• Journal of Information Processing Systems
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• 제6권2호
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• pp.147-162
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• 2010

In this paper, we present a fine-grained localization algorithm for wireless sensor networks using a mobile beacon node. The algorithm is based on distance measurement using RSSI. The beacon node is equipped with a GPS sender and RF (radio frequency) transmitter. Each stationary sensor node is equipped with a RF. The beacon node periodically broadcasts its location information, and stationary sensor nodes perceive their positions as beacon points. A sensor node's location is computed by measuring the distance to the beacon point using RSSI. Our proposed localization scheme is evaluated using OPNET 8.1 and compared with Ssu's and Yu's localization schemes. The results show that our localization scheme outperforms the other two schemes in terms of energy efficiency (overhead) and accuracy.

• 한국통신학회논문지
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• 제37권5B호
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• pp.370-376
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• 2012

CSS(Chirp Spread Spectrum)는 WPAN(Wireless Personal Area Network) 환경에서 SDS-TWR(Symmetric Double Sided - Two Way Ranging) 기반의 위치인식 시스템을 구현하는 기술로 사용된다. 그러나 CSS의 SDS-TWR은 전파 및 장애물과 같은 환경에 따른 간섭으로 인해 레인징 오차가 발생한다. 따라서 위치인식 시스템 개발을 위해서는 이를 보정하기 위한 보정 알고리즘이 요구된다. 본 논문은 위치인식 정확도 성능 향상을 위하여 AEDR(Algorithm of Equivalent Distance Rate) 알고리즘과 칼만필터가 적용된 KF_EDR(Kalman Filter and Equivalent Distance Rate) 보정 알고리즘을 제안하고, 그 성능을 분석 및 평가하였다. 실험 결과, KF_EDR은 AEDR 알고리즘에 비해 위치인식 정확도를 복도 그리고 운동장에서 각각 10.5%, 4.2% 더 개선시켰다. 이 결과는 위치인식 데이터의 신뢰성을 향상시킴 으로써 실제 위치인식 시스템 구현에 상당한 도움을 줄 수 있을 것으로 판단된다.

• 한국통신학회논문지
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• 제38C권5호
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• pp.434-439
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• 2013

최근 많은 감시카메라 (CCTV)들이 사건/사고의 해결되고 있지만 기존의 감시카메라 시스템은 영상이 촬영되지 않는 지역인 사각지대에 대한 감시가 불가능하고 이러한 사각지대로 인해 감시의 효율이 낮아진다. 본 논문에서는 지하주차장에서 감시카메라 사각지대 문제 해결을 위하여 지하주차장에서 음의 세기를 이용한 퍼지로직 기반 음원 위치추정 시스템을 제안하고, 실험을 통해 성능을 분석하였다. 성능분석 결과, 퍼지로직 기반 음원 위치추정 알고리즘 (SLA_fuzzy)는 사각지대 감시카메라용 위치추정 알고리즘 (SLA) 보다 평균 4배 정도 안정적이며, 위치추정정확도가 약 29%정도 향상되었음을 확인하였다.

• 제어로봇시스템학회논문지
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• 제20권1호
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• pp.101-105
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• 2014

For a localization system, the TDOA (Time Difference of Arrival) measurement and AOA (Angle of Arrival) measurement are often used for estimating target's positions. Although it is known that the accuracy of TDOA based localization is superior to that of AOA based one, it may have a poor vertical accuracy in bad geometrical conditions. This paper, therefore, proposes a localization algorithm in which the vertical position is estimated by AOA measurements and the horizontal one is estimated by TDOA measurement in order to achieve high 3D-location accuracy. And this algorithm is applied to a GPS jammer localization systems because it has a large value of the DOP (Dilution of Precision) when the jammer is located far away from the system. Simulation results demonstrate that the proposed hybrid TDOA/AOA location algorithm gives much higher location accuracy than TDOA or AOA only location.

• 한국산학기술학회논문지
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• 제11권4호
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• pp.1248-1253
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• 2010

본 논문은 SDS-TWR(Symmetric Double-Sided Two-Way Ranging)의 Ranging 오차를 보정하기 위하여 균등거리비율 개념을 적용한 위치인식 보정 알고리즘인 AEDR(Algorithm for localization using the concept of Equivalent Distance Rate)을 제안하고, 위치인식 실험을 통해 위치인식 측정 성능을 분석하였다. SDS-TWR의 Ranging 오차는 실험에 의하면 비콘노드와 이동노드의 특정 거리구간에서 평균 1m~8m로 측정되었다. 그러나 제안한 AEDR에 의한 위치인식 성능은 실험을 통해 전체적으로 교내 강당과 복도 모두에서 SDS-TWR 보다 4배 정도 우수하였으며, 측정된 3~10m 이상의 위치인식 오차를 평균 2m 내외로, 3m 이내의 위치인식 오차를 평균 1m 내외로 각각 감소시킬 수 있음을 확인하였다. 특히 AEDR은 LOS(Line Of Sight) 보다 NLOS(Non Line Of Sight)에서 훨씬 더 위치인식 보정 성능이 우수함을 나타내며, 대부분의 센서 네트워크의 환경이 NLOS임을 고려할 때 AEDR이 실제환경에서의 위치인식에 큰 도움을 줄 수 있다고 판단된다.

• 로봇학회논문지
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• 제2권1호
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• pp.40-47
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• 2007

Recently, with the development of service robots and with the new concept of ubiquitous world, the position estimation of mobile objects has been raised to an important problem. As pre-liminary research results, some of the localization schemes are introduced, which provide the absolute location of the moving objects subjected to large errors. To implement a precise and convenient localization system, a new absolute position estimation method for a mobile robot in indoor environment is proposed in this paper. Design and implementation of the localization system comes from the usage of active beacon systems (based upon RFID technology). The active beacon system is composed of an RFID receiver and an ultra-sonic transmitter: 1. The RFID receiver gets the synchronization signal from the mobile robot and 2. The ultra-sonic transmitter sends out the traveling signal to be used for measuring the distance. Position of a mobile robot in a three dimensional space can be calculated basically from the distance information from three beacons and the absolute position information of the beacons themselves. Since it is not easy to install the beacons at a specific position precisely, there exists a large localization error and the installation time takes long. To overcome these problems, and provide a precise and convenient localization system, a new auto calibration algorithm is developed in this paper. Also the extended Kalman filter has been adopted for improving the localization accuracy during the mobile robot navigation. The localization accuracy improvement through the proposed auto calibration algorithm and the extended Kalman filter has been demonstrated by the real experiments.

• 대한음성학회지:말소리
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• 제67호
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• pp.135-147
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• 2008

In this paper, we propose a method for source localization in reverberant environments based on an adaptive eigenvalue decomposition (AED) algorithm which directly estimates channel impulse responses from a speaker to microphones. Unfortunately, the AED algorithm may suffer from whitening effects on channels estimated from temporally correlated natural sounds. The proposed method which applies sparse priors to the estimated channels can avoid the temporal whitening and improve the performance of source localization in reverberant environments. Experimental results show the effectiveness of the proposed method.

• 전기학회논문지
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• 제63권2호
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• pp.277-283
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• 2014

This paper proposes robot localization using Fuzzy-Extended Kalman Filter algorithm of the mobile robots equipped with least sensors. In order to improve the accuracy of the localization, we usually add the sensors or equipment. However, it increases the simulation time and expenses. This paper solves this problem using only the odometer and ultrasonic sensors to get the localization with the Fuzzy-Extended Kalman Filter algorithm method. By inputting the robot's angular velocity, sensor data variation, and residual errors into the fuzzy algorithm, we get the sensor weight factor to decide the sensor's importance. The performance of the designed method shows by the simulation and Pioneer 3-DX mobile robot test in the indoor environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2301-2306
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• 2005

Even if there are lots of researches on localization using 2D range finder in static environment, very few researches have been reported for robust real-time localization of mobile robot in uncertain and dynamic environment. In this paper, we present a new localization method based on ICP(Iterative Closest Point) algorithm for navigation of mobile robot under dynamic or uncertain environment. The ICP method is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. We use the method to align global map with 2D scanned data from range finder. The proposed algorithm accelerates the processing time by uniformly sampling the line fitted data from world map of mobile robot. A data filtering method is also used for threshold of occluded data from the range finder sensor. The effectiveness of the proposed method has been demonstrated through computer simulation and experiment in an office environment.

• Current Optics and Photonics
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• 제5권6호
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• pp.672-679
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• 2021

We propose a high-speed layer-based algorithm for synthesizing computer-generated holograms (CGHs), featuring sparsity-based image segmentation and computational parallelism. The sparsity-based image segmentation of layer-based three-dimensional scenes leads to considerable improvement in the efficiency of CGH computation. The efficiency enhancement of the proposed algorithm is ascribed to the field localization of the fast Fourier transform (FFT), and the consequent reduction of FFT computational complexity.