• ETRI Journal
• /
• 제37권4호
• /
• pp.707-716
• /
• 2015

The purpose of a localization system is to estimate the coordinates of the geographic location of a mobile device. The accuracy of wireless localization is influenced by nonline-of-sight (NLOS) errors in wireless sensor networks. In this paper, we present an improved time of arrival (TOA)-based localization method for wireless sensor networks. TOA-based localization estimates the geographic location of a mobile device using the distances between a mobile station (MS) and three or more base stations (BSs). However, each of the NLOS errors along a distance measured from an MS (device) to a BS (device) is different because of dissimilar obstacles in the direct signal path between the two devices. To accurately estimate the geographic location of a mobile device in TOA-based localization, we propose an optimized localization method with a BS selection scheme that selects three measured distances that contain a relatively small number of NLOS errors, in this paper. Performance evaluations are presented, and the experimental results are validated through comparisons of various localization methods with the proposed method.

• 한국멀티미디어학회논문지
• /
• 제19권2호
• /
• pp.240-251
• /
• 2016

This paper presents a real-time indoor location and pose estimation method that utilizes simple artificial markers and image analysis techniques for the purpose of warehouse automation. The conventional indoor localization methods cannot work robustly in warehouses where severe environmental changes usually occur due to the movement of stocked goods. To overcome this problem, the proposed framework places artificial markers having different interior pattern on the predefined position of the warehouse floor. The proposed algorithm obtains marker candidate regions from a captured image by a simple binarization and labeling procedure. Then it extracts maker interior pattern information from each candidate region in order to decide whether the candidate region is a true marker or not. The extracted interior pattern information and the outer boundary of the marker are used to estimate location and heading angle of the localization system. Experimental results show that the proposed localization method can provide high performance which is almost equivalent to that of the conventional method using an expensive LIDAR sensor and AMCL algorithm.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2007년도 추계종합학술대회
• /
• pp.457-461
• /
• 2007

In many applications, received signal strength indicator is used for location tracking and sensor nodes localization. For location finding, the distances between sensor nodes can be estimated by converting received signal's power into distance using path loss prediction model. Many researches have done the analysis of power-distance relationship for radio channel characterization. In indoor environment, the general conclusion is the non-linear variation of RSSI values as distance varied linearly. This has been one of the difficulties for indoor localization. This paper presents works on indoor RSSI characterization based on statistical methods to find the overall trend of RSSI variation at different places and times within the same room From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. This two factors are directly indicated by the two main parameters of path loss prediction model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. Using this relationship, the characterization for location estimation can be more efficient and accurate.

• Journal of Electrical Engineering and information Science
• /
• 제1권2호
• /
• pp.45-51
• /
• 1996

This paper presents a neural network approach for on-line estimation of partial discharge(PD) location using advanced correlation technique in power transformer. Ultrasonic sensors detect ultrasonic signals generated by a PD and the proposed method calculates time difference between the ultrasonic signals at each sensor pair using the cross-correlation technique applied by moving average and the Hamming window. The neural network takes distance difference as inputs converted from time difference, and estimates the PD location. Case studies showed that the proposed method using advanced correlation technique and a neural network estimated the PD location better than conventional methods.

• 제어로봇시스템학회논문지
• /
• 제19권2호
• /
• pp.125-130
• /
• 2013

Compared to OWR (One-Way Ranging) method that requires precise network time synchronization, TWR (Two-Way Ranging) method has advantages in building an indoor WPAN (Wireless Personal Area Network) location system with lower cost. However, clock offsets of nodes in WPAN system should be eliminated or compensated to improve location accuracy of the TWR method. Because conventional clock offset elimination methods requires multiple TWR transactions to reduce clock offset, they produce network traffic burden instead. This paper presents a clock offset estimation method that can reduce clock offset error with a single TWR transaction. After relative clock offsets of sensor nodes are estimated, clock offsets of mobile tags are estimated using a single TWR communication. Simulation results show that location accuracy of the proposed method is almost similar to the conventional clock offset elimination method, while its network traffic is about a half of the conventional method.

• 한국조명전기설비학회:학술대회논문집
• /
• 한국조명전기설비학회 2006년도 춘계학술대회 논문집
• /
• pp.370-375
• /
• 2006

This paper suggests the method for estimating a partial discharge (PD) location using divide of the inside transformer as a grid. The PD location is found swiftly and economically compared with the typical method detecting a PD. The reason is that the location of PD is detected in the section. The estimation of PD location is trained using the Neural Network. JavaNNS(Java Neural Network Simulator) and SNNS(Stuttgart Neural Network Simulator) are used for searching the location of PD. The simulation procedure is following, The transformer is assumed that the case is a regular hexahedron. The sensor is installed in a proper location. A section of PD location is set as a target, and training set is studied with several PD locations in the inside of the transformer. As a result of training process, the learning capability of neural network is excellent. The PD location is detected by division of internal structure of transformer and application of neural network.

• 한국산업융합학회 논문집
• /
• 제10권2호
• /
• pp.105-113
• /
• 2007

Accurate and low-cost sensor localization is a critical requirement for the deployment of wireless sensor networks in a wide variety of application. Sensor position is used for its data to be meaningful and for energy efficient data routing algorithm especially geographic routing. The previous works for sensor localization utilize global positioning system(GPS) or estimate unknown-location nodes position with help of some small reference nodes which know their position previously. However, the traditional localization techniques are not well suited in the senor network for the cost of sensors is too high. In this paper, we propose the sensor localization method with a mobile robot, which knows its position, moves through the sensing field along pre-scheduled path and gives position information to the unknown-location nodes through wireless channel to estimate their position. We suggest using the sensor position estimation method and an efficient mobility path model. To validate our method, we carried out a computer simulation, and observed that our technique achieved sensor localization more accurately and efficiently than the conventional one.

• 제어로봇시스템학회논문지
• /
• 제16권12호
• /
• pp.1159-1166
• /
• 2010

Today, detecting the location of moving object has been traced as various methods in our world. In this paper, we preset the system to improve the estimation accuracy utilizing detail localization using radar sensor based on WSN and situational awareness for a calibration (context aware) database, Rail concept. A variety of existing location tracking method has a problem with receiving of data and accuracy as tracking methodology, and since these located data are the only data to be collected for location tracing, the context aware or monitering as the surrounding environment is limited. So, in this paper, we enhanced the distance aware accuracy using radar sensor utilizing the Doppler effect among the distance measuring method, estimated the location using the Triangulation algorithm. Also, since we composed the environment data(temperature, illuminancem, humidity, noise) to entry of the database, it can be utilized in location-based service according to the later action information inference and positive context decision. In order to verify the validity of the suggested method, we give a few random situation and built test bed of designed node, and over the various test we proved the utilizing the context information through route tracking of moving and data processing.

• 한국통신학회논문지
• /
• 제34권12B호
• /
• pp.1491-1497
• /
• 2009

센서노드의 위치 측정 방법은 신호 도착시간차(Time of arrival, ToA), 수신신호세기(Received Signal Strength, RSS), 신호각도(Angle of Arrival, AoA) 방법을 비롯하여 다양한 방법들이 연구/발표되고 있다. 본 논문에서는 센서노드의 위치 정확도 향상을 위해 일반 센서노드에서 획득할 수 있는 신호도착 시간과 신호세기를 이용한 ToA와 RSS를 상호 보정하는 방법을 제안한다. 실내/외 실험결과 제안 알고리즘은 노드간 실제 거리와의 오차를 기존의 ToA 보다 30%이상의 성능 향상을 기대할 수 있었다. 본 논문에서 제안한 센서노드의 위치측정 방법은 센서노드간 거리 측정의 정확도를 향상시킬 수 있고, 이를 이용하여 센서네트워크 환경에서 향상된 노드의 위치 식별에 기여할 것으로 판단한다.

• 정보처리학회논문지C
• /
• 제17C권2호
• /
• pp.165-172
• /
• 2010

다양한 분야에서 응용될 수 있는 센서 네트워크 통신에 안전성을 제공하기 위해서는 센서 노드 간 pairwise 키설정이 기본이 되어야한다. 본 논문에서는 네트워크 필드를 육각형의 클러스터로 나누고 각 센서 노드마다 예상되는 위치에 따라 세 개의 서로 다른 키 정보를 사전에 나누어 주어 노드 배치 후 갖고 있는 정보를 이용하여 모든 이웃 노드와의 pairwise 키를 설정할 수 있도록 한다. 특히 키스트링 기법을 적용하여 이를 클러스터링 정보와 연계되도록 함으로써 적은 양의 정보를 가지고도 이웃한 모든 노드들 간에 pairwise 키를 설정할 수 있도록 하였다. 제안된 키설정 메커니즘을 통하여 필요한 메모리의 양을 줄이면서도 보안 강도를 높일 수 있음을 증명한다.