• The Journal of the Acoustical Society of Korea
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• v.38 no.2
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• pp.154-159
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• 2019

When measuring the radiating noise of an underwater moving source, the range information between the acoustic source and the receiver is an important evaluation factor, and the measurement standards such as a receiver position, a moving source depth and a speed are set. Although there is a method of using the cross correlation as a method of finding the range of the underwater moving source, this method requires a time synchronization process. In this paper, we proposed the method to estimate the range by comparing the Doppler frequency difference of the theoretically calculated multipath signal with the Doppler frequency difference of the multipath signal estimated from the received signal. The proposed method does not require a separate time synchronization process. Simulations were performed to verify the performance, and the ranging error of the proposed method reduced by about 95 % than that of the conventional method.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.455-465
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• 2024

In shallow water, the array invariant, known as the effective range estimation method, is developed based on the broadband dispersion characteristics in an ideal waveguide, which can be summarized by the waveguide invariant. It is robust enough to estimate both the array tilt and range simultaneously, even in situations where array tilt exists. Recently, it has been extended to fully consider the angle dependence of the waveguide invariant. However, applying the array invariant in range-dependent environments instead of range-independent environments can lead to range estimation errors due to bathymetry mismatch. In this paper, we interpret such range estimation errors by introducing the concept of effective range. Through numerical simulations and experimental data in a weakly range-dependent environment, we demonstrate the relationship between range estimation errors and effective range.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.1-9
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• 2012

In this paper, we propose a vision-based robust vehicle detection and inter-vehicle distance estimation algorithm for driving assistance system. We use the haar-like features of car rear-shadows, as well as the edge features for detecting of vehicles. The use of additional vehicle edge features greatly reduces the false-positive errors in the vehicle detection. And, after analyzing the conventional two inter-vehicle distance estimation methods: the location-based and the vehicle width-based, an improved inter-vehicle distance estimation algorithm which has the advantage of both method is proposed. Several experimental results show the effectiveness of the proposed method.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.320-328
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• 2023

Underwater active target detection is vital for defense systems, requiring accurate detection and estimation of distance and velocity. Sequential transmission is necessary at each beam angle, but divided pulse length leads to range ambiguity. Multi-frequency transmission results in time-bandwidth product losses when bandwidth is divided. To overcome these problem, we propose a novel method using Generalized Sinusoidal Frequency Modulation (GSFM) for rapid target detection, enabling low-correlation pulses between subpulses without bandwidth division. The proposed method allows for rapid updates of the distance and velocity of target by employing GSFM with minimized pulse length. To evaluate our method, we simulated an underwater environment with reverberation. In the simulation, a linear frequency modulation of 0.05 s caused an average distance estimation error of 50 % and a velocity estimation error of 103 % due to limited frequency band. In contrast, GSFM accurately and quickly tracked targets with distance and velocity estimation errors of 10 % and 14 %, respectively, even with pulses of the same length. Furthermore, GSFM provided approximate azimuth information by transmitting highly orthogonal subpulses for each azimuth.

• The Journal of the Acoustical Society of Korea
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• v.36 no.6
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• pp.413-418
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• 2017

When measuring the radiated noise of an underwater vehicle, range information between acoustic source and receiver is an important evaluating factor, but it cannot use GPS. There is a method of using the cross correlation for finding the range of the acoustic source instead of the GPS. However, this method has heavy computational loads. This paper proposes a fast Fourier transform based method with a relatively small amount of computation to estimate the range of a source. The proposed method estimates Doppler frequencies of CW signals received at multiple receivers by fast Fourier transform and estimates the source range by comparing theoretical Doppler frequencies map previously calculated by a receiver position and source depth information. Simulation and lake trial were performed to verify the performance.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.209-216
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• 2005

In wireless sensor networks, an estimation method is proposed for distances between nodes within two hops. The method uses only proximity information of nodes without physiccal distance measurements. It drastically improves the performance of localization algorithms based on Proximity information. In addition, it is the first method that estimates distances between nodes exactly in two hops. The distances are estimated from the number of common neighbors under an assumption that the number of common neighbors is proportional to the intersection of two unit disks centered at the two nodes. Simulation analysis shows that the estimation error is roughly from 10 to 20 percent of real distances. Meanwhile, the number of messages required by a distributed algorithm realizing this method is only two times the number of nodes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.400-406
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• 2006

Knowledge of camera parameters, such as position, orientation and focal length, is essential to 3D information recovery or virtual object insertion. This paper analyzes the error sensitivity of focal length due to position error of feature points which are employed for self-calibration. We verify the dependency of the focal length on the distance from the principal point to feature points with simulations, and propose a criterion for feature selection to reduce the error sensitivity.

• The Journal of the Acoustical Society of Korea
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• v.26 no.4
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• pp.166-172
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• 2007

In this paper, we address the target positioning performance of Multi-Static sonar with respect to target positioning method and measurement error. Based on the analysis on two candidate solution approaches, namely, Least Square (LS) using range and angular information simultaneously and Maximum Likelihood (ML) using only range information as the existing information fusion methods for possible application to Multi-Static sonar, we propose to employ ML using range and angular information. Assuming that each sensor can receive range and angular information, we conduct representative comparison experiments over the existing and proposed methods under various measurement noise scenarios. We also investigate the target positioning performance according to number of sensors, distance between transmitter and receiver. According to the experimental results, RMSE of the proposed ML with distance and direction information is found to be more superior to ML using distance alone and to LS in case distance between transmitter and receiver is longer and number of receiver is smaller.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.279-286
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• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.