• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.2
• /
• pp.68-78
• /
• 2000

This paper suggests a new map-matching algorithm for matching traveling trace of vehicle, which is measured by GPS receiver, to the road of a digital map This eventually brings the Improvement of positioning accuracy of the vehicle with GPS receiver After representing the travelling vehicle's motion by state equations using Singer's model, the proposed map-matching algorithm places the position of a vehicle right on the road and also improves the positioning accuracy of the vehicle using a Kalman filter In the crossroad, since it is difficult to determine precisely a current travelling road, we take linear regression to the estimated values from Kalman filtering This gives the direction angle of turning vehicle, then we can determine the correct route direction after comparing with each route-direction angle at the intersection.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.46 no.8
• /
• pp.631-638
• /
• 2018

In this paper, we propose a method to improve the performance by guidance technique and applying it to the precision guided ammunition. The proposed method is a technique designed to reduce the target error of ammunition by reducing the projectile error without analyzing the motion characteristics of the shot. This technique is applied to the moving average filter technique which is widely used as signal processing technique to reduce the fluctuation of the output of the inboard mounting inertial sensor caused by the rotation and the coning motion of the ammunition. In order to compare the performance of the applied technique including the simple 3D guided control technique and the proposed improvement technique. It is confirmed that the application of this technique improves the accuracy of impact of the cannon - launched ammunition with severe environmental conditions and irregular motion characteristics unlike the missile.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.368-371
• /
• 2006

A coastline is the boundary between land and ocean masses. Knowledge of coastline is essential for autonomous navigation, geographical exploration, coastal erosion monitoring and modelling, water line change, etc. Many methods have been researched to extract coastlines from the synthetic aperture radar (SAR) and optic images. Most methods were based on the intensity contrast between land and sea regions. However, in these methods, a coastline detection task was very difficult because of insufficient intensity contrast and the ambiguity in distinguishing coastline from other object line. In this paper, we propose an efficient method for the delineation of coastline using interferometric coherence values estimated from ERS tandem pair. The proposed method uses the facts that a tandem pair of ERS is acquired from a time interval of an accurate day and that the coherent and incoherent values in coherence map are land and water, respectively. The coherence map was generated from ERS tandem pair, filtered by MAP filter, and divided into land and water by the determination of threshold value that is based on the bimodality of the histogram. Finally, a coastline was detected by delineating the boundary pixels. There was a good visual match between the detected coastline and the manually contoured line. The interferometric coherence map will be helpful to identify land and water regions easily, and can be used to many applications that are related with a coastline.

• Journal of the Korean Society for Library and Information Science
• /
• v.36 no.4
• /
• pp.175-205
• /
• 2002

Information visualization in information retrieval is a creating tool that enables us to observe, manipulate, search, navigate, explore, filter, discover, understand, interact with large volumes of data for more rapidly and far more effectively to discover hidden patterns. The focus of this study is to investigate and analyze information visualization techniques in information retrieval system in the three-schematic levels. In result, it was found that first, scientific data, documents, and retrieval result information are visualized through various techniques. Second, information visualization techniques which facilitate navigation and interaction are zoom and pan, focus+context techniques, incremental exploration, and clustering. Third, the visual metaphors used by the visualization systems are presented in the linear structure, hierarchy structure, network structure, and vector scatter structure.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.31 no.10
• /
• pp.51-59
• /
• 2003

A method of autonomous update is presented for onboard orbit propagator. On board propagator is an alternative means that could be used for navigation purpose in case of CPS receiver's failure. Although the ground station is not a able to upload a new propagator, the onboard propagator must be maintained most up-to-date. For this, a filtering technique is proposed wherein GPS data are effectively used to continuously update the on board propagator which was uploaded previously. Even if the ground station has generated the on board propagator based on the wrong information, the onboard propagator with updating scheme can automatically correct the errors in the coefficients of residual reconstruction function. Several scenarios were used to show the validity of the scheme for updating the onboard propagator using KOMPSAT-1 orbit data.

• Journal of Korean Society for Geospatial Information Science
• /
• v.14 no.3 s.37
• /
• pp.47-53
• /
• 2006

In this contribution, an integration of seamless navigation system for the pedestrian is introduced. To overcome the GPS outages in various situations, multi-sensor of GPS, INS, electronic barometer and compass are considered in one Extented Kalman filter. Especially, the integrated system is designed for low-cost for the practical applications. Therefore, a MEMS IMU is considered, and the low quality of the heading is compensated by the electronic compass. In addition, only the pseudoranges from GPS measurements are considered for possible real-time application so that the degraded height is also controlled by a barometer. The mathematical models for each sensor with systematic errors such as biases, scale factors are described in detail and the results are presented in terms of a covariance analysis as well as the position and attitude errors compared to the high-grade GPS/INS combined solutions. The real application scenario of GPS outage is also investigated to assess the feasible accuracy with respect to the outage period. The description on the current status of the development and future research directions are also stated.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.39 no.4
• /
• pp.429-441
• /
• 2002

This paper concerns extracting 3D motion information from a 3D input device in real time focused to enabling effective human-computer interaction. In particular, we develop a novel algorithm for extracting 6 degrees-of-freedom motion information from a 3D input device by employing an epipolar geometry of stereo camera, color, motion, and structure information, free from requiring the aid of camera calibration object. To extract 3D motion, we first determine the epipolar geometry of stereo camera by computing the perspective projection matrix and perspective distortion matrix. We then incorporate the proposed Motion Adaptive Weighted Unmatched Pixel Count algorithm performing color transformation, unmatched pixel counting, discrete Kalman filtering, and principal component analysis. The extracted 3D motion information can be applied to controlling virtual objects or aiding the navigation device that controls the viewpoint of a user in virtual reality setting. Since the stereo vision-based 3D input device is wireless, it provides users with a means for more natural and efficient interface, thus effectively realizing a feeling of immersion.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.4
• /
• pp.438-444
• /
• 2004

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using the a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Since the equations are based or the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot. The Kalman filter scheme is applied for this method. its performance is verified by the computer simulation and the experiment.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.3
• /
• pp.164-173
• /
• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• The KIPS Transactions:PartB
• /
• v.12B no.3 s.99
• /
• pp.273-282
• /
• 2005

Real-time Object tracking is an important field in developing vision applications such as surveillance systems and vision based navigation. mean-shift algerian and Condensation algorithm are widely used in robust object tracking systems. Since the mean-shift algorithm is easy to implement and is effective in object tracking computation, it is widely used, especially in real-time tracking systems. One of the drawbacks is that it always converges to a local maximum which may not be a global maximum. Therefore, in a cluttered environment, the Mean-shift algorithm does not perform well. On the other hand, since it uses multiple hypotheses, the Condensation algorithm is useful in tracking in a cluttered background. Since it requires a complex object model and many hypotheses, it contains a high computational complexity. Therefore, it is not easy to apply a Condensation algorithm in real-time systems. In this paper, by combining the merits of the Condensation algorithm and the mean-shift algorithm we propose a new model which is suitable for real-time tracking. Although it uses only a few hypotheses, the proposed method use a high-likelihood hypotheses using mean-shift algorithm. As a result, we can obtain a better result than either the result produced by the Condensation algorithm or the result produced by the mean-shift algorithm.