• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.6
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• pp.729-737
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• 2012

In case that multiple jammers are transmitting the signals which are the same type a general algorithm based on TDOA method cannot estimate the positions of multiple jammers because there are many TDOA measurements including true and false values. This paper, therefore, designs a new algorithm based on TDOA method to localize multiple jammers. In this algorithm, TDOA measurements are obtained by rotating the reference sensor, and then the positions of multiple jammers can be estimated by detecting congregated point among the multiple estimated positions from TDOA measurements. Through computer simulations, it is verified that this algorithm localizes the multiple jammers well. The performance of the algorithm are also analysed by changing the distance between sensors and jammer, and sampling frequency.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.300-306
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• 2023

A hull-cleaning robot sticks to the surface of a vessel and moves for efficient cleaning. Precise path planning and tracking using the current position is crucial. Many robots rely on the INS algorithm, but errors accumulate. To fix this, GPS, sonar, and USBL are used, though with limitations. Selecting suitable sensors for the surface operation and accurate positioning algorithm are vital. In this study, we developed a robot position estimation algorithm using the structure of a ship. Problems that arise when expanding the 2D position estimation algorithm used in existing wall structures to 3D were evaluated and methods for solving them were proposed. In addition, we aimed to improve performance by deriving singularities that exist in the robot path and proposing an error correction algorithm based on the singularities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2263-2268
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• 2010

In this paper, the hybrid compensation algorithm($A_{HB}$) for localization using the Compensation Algorithm distance($CA_d$) and the Algorithm of Equivalent Distance Rate(AEDR) in SDS-TWR(Symmetric Double-Sided Two-Way Ranging) is suggested and the performance of the proposed algorithm is analyzed by practical experimentations. From experimentations, it is confirmed that the errors are reduced in 28 coordinates of total 32 coordinates in the experimental region and the errors are reduced about above 70% in the assigned 3 type error level ranges by $A_{HB}$. Also, it is analyzed that the average localization error is reduced from 2.67m to 1.19m as 55.4% in total 32 coordinates by $A_{HB}$ and the error compensation capability of $A_{HB}$ is very excellent as above 90%. From above results, we have seen that the error reduction ratio and error compensation capability of $A_{HB}$ is more excellent than each $CA_d$ or AEDR.

• Journal of IKEEE
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• v.17 no.4
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• pp.440-445
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• 2013

This paper proposes a local estimation system which combines Cell Divide Algorithm with low-cost GPS/INS fused by Extended Kalman Filter(EKF) for localization of Quad-rotor when it returns to the departure point. In the research, the low-cost GPS and INS are fused by EKF to reduce the local error of low-cost GPS and the accumulative error of INS due to continuous integration of sensor error values. When the Quad-rotor returns to the departure point in the fastest path, a moving path can be known because it moves straight, where Cell Divide Algorithm is used to divide moving route into the cells. Then it determines the closest position of data of GPS/INS system fused by EKF to obtain the improved local data. The proposed system was verified through comparing experimental localization results obtained by using GPS, GPS/INS and GPS/INS with Cell Divide Algorithm respectively.

• The Journal of the Acoustical Society of Korea
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• v.20 no.1
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• pp.36-42
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• 2001

This paper propose new sound localization algorithm that detects the sound source bearing in a closed office environment using two microphone array. The proposed Subband CPSP (Cross Power Spectrum Phase) algorithm is a development of previously Down CPSP method using subband approach. It first split the received microphone signals into subbands and then calculates subband CPSP which result in possible source bearings. This type of algorithm, Subband CPSP, can provide more robust and reliable sound localization system because it limits the effects of environmental noise within each subband. To verify the performance of the proposed Subband CPSP algorithm, a real time simulation was conducted and it was compared with previous CPSP method. From the simulation results, the proposed Subband CPSP is superior to previous CPSP algorithm more than 5％ average accuracy for sound source detection.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.306-311
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• 2003

This paper presents a novel localization paradigm for mobile robots based on artificial and natural landmarks. A model-based object recognition method detects natural landmarks and conducts the global and topological localization. In addition, a metric localization method using artificial landmarks is fused to complement the deficiency of topology map and guide to action behavior. The recognition algorithm uses a modified local Zernike moments and a probabilistic voting method for the robust detection of objects in cluttered indoor environments. An artificial landmark is designed to have a three-dimensional multi-colored structure and the projection distortion of the structure encodes the distance and viewing direction of the robot. We demonstrate the feasibility of the proposed system through real world experiments using a mobile robot, KASIRI-III.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.433-438
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• 2007

This paper presents a distance mapping-based localization method with incomplete data which means partially observed data. We make three contributions. First, we propose the use of Multi Dimensional Scaling (MDS) for multi-robot localization. Second, we formulate the problem to accomodate partial observations common in multi-robot settings. We solve the resulting optimization problem using #Scaling by Majorizing a Complicated function (SMACOF)#, a popular algorithm fur iterative MDS. Third, we not only verify the performance of MDS-based multi-robot localization by computer simulations, but also implement a real world localization of multi-robot team. Using extensive empirical results, we show that the accuracy of the proposed method is almost similar to that of Monte Carlo Localization(MCL).

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.420-427
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• 2010

This paper describes a localization method based on Monte Carlo Localization approach for a mobile robot. The method uses range data which are measured from ultrasound transmitting beacons whose locations are given a priori. The ultrasound receiver on-board a robot detects the range from the beacons. The method requires several beacons, theoretically over three. The method proposes a sensor model for the range sensing based on statistical analysis of the sensor output. The experiment uses commercialized beacons and detector which are used for trilateration localization. The performance of the proposed method is verified through real implementation. Especially, it is shown that the performance of the localization degrades as the sensor update rate decreases compared with the MCL algorithm update rate. Though the method requires exact location of the beacons, it doesn't require geometrical map information of the environment. Also, it is applicable to estimation of the location of both the beacons and robot simultaneously.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.2 s.21
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• pp.49-57
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• 2005

The target localization using the line arrays buried in the seabed is a difficult problem due to the complex sea bottom characteristics and need to compensate the wave propagation effect to localize the target accurately Sound speed mismatch in the seabed causes a bias in the target bearing estimation and induces the localization error. In this paper we describe a target localization method with improved accuracy of target bearing and localization by calibration the sound speed in the seabed. The proposed algorithm is verified through the ocean data.

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.156-162
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• 2016

For the underwater localization, acoustic sensor systems are widely used due to greater penetration properties of acoustic signals in underwater environments. On the other hand, the good penetration property causes multipath and interference effects in structured environment too. To overcome this demerit, a localization method using the attenuation of electro-magnetic(EM) waves was proposed in several literatures, in which distance estimation and 2D-localization experiments show remarkable results. However, in 3D-localization application, the estimation difficulties increase due to the nonuniform (doughnut like) radiation pattern of an omni-directional antenna related to the depth direction. For solving this problem, we added a depth sensor for improving underwater 3D-localization with the EM wave method. A micro scale pressure sensor is located in the mobile node antenna, and the depth data from the pressure sensor is calibrated by the curve fitting algorithm. We adapted the depth(z) data to 3D EM wave pattern model for the error reduction of the localization. Finally, some experiments were executed for 3D localization with the fast calculation and less errors.