• Spatial Information Research
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• v.14 no.4 s.39
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• pp.433-449
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• 2006

Two primary objectives of this study were to determine important personal factors in performing cognitive distance mapping, and to understand how human's cognitive distance mapping capabilities were influenced by reference and subjects' locations using Global Positioning System (GPS). Undergraduate and graduate students at the University of Kansas, USA were interviewed and surveyed throughout the campus area giving them a paper-and-pencil test. Study results showed that females had more accurate cognitive mapping capability than males regardless of ethnic background and academic levels. Generally, subjects with longer affiliation with the university, higher ages and academic levels had less variability in their mapping accuracy. Subjects tended to more accurately map the target locations closer to the reference points than those located farther away, and subjects who were closer to a reference point performed their distance mapping better than those farther away. A correlation analysis reported that male subjects used reference-to-target and subject-to-reference distances more sensitively than females to estimate the locations of the targets. This result indicates that males might have used the reference point-based map scale more strenuously than females.

• The KIPS Transactions:PartC
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• v.16C no.2
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• pp.229-236
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• 2009

UWB signal with high resolution capability can be used to estimate ranging and positioning in wireless personal area networks. The clock frequency differences of nodes have serious affects on asynchronous ranging methods to estimate locations of mobile nodes. The specification of high rate UWB describes successive TWR method with the estimation of a relative clock frequency offset. In this paper, we complete the ranging equations using relative frequency offset and time information, and propose a method to estimate the exact frequency offsets. We evaluate the ranging algorithms with simulation. The results show that the performances of the algorithms using frequency offsets are very close without noise. But, at noise environment, the method of exact frequency offsets shows better performance than that of relative frequency offsets.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.71-76
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• 2023

In this paper, we propose a smoothed received signal strength indicator (RSSI)-based distance estimation using deep neural network (DNN) for accurate distance estimation in an environment where a single receiver is used. The proposed scheme performs a data preprocessing consisting of data splitting, missing value imputation, and smoothing steps to improve distance estimation accuracy, thereby deriving the smoothed RSSI values. The derived smoothed RSSI values are used as input data of the Multi-Input Single-Output (MISO) DNN model, and are finally returned as an estimated distance in the output layer through input layer and hidden layer. To verify the superiority of the proposed scheme, we compared the performance of the proposed scheme with that of the linear regression-based distance estimation scheme. As a result, the proposed scheme showed 29.09% higher distance estimation accuracy than the linear regression-based distance estimation scheme.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.64-76
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• 2014

This study identified the causes of errors that could take place in the estimation process of vehicle miles traveled and quantified the effects of each of those causes on the estimation accuracy of vehicle miles traveled via error rate to propose an efficient way to estimate vehicle miles traveled. The study proceeded as follows: first, the study established survey data of vehicle miles traveled in the pilot test areas to test the accuracy of a method to estimate vehicle miles traveled. Second, the causes of errors with the estimation of vehicle miles traveled were categorized into errors with the sample size, sampling methods, and homogeneous link setting methods. In addition, many different methodologies were set to minimize errors with the estimation of vehicle miles traveled according to each of the causes. Third, error rates of estimation of vehicle miles traveled were compared and analyzed according to each of the methodologies. Finally, a toy network was established to propose a way of estimating vehicle miles traveled by taking the local characteristics into consideration. The study finds its significance in that it proposed an efficient way to estimate vehicle miles traveled through an experiment and planning approach and made use of survey data of vehicle miles traveled to test estimation accuracy. The proposed way of estimating vehicle miles traveled by taking into account the local characteristics will make a contribution to the estimation of vehicle miles traveled by the areas in future along with the level of data offered in the study.

• Korean Journal of Optics and Photonics
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• v.17 no.6
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• pp.537-543
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• 2006

A method of estimating the distance using single zoom camera limits a distance range(only optical axis) in field of view. So, in this paper, we propose a method of estimating the distance information in Stereoscopic display using the stereo zoom lens module for estimating the distance in the wide range. The binocular stereo zoom lens system is composed using a horizontal moving camera module. The left and right images are acquired in polarized stereo monitor for getting the conversion and estimating a distance. The error distance is under 10mm which has difference between optically a traced distance and an estimated distance in left and right range $(0mm{\sim}500mm)$ at center. This presents the system using a function of the zoom and conversion has more precise distance information than that of conversion control. Also, a method of estimating a distance from horizontal moving camera is more precise value than that from toe-in camera by comparing the error distance of the two camera methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.595-605
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• 2012

DV-Hop is one of the well known range-free localization algorithms. The algorithm works well in case of isotropic network since the sensor and anchor nodes are placed in the entire area. However, it results in large errors in case of anisotropic networks where the hop count between nodes is not linearly proportional to the Euclidean distance between them. Hence, we proposed a novel range-free algorithm for anisotropic networks to improve the localization accuracy. In the paper, the Euclidean distance between anchor node and unknown node is estimated by the average hop distance calculated at each hop count with hop count and distance information between anchor nodes. By estimating the unknown location of nodes with the estimated distance estimated by the average hop distance calculated at each hop, the localization accuracy is improved. Simulation results show that the proposed algorithm has more accuracy than DV-Hop.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.265-271
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• 2023

Recently, location information services are gradually expanding due to the development of information and communication technology. RSSI is widely used to extract indoor and outdoor locations. The indoor and outdoor location estimation methods using RSSI are less accurate due to the influence of radio wave paths, interference, and surrounding wireless devices. In order to improve this problem, a distance estimation method that takes into account the wireless propagation environment is necessary. Therefore, in this study, we propose a distance estimation algorithm that takes into account the radio wave environment. The proposed method estimates the distance by learning RSSI input and output considering the RBF neural network and the propagation environment. To evaluate the performance of the proposed method, the performance of estimating the location of the receiver within a range of up to 55[m] using a BLE beacon transmitter and receiver was compared with the average filter and Kalman filter. As a result, the distance estimation accuracy of the proposed method was 6.7 times higher than that of the average filter and Kalman filter. As shown in the results of this performance evaluation, if the method of this study is applied to location services, more accurate location estimation will be possible.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12C
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• pp.1125-1132
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• 2005

Ultra-wideband (UWB) ranging poses a set of time delay estimation problems for designers. The possibility of a large error can be a challenging problem for accurate ranging and positioning. An approximate analysis of large error performance of UWB ranging in multipath and multiuser environments is posed. Both analytical and experimental approaches are taken to evaluate the large error variance in a correlation-based serial search scenario.

• The Journal of the Acoustical Society of Korea
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• v.38 no.6
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• pp.630-636
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• 2019

Passive Ranging Sonar (PRS) is a type of passive sonar consisting of three sub-array on the port and starboard, and has a characteristic of detecting a target and calculating a bearing and a distance. The bearing and distance calculation requires physical sub-array position information, and the bearing and distance accuracy performance are deteriorated when the position information of the sub-array is inaccurate. In particular, it has a greater impact on distance accuracy performance using plus value of two time-delay than a bearing using average value of two time-delay. In order to improve this, a study on sub-array position error estimation and error compensation is needed. In this paper, We estimate the sub-array position error based on enetic algorithm, an optimization search technique, and propose a method to improve the performance of distance accuracy by compensating the time delay error caused by the position error. In addition, we will verify the proposed algorithm and its performance using the sea-going data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6C
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• pp.453-461
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• 2012

This paper proposes an improved phase estimation method for AM(Amplitude Modulation) range measurement system. The previous phase estimation method induces errors by Doppler shift of a moving target. The proposed method compensates phase estimation error through the ADC(Adaptive Doppler Correction) to take the Doppler shift, thus can improve distance measurement accuracy. When compared with the previous method through simulation results, the Doppler shift compensation and accuracy are improved by 94.7% and 50%, respectively. Target distance error in an acoustic tank is estimated to be 7.7cm, which confirms that the proposed method can be used to estimate the distance in the marine environment.