• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.4B
• /
• pp.300-308
• /
• 2012

Many indoor location tracking technologies have been proposed. Generally indoor location tracking using TOA signal is used, there is a weak point that it's difficult to track the location due to obstacles like a refraction, reflection and dispersion of radio wave. In this paper, we apply ETOA(Estimated-TOA) algorithm in NLOS(Non-Line-Of-Sight) environment to solve above problem. In NLOS environment, TOA value between Beacon and Mobile node is predicted by ETOA algorithm and the tracking of indoor location is also possible to identify using two NLOS beacons of three beacons by this algorithm. We show that the proposed algorithm is accurate location tracking is accomplished using the applying the proposed algorithm to indoor moving robot and the inertia sensor of robot and Kalman filter algorithm.

• The KIPS Transactions:PartA
• /
• v.10A no.4
• /
• pp.381-388
• /
• 2003

Location tracking is used to keep track of the location information of a mobile terminal in an idle state for a cail setup between mobile terminals. In this paper, we introduce a location update algorithm based on the call arrival history, which is appropriate for a variable call arrival rate over time. The location tracking strategy which uses the proposed algorithm can find changes in the call arrival rate by maintaining a call arrival history of a mobile terminal, from which a mobile terminal can calculate an appropriate timeout interval for a variable call arrival rate. We show that the proposed scheme is appropriate for a variable call arrival rate by presenting a simple analytical model and analytical results to investigate its performance for both a fixed and a variable call arrival rate.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.10
• /
• pp.5112-5128
• /
• 2016

Tracking human body is an important problem in computer vision field. Tracking failures caused by occlusion can lead to wrong rectification of the target position. In this paper, a robust human tracking algorithm is proposed to address the problem of occlusion, rotation and improve the tracking accuracy. It is based on Tracking-Learning-Detection framework. The key auxiliary information is used in the framework which motivated by the fact that a tracking target is usually embedded in the context that provides useful information. First, face localization method is utilized to find key face location information. Second, the relative position relationship is established between the auxiliary information and the target location. With the relevant model, the key face information will get the current target position when a target has disappeared. Thus, the target can be stably tracked even when it is partially or fully occluded. Experiments are conducted in various challenging videos. In conjunction with online update, the results demonstrate that the proposed method outperforms the traditional TLD algorithm, and it has a relatively better tracking performance than other state-of-the-art methods.

• Journal of IKEEE
• /
• v.15 no.1
• /
• pp.76-85
• /
• 2011

In this paper, we analysed RSS characteristics by external factors and presented an efficient algorithm for real-time location tracking and its hardware system. The proposed algorithm enhanced the ranging accuracy using Kalman Filter based on the RSS DB. The location tracking system that consists of the tag, AP(Access Point), a data collector(Data Receiver) with IEEE 802.15.4(ZigBee) network environment, and location tracking application that reveal locations of each tag is implemented for the test environment. The location tracking system presented in this paper is implemented with MSP430 microprocessor manufactured by TI(Texas Instrument), CC2420 RF chipset and the location tracking application. With the results of the experiment, the proposed algorithm and the system can achieve the efficiency and the accuracy of location tracking with the average error of 19.12cm, and its standard deviation of 5.31cm in outdoor circumstance. Also, the experimental result shows that exact tracking of position in indoor circumstance cannot achieve because of vulnerable RSS with external circumstance.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.1
• /
• pp.1-8
• /
• 2016

In this study, an WiFi fingerprinting method based on the k-nn algorithm was applied to improve the accuracy of location tracking of a moving train on a platform and evaluate the performance to minimize the estimation error of location tracking. The data related to the position of the moving train are monitored by the control center for trains and used widely for the safety and comfort of passengers. The train location tracking methods based on WiFi installed by telecom companies were evaluated. In this study, a simulator was developed to consider the environments of two cases; in already installed WiFi devices and new installed WiFi devices. The developed simulator can simulate the localized estimation of the position under a variety of conditions, such as the number of WiFi devices, the area of platform and entry velocity of train. To apply location tracking algorithms, a k-nn algorithm and fuzzy k-nn algorithm were applied selectively according to the underlying condition and also four distance measurement algorithms were applied to compare the error of location tracking. In conclusion, the best method to estimate train location tracking is a combination of the k-nn algorithm and Minkoski distance measurement at a 0.5m grid unit and 8 WiFi AP installed.

• Journal of KIISE:Computing Practices and Letters
• /
• v.14 no.3
• /
• pp.266-270
• /
• 2008

Bluetooth technology provides a way to connect and exchange information between personal devices over a secure and short-range radio frequency without any authentication infrastructures. For this infrastructure-less feature, Bluetooth has several problems which could not occur in other network, and among them location tracking attacks is essential problem which should be solved. In this paper, we introduce the location tracking attack and propose an anonymous connection protocol against it. We also perform security analysis based on possible scenarios of this attack, and estimate both execution time and memory spaces of our scheme and existing methods.

• Journal of Korea Game Society
• /
• v.20 no.6
• /
• pp.43-52
• /
• 2020

This paper presents a fast pattern tracking method using location prediction in cubemap video for 360-degree VR. A spherical cubemap frame has six face textures and searching a pattern is much slower than a flat image. To overcome the limitation, we propose a method of predicting the location of target pattern using Kalman filter and reducing the search area by considering only textures of predicted location. The experimental results showed that the proposed system is much faster than the previous method of searching all six faces and also gives accurate pattern tracking performance.

• Journal of Internet Computing and Services
• /
• v.17 no.6
• /
• pp.1-8
• /
• 2016

Current indoor intrusion detection and location tracking methods have the weakness in seamless operations in tracking the objective because the object must possess a communicating device and the limitation of the single cell size (approximate $100cm{\times}100cm$) exits. Also, the utilization of CCTV technologies show the shortcomings in tracking when the object disappear the area where the CCTV is not installed or illumination is not enough for capturing the scene (e.g. where the context-awarded system is not installed or low illumination presents). Therefore, in this paper we present an improved in-door tracking system based on sensor networks. Such system is built on a simulated scenario and enables us to detect and extend the area of surveillance as well as actively responding the emergency situation. Through simulated studies, we have demonstrated that the proposed system is capable of supplementing the shortcomings of signal cutting, and of estimating the location of the moving object. We expect the study will improve the better analysis of the intruder behavior, the more effective prevention and flexible response to various emergency situations.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2010.07a
• /
• pp.403-405
• /
• 2010

위치 추적 서비스와 같은 LBS 서비스는 신속하게 변화하는 수많은 양의 공간 및 이동 객체를 관리 및 실시간으로 처리해야 하므로 고성능의 DBMS가 필요하다. 본 논문에서는 실시간 처리와 고성능 처리를 향상시키기 위한 메인 메모리 기반의 이동체 DBMS를 사용한 위치 추적 서비스 시스템을 제안하였다.

• International Journal of Contents
• /
• v.5 no.2
• /
• pp.59-63
• /
• 2009

Since it is hard to use GPS for tracking mobile user in indoor environments, much research has focused on techniques using existing wireless local area network infrastructure. Signal strength received at a fixed location is not constant, so fingerprinting approach which use pattern matching is popular. But this approach has to pay additional costs to determine user location. This paper proposes a new approach to find user's location efficiently using an index scheme. After analyzing characteristics of RF signals, the paper suggests the data processing method how the signal strength values for each of the access points are recorded in a radio map. To reduce computational cost during the location determination phase, multidimensional indexes for radio map with the important information which is the order of the strongest access points are used.