• Journal of Information Processing Systems
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• v.6 no.2
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5B
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• pp.370-376
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• 2012

The CSS(Chirp Spread Spectrum) technology is used for developing various WPAN(Wireless Personal Area Network) application fields in general, and it can be adapted to implement localization systems especially using SDS-TWR(Symmetric Double Sided - Two Way Ranging). But the ranging errors are occurred in many practical applications due to some interferences by some experiments. Thus, the compensation algorithm for localization is required for developing localization applications. The suggested compensation algorithm that is named KF_EDR(Kalman Filter and Equivalent Distance Rate) for localization in order to reduce the ranging errors is suggested in this paper. The KF_EDR compensation algorithm for localization is mainly composed of the AEDR(Algorithm of Equivalent Distance Rate) and the Kalman Filter. It is confirmed that the improved error ratio of the KF_EDR are 10.5% and 4.2% compared with the AEDR algorithm in lobby and stadium. From the results, it is analyzed that the KF_EDR can be widely used for some localization system in ubiquitous society.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.5
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• pp.434-439
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• 2013

It is very difficult to monitor the blind spots that are not recognized by traditional surveillance camera (CCTV) systems, and the surveillance efficiencies are very low though many accidents/events can be solved by the systems. In this paper, the fuzzy logic based sound source localization system using sound strength in the underground parking lot is suggested and the performance of the system is analyzed in order to enhance the stabilization and the accuracy of the localization algorithm in the suggested system. It is confirmed that the localization stabilization of the localization algorithm (SLA_fuzzy) using the fuzzy logic in the suggested system is 4 times higher than that of the conventional localization algorithm (SLA). In addition to this, the localization accuracy of the SLA_fuzzy in the suggested system is 29% higher than that of the SLA.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1248-1253
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• 2010

In this paper, the compensation algorithm for localization using the concept of equivalent distance rate(AEDR) in order to compensate ranging error in the SDS-TWR(Symmetric Double-Sided Two-Way Ranging) is proposed and the performance of the proposed algorithm is analyzed by the localization experiments. The ranging error of the SDS-TWR in the distance between mobile node and beacon node is measured to average 1m~8m by ranging experiments. But it is confirmed that the performance of the localization by the AEDR is better than that of the SDS-TWR 4 times in university auditorium and corridor, and the localization error of above 3~10m is reduced to average 2m and that of below 3m is reduced to average 1m respectively. It is concluded that the AEDR is superior to the NLOS(Non Line Of Sight) than LOS(Line Of Sight) in performance of ranging compensation for localization, and the AEDR is more helpful to localization systems practically considering the environment of sensor networks is under NLOS.

• The Journal of Korea Robotics Society
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• v.2 no.1
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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.

• MALSORI
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• no.67
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.2
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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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• 2005.06a
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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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• v.5 no.6
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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.