• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.11
• /
• pp.159-166
• /
• 2012

There are several ways such as GPS(Global Positioning System) and INS (Inertial Navigation System) to track the location of moving vehicle. The GPS has the advantages of having non-accumulative error even if it brings about errors. In order to obtain the position information, we need to receive at least 3 satellites information. But, the weak point is that GPS is not useful when the 혠 signal is weak or it is in the incommunicable region such as tunnel. In the case of INS, the information of the position and posture of mobile with several Hz~several hundreds Hz data speed is recorded for velocity, direction. INS shows a very precise navigational performance for a short period, but it has the disadvantage of increasing velocity components because of the accumulated error during integration over time. In this paper, sensor fusion algorithm is applied to both of INS and GPS for the position information to overcome the drawbacks. The proposed system gets an accurate position information from experiment using SVD in a non-accessible GPS terrain.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.11 no.11
• /
• pp.1031-1038
• /
• 2016

In the UAVs, the position error of the inertial navigation system is constantly increased when global positioning system goes wrong due to interference. It makes impossible to ensure mission and flight safety. If the data-link system provide the position of the UAV for inertial navigation system periodically, then the UAV may operate normally under malfunction of the global positioning system. In this paper, we introduce an algorithm for estimating the position of the UAV using the monopulse tracking and distance measurement of the line-of-sight data-link system. Also, we propose a method to improve the performance of position estimation. And we assured ourselves that this method can be applied in the UAVs.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.31 no.5
• /
• pp.117-123
• /
• 2003

One of the most important elements in satellite attitude control is sensor technology. Generally, inertial sensors introduce drift and noise which cause continuous errors. Absolute reference is needed to eliminate the problem of the inertial sensors. Star trackers are used primarily for such a purpose. There has been relatively less research effort or ground feasibility test experience on star trackers in the domestic side despite the importance of the associated technologies. In this paper, we re-introduce the basic concept of a star tracker and present the S/W simulator for the star tracker. The star simulator may be used ground test of a star tracker for the basic functioning test or the whole spacecraft test with the star tracker assembled.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.10
• /
• pp.64-76
• /
• 1998

In this paper, we propose the dynamic modeling, path planning and tracking algorithms of 4-wheeled 2-d.o.f.(degree of freedom) mobile robot(WMR). The gaussian functions are applied to design the smooth path of WMR. To calculate the WMR position in real time, we use three components of inertial measurement units(IMU). These units have initial error because of the rotation rate of earth, gravity acceleration and so on. Therefore we derive the initial error model of IMU, and compare the fitness diagnosis about probability characteristics of real data adn estimated data. The performance of IMU with error model and Kalman filter is compared to that without filter and error model. The simulation results show that the proposed dynamic model, path planning and tracking algorithms are more useful than the conventional control algorithm.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.2
• /
• pp.291-298
• /
• 2020

Sign language was designed for the deaf and dumb people to allow them to communicate with others and connect to the society. However, sign language is uncommon to the rest of the society. The unresolved communication barrier had eventually isolated deaf and dumb people from the society. Hence, this study focused on design and implementation of a wearable sign language interpreter. 6 inertial measurement unit (IMU) were placed on back of hand palm and each fingertips to capture hand and finger movements and orientations. Total of 28 proposed word-based American Sign Language were collected during the experiment, while 156 features were extracted from the collected data for classification. With the used of the long short-term memory (LSTM) algorithm, this system achieved up to 99.89% of accuracy. The high accuracy system performance indicated that this proposed system has a great potential to serve the deaf and dumb communities and resolve the communication gap.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.5
• /
• pp.1317-1340
• /
• 2024

With the rapid development of information technology, people's demands on precise indoor positioning are increasing. Wireless sensor network, as the most commonly used indoor positioning sensor, performs a vital part for precise indoor positioning. However, in indoor positioning, obstacles and other uncontrollable factors make the localization precision not very accurate. Ultra-wide band (UWB) can achieve high precision centimeter-level positioning capability. Inertial navigation system (INS), which is a totally independent system of guidance, has high positioning accuracy. The combination of UWB and INS can not only decrease the impact of non-line-of-sight (NLOS) on localization, but also solve the accumulated error problem of inertial navigation system. In the paper, a fused UWB and INS positioning method is presented. The UWB data is firstly clustered using the Fuzzy C-means (FCM). And the Z hypothesis testing is proposed to determine whether there is a NLOS distance on a link where a beacon node is located. If there is, then the beacon node is removed, and conversely used to localize the mobile node using Least Squares localization. When the number of remaining beacon nodes is less than three, a robust extended Kalman filter with M-estimation would be utilized for localizing mobile nodes. The UWB is merged with the INS data by using the extended Kalman filter to acquire the final location estimate. Simulation and experimental results indicate that the proposed method has superior localization precision in comparison with the current algorithms.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.8
• /
• pp.682-687
• /
• 2013

Navigation is a crucial capability for all types of manned or unmanned vehicles. However, vehicle navigation in underwater environments still remains a challenging problem since GPS signals for position fixes are not available in the water. Terrain-referenced underwater navigation is an alternative navigation technique that utilizes geometric information of the subsea terrain to correct drift errors due to dead-reckoning or inertial navigation. Terrain-referenced navigation requires the description of an undulating terrain surface as a mathematical function or table, which often leads to a highly nonlinear estimation problem. Recently, PFs (Particle Filters), which do not require any restrictive assumptions about the system dynamics and uncertainty distributions, have been widely used for nonlinear filtering applications. However, PF has considerable computational requirements which used to limit its applicability to problems of relatively low state dimensions. This study proposes the use of a Rao-Blackwellized particle filter that is computationally more efficient than the standard PF for terrain-referenced underwater navigation involving a moderate number of states, and its performance is compared with that of the extended Kalman filter algorithm. The validity and feasibility of the proposed algorithm is demonstrated through numerical simulations.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.6
• /
• pp.267-275
• /
• 2013

EKF has been widely used for GPS/INS integration as standard method but EKF has one well-known drawback. if the errors are not within the bounded region, the filter may be divergent. The particle filter has the advantage of the nonlinear and non-gaussian system. This paper proposes a method for compensating the GPS position errors based on the particle filter and presents loosely-coupled GPS/INS integration using proposed algorithm. We used GPS position pattern with particle filter and added attitude kalman filter for improving attitude accuracy. To verify the performance, the proposed method is compared with high cost GPS as reference. In the experimental result, we verified that the accuracy and robust were well improved by the proposed method filter effectively and robustness than by original loosely-coupled integration when vehicle turns at corner.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.7
• /
• pp.633-643
• /
• 2005

An unmanned aerial vehicle (UAV) is an aircraft controlled by .emote commands from ground station and/o. pre-programmed onboard autopilot system. A navigation system in the UAV provides a navigation data for a flight control computer(FCC). The FCC requires accurate and reliable position, velocity and attitude information for guidance and control. This paper proposes an ADGPS/INS integrated navigation system for a UAV. The proposed navigation system comprises an attitude determination GPS (ADGPS) receive., a navigation computer unit, and a low-cost commercial MEMS inertial measurement unit(IMU). The navigation algorithm contains a fault detection and isolation (FDI) function fur integrity. In order to evaluate the performance of the proposed navigation system, two flight tests were preformed using a small aircraft. The first flight test was carried out to confirm fundamental operation of the proposed navigation system and to check the effectiveness of the FDI algorithm. In the second flight test, the navigation performance and the benefit of the GPS attitude information were checked in a high dynamic environment. The flight test results show that the proposed ADGPS/INS integrated navigation system gives a reliable performance even when anomalous GPS data is provided and better navigation performance than a conventional GPS/INS integration unit.

• Proceedings of the KSME Conference
• /
• 2000.04b
• /
• pp.535-540
• /
• 2000

The objective of the present study is to visualize the pulsatile flow fields by using three-dimensional computer simulation and the PIV system. A closed flow loop system was built for the steady and unsteady experiments. The Harvard pulsatile pump was used to generate the pulsatile pressure and velocity waveforms. Conifer powder as the tracing particles was added to water to visualize the flow field. Two consecutive particle images were captured by a CCD camera for the image processing. The cross-correlation method in combination with the moving searching area algorithm was applied for the image processing of the flow visualization. The pulsatile flow fields were visualized effectively by the PIV system in conjunction with the applied algorithm. The range validation and the area interpolation methods were used to obtain the final velocity vectors with high accuracy. The finite volume predictions were used to analyze three-dimensional flow patterns in the bifurcation model. The results of the PIV experiment and the computer simulation are in good agreement and the results show the recirculation zones and formation of the paired secondary flow distal to the apex of the bifurcated model. The results also show that the branch flow is pushed strongly to the inner wall due to the inertial force effect and helical motions are generated as the flow proceeds toward the outer wall.