways and vertical directions. In local environment, even an expressway has lack of straight drive which is constraint of VMS-aided navigation algorithm. This paper proposes an enhanced VMS-aided navigation algorithm for LNS with indirect drive by restricting filter update condition. Also, there is a result of vehicle test to prove performance of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.8
• /
• pp.744-749
• /
• 2012

In this paper, we suggest that how to improve an accuracy of mobile robot's localization by using the sensor network information which fuses the machine vision camera, encoder and IMU sensor. The heading value of IMU sensor is measured using terrestrial magnetism sensor which is based on magnetic field. However, this sensor is constantly affected by its surrounding environment. So, we isolated template of ceiling using vision camera to increase the sensor's accuracy when we use IMU sensor; we measured the angles by pattern matching algorithm; and to calibrate IMU sensor, we compared the obtained values with IMU sensor values and the offset value. The values that were used to obtain information on the robot's position which were of Encoder, IMU sensor, angle sensor of vision camera are transferred to the Host PC by wireless network. Then, the Host PC estimates the location of robot using all these values. As a result, we were able to get more accurate information on estimated positions than when using IMU sensor calibration solely.

• Journal of Ocean Engineering and Technology
• /
• v.19 no.5 s.66
• /
• pp.71-77
• /
• 2005

This paper presents an integrated underwater navigational algorithm for unmanned underwater vehicles, using additional two-range transducers. This paper proposes a measurement model, using two range measurements, to improve the performance of an IMU-DVL (inertial measurement unit - Doppler velocity log) navigation system for long-time operation of underwater vehicles, excluding DVL measurement. Extended Kalman filter was adopted to propagate the error covariance, to update the measurement errors, and to correct the state equation when the external measurements are available. Simulation was conducted with the 6-d.o.f nonlinear numerical model of an AUV in lawn-mowing survey mode, at current flaw, where the velocity information is unavailable. Simulations illustrate the effectiveness of the integrated navigation system, assisted by the additional range measurements without DVL sensing.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.5
• /
• pp.190-196
• /
• 2015

In this paper, we propose multiple location error compensation algorithm for GPS/INS fusion using kalman filter and introduce the way to reduce location error in 9-axis navigation devices for implementing inertial navigation technique. When evaluating location, there is an increase of location error. So navigation systems need robust algorithms to compensate location error in GPS/INS fusion. In order to improve robustness of 9-axis inertial sensor(mpu-9150) over its disturbance, we used tilt compensation method using compensation algorithm of acceleration sensor and Yaw angle compensation to have exact azimuth information of the object. And it shows improved location result using these methods combined with kalman filter.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1429-1432
• /
• 2005

This work is towards the development of a low-cost, small-sized inertial navigation system(INS) which consists of 3 accelerometers, 3 semiconductor gyros and a magnetic compass sensor. This paper explains in detail the structure of the developed system and proposes a 3 dimensional attitude estimation algorithm with Indirect Kalman Filter. The experiments are performed with the developed system attached to a 6 DOF robot for showing the effectiveness of the algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.36 no.5
• /
• pp.462-471
• /
• 2008

Flight recoder is used to analyze the accident factors and prevent the accident. In the analysis of the flight recorder, the most important factor is how to estimate the precise location of the flight. Traditional aviation navigation is based on stable sensors such as DME and VOR. In order to enhance the precision of the location estimation, the integrated navigation algorithm is designed to incorporate DME, Air data sensors and INS(Inertial Navigation System). The results demonstrate that the proposed algorithm can achieve better accuracy, comparing with the traditional navigation schemes, in flight location estimation.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.10
• /
• pp.609-617
• /
• 2016

In general, Personal Navigation Systems (PNSs) can be defined systems to acquire pedestrian positional information. GPS is an example of PNS. However, GPS can only be used where the GPS signal can be received. Pedestrian Dead Reckoning (PDR) can estimate the positional information of pedestrians using Inertial Measurement Unit (IMU). Therefore, PDR can be used for GPS-disabled areas. This paper proposes a PDR scheme considering various movement types over GPS-disabled areas as combat environments. We propose a movement distance estimation scheme and movement direction estimation scheme as pedestrian's various movement types such as walking, running and crawling using IMU. Also, we propose a fusion algorithm between GPS and PDR to mitigate the lack of accuracy of positional information at the entrance to the building. The proposed algorithm has been tested in a real test bed. In the experimental results, the proposed algorithms exhibited an average position error distance of 5.64m and position error rate in goal point of 3.41% as a pedestrian traveled 0.6km.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.10
• /
• pp.2586-2592
• /
• 2014

Lost fishing gears become a major cause of marine pollution, and many policy and technical efforts have been conducted for that. For efficient retrieving lost fishing gears in underwater, It is important to know the current position. Using GPS in the sub-sea environment is impossible and localization requires the use of special systems, and mobility due to water currents for underwater localization also has to be considered. In this paper, described with respect to the system for a self-generated location informations without using an external signal, such as a GPS and Sonar and storing them. Using the characteristics of the geomagnetic and INS principle, proposed informations and a way for estimating self position during movement. Embedded based system suggested and implemented in this study is tested for validating it's functionality.