• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.344-346
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• 2019

In this paper, we propose a distance estimation method using the convolutional neural network in Ultra-Wideband (UWB) systems. The training data set used to learn the deep learning model using the convolutional neural network is generated by the MATLAB program and utilizes the IEEE 802.15.4a standard. The performance of the proposed distance estimation method is verified by comparing the threshold based distance estimation technique and the performance comparison used in the conventional distance estimation.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1323-1324
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• 2015

최근, 다수의 이동 로봇으로 구성된 무선 네트워크 기반 군집 로봇 시스템을 제한적인 환경을 벗어나 다양하고 동적인 환경에서 운용하기 위한 연구가 진행 중이다. 특히, 다수 로봇의 위치를 측정하기 위해 실내 환경에 기반 시설 없이 로봇에 장착된 센서들에 의해 위치를 추정하는 방법이 필요하다. 이를 위해, 본 논문에서는 로봇간의 상대적인 정보를 통해 다수 이동 로봇의 거리를 추정하는 방법을 제안한다. 제안한 방법은 먼저, 다수 이동 로봇의 거리를 추정하기 위해 무선 신호를 기반으로 하는 RSSI 방법을 이용하여 다수 이동 로봇의 거리를 추정한다. 그 다음, 추정된 거리와 추측 항법(Dead Reckoning)을 융합하여 이동 중인 로봇의 거리를 추정하는 방법을 제안한다. 마지막으로, 시뮬레이션 도구를 이용하여 응용 가능성을 증명한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.41-47
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• 2024

With the advancement and proliferation of the Internet of Things (IoT), a wide range of location-based services are being offered, and various ranging methods are being researched to meet the objectives of the required services. Conventional ranging methods involve the direct exchange of signals between tags and anchors to estimate distance, presenting a limitation in efficiently utilizing communication resources in large-scale IoT environments. To overcome these limitations, active-passive ranging methods have been proposed. However, there is a lack of theoretical convergence guarantees against clock drift errors and a detailed analysis of the characteristics of ranging estimation techniques, making it challenging to derive precise positioning results. In this paper, an improved active-passive ranging method that accounts for clock drift errors is proposed for precise positioning in large-scale IoT environments. The simulation results confirmed that the proposed active-passive ranging method can enhance distance estimation performance by up to 94.4% and 14.4%, respectively, compared to the existing active-passive ranging methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.5
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• pp.637-642
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• 2011

In this paper, a new technique to estimate the distances between a vanishing point and moving objects is proposed. A vanishing point for an input image is estimated and it use to extract distance form the vanishing point to a moving object. Using the obtained distances, moving objects is extracted. In simulation results, several performances for a test image sequnce is shown.

• 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 Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.65-71
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• 2014

This paper present the multi-modal user distance estimation system using mono camera and mono microphone basically equipped with a mobile device. In case of a distance estimation method using an image, we is estimated a distance of the user through the skin color region extraction step, a noise removal step, the face and eyes region detection step. On the other hand, in case of a distance estimation method using speech, we calculates the absolute difference between the value of the sample of speech input. The largest peak value of the calculated difference value is selected and samples before and after the peak are specified as the ROI(Region of Interest). The samples specified perform FFT(Fast Fourier Transform) and calculate the magnitude of the frequency domain. Magnitude obtained is compared with the distance model to calculate the likelihood. We is estimated user distance by adding with weights in the sorted value. The result of an experiment using the multi-modal method shows more improved measurement value than that of single modality.

• The Journal of the Acoustical Society of Korea
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• v.34 no.1
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• pp.60-65
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• 2015

In this paper, we used the sound of gunshots recorded by multiple microphones to increase the accuracy of the calculation of the distance between sniper and the microphone array. This method is crucial for achieving military objectives. Gunshots are comprised of the explosion of driving gas from the muzzle and the supersonic shock wave from the flying bullet. The original distance calculation method compares the time difference of arrival and angle of incidence to estimate the sniper's location. The disadvantage of this method is that when the angles of incidence coincide the margin of error increases, to solve this problem we suggest a new method using the characteristic changes of the shock wave with the increase of perpendicular distance between the microphone and the trajectory of the bullet. This theory is verified by experiments.

• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.52-57
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• 2001

The passive ranging estimation techniques using a focused beamformer have been studied under the water. It is well known that the passive ranging estimation method using a focused beamformer is excellently evaluated. Among these, the passive ranging sonar is known to have a good performance under low signal-to-noise. ratio. However, its performance is degraded in multi-source environments. In this paper, we proposed the technique using dual focused beamformers to estimate the range. And when the sampling frequency is low, it is very difficult to steer the focused beam to the desired direction, as a result of this, the low performance occurs because of a distorted beam pattern. In this paper, we study the effect of sampling rate on passive ranging by using focused beamformer. And we verified the performance of the proposed method via computer simulation.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.23-29
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• 2015

In this paper, we introduce a underwater ranging algorithm with Look-up Table (LUT) by modifying the existing method which is using the changes of angles of accoustic rays with SSP (Sound Speed Profile). We compare the horizontal distance errors and the calculation times. Our new algorithm exploits Time of Arriva l(ToA) - horizontal distance table based on SSP. This algorithm offers faster calculation speed than the previous one with the slight increase of the distance estimation error.