• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.169-172
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• 2019

Frequency-modulated continuous wave(FMCW) radars with array antennas are widely used because of their light weight and relatively high resolution. A usual approach for the joint range and angle estimation of a target using an array FMCW radar is to create a range-angle matrix with the deramped received signal, and subsequently apply two-dimensional(2D) frequency estimation methods such as 2D fast Fourier transform on the range-angle matrix. However, such frequency estimation approaches cause bias errors since the frequencies in the range-angle matrix are not independent. Therefore, we propose a new maximum likelihood-based algorithm for joint range and angle estimation of targets using array FMCW radar, and demonstrate that the proposed algorithm achieves the Cram?r-Rao bounds, both for range as well as angle estimation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.2
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• pp.100-105
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• 2014

This paper comparatively analyze to integration case to have a influence detection range estimation about radar cross section in radar system. This paper estimate detection range used to probability of detection in radar equation that used to swerling case 1 in case of radar cross section is small and used to swerling case 3 in case of radar cross section is large. Through simulation, coherent integration and non-coherent integration about swerling case difference were comparatively analyzed. Through simulation, non-coherent integration case is outstanding detection range and we known that coherent integration don't suitable for detection range estimation.

• 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 the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.113-117
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• 2014

This paper comparatively analyze to integration case to have a influence detection range estimation about radar cross section in radar system. This paper estimate detection range used to probability of detection in radar equation that used to swerling case 1 in case of radar cross section is small and used to swerling case 3 in case of radar cross section is large. Through simulation, coherent integration and non-coherent integration about swerling case difference were comparatively analyzed. In the result of comparative analysis, non-coherent integration case is outstanding detection range and we known that coherent integration don't suitable for detection range estimation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.15-21
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• 2011

In the range-based localization, the localization accuracy will be high dependent on the accuracy of distance measurement between two nodes. The received signal strength(RSS) is one of the simplest methods of distance measurement, and can be easily implemented in a ranging-based method. However, a RSS-based localization scheme has few problems. One problem is that the signal in the communication channel is affected by many factors such as fading, shadowing, obstacle, and etc, which makes the error of distance measurement occur and the localization accuracy of sensor node be low. The other problem is that the sensor node estimates its location for itself in most cases of the RSS-based localization schemes, which makes the sensor network life time be reduced due to the battery limit of sensor nodes. Since beacon nodes usually have more resources than sensor nodes in terms of computation ability and battery, the beacon node based localization scheme can expand the life time of the sensor network. In this paper, therefore we propose a beacon node based localization algorithm using received signal strength(RSS) and path loss calibration in order to overcome the aforementioned problems. Through simulations, we prove the efficiency of the proposed scheme.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.210-213
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• 1999

수동소나체계에서 음원의 위치와 관련된 매개변수를 산출하기 위해 정합장처리(Matched Field Processing)가 이용된다 본 연구에서는 수직선배열센서를 이용한 정합장처리에서 음원 위치추정에 영향을 미치는 다양한 요인 중, 수직음속분포 오정합(mismatch)에 의한 영향을 MV 프로세서 (Minimum Variance Processor)를 이용하여 모의실험함으로써 그 결과를 분석하였다. 천해 모의환경에서 동일한 기울기로 증감하는 수직음속분포 오정합은 음원 위치추정에서 거리성분의 오차를 가지며, 상이한 기울기를 갖는 수직음속분포 오정합은 거리와 수심 성분의 오차가 유발됨을 확인할 수 있었다. 심해 모의 환경에서 수직음속분포 오정합은 거리와 수심 성분의 오차가 유발되고, 거리추정의 전반적인 경향은 천해의 동일한 기울기를 가지는 경우와 유사함을 확인할 수 있었다.

• 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 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.538-540
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• 2015

안전 거리 미확보는 교통 사고 원인 중 3위에 이르는 큰 위험 요소이다. 이러한 차간거리 미확보로 인한 사고는 조금만 빨리 대응하여도 사전에 방지할 수 있다. 따라서 주행 중 실시간으로 차간 거리를 추정하여 제공하는 시스템이 필요하다. 본 논문에서는 안드로이드 기반의 실시간 촬영 영상에서 차량의 에지와 후미등을 이용하여 차량을 검출하고, 검출된 차량의 폭을 이용하여 차간 거리를 추정하여 제공하는 시스템을 제안하고, 구현 결과를 제시한다.

• The KIPS Transactions:PartC
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• v.15C no.1
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• pp.31-36
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• 2008

The clock frequency difference of sensor nodes is one of main parameters in TOF estimation and affect to degrade ranging algorithms to estimate positions of mobile nodes in wireless sensor networks. The specification of IEEE802.15.4a describes asynchronous TWR and SDS-TWR insensitive to frequency difference without any additional network synchronization. But the TWR and SDS-TWR can not eliminate sufficiently the effect of frequency difference of node pair, packet processing delay and its difference. Especially use of low cost oscillator with wide range offset, sensor node with different hardware and software can make the positioning errors worse. We propose an estimation method of frequency differences, and apply the measured frequency differences to TWR and SDS-TWR. We evaluate the performance of the proposed algorithm with simulation, and make certain that the proposed method enhances the performance of existing algorithms with positioning errors less than 25 cm.