• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.251-257
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• 2021

An underwater platform operating a passive sonar needs to acquire the target position to perform its mission. In an environment where sea-floor reflections exist, the position of a target can be estimated using the difference in the arrival time between the signals received through multipaths. In this paper, a method of localization for passive sonar is introduced, based on the EKF (Extended Kalman Filter) using the multipath time difference of arrival in underwater environments. TMA (Target Motion Analysis) requires accumulated measurements for long periods and has limitations on own-ship movement, allowing it to be used only in certain situations. The proposed method uses an EKF, which takes measurements of the time differences of the signal arrival in multipath environments. The method allows for target localization without restrictions on own-ship movement or the need for an observation time. To analyze the performance of the proposed method, simulation according to the distance and depth of the target was performed repeatedly, and the localization error according to the distance and water depth were analyzed. In addition, the correlation with the estimated position error was assessed by analyzing the arrival time difference according to the water depth.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.133-140
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• 2016

In active sonar field, a target detection and localization based on a distributed sensor network has been much studied for the underwater surveillance of the coast. Zhou et al. proposed a target localization method utilizing the positions of target-detected sensors in distributed sensor network which consists of detection-only sensors. In contrast with a conventional method, Zhou's method dose not require to estimate the propagation model parameters of detection signal. Also it needs the lower computational complexity, and to transmit less data between network nodes. However, it has large target localization error. So it has been modified for reducing localization error by Ryu. Modified Zhou's method has better estimation performance than Zhou's method, but still relatively large estimation error. In this paper, a target localization method based on modified Zhou's method is proposed for reducing the localization error. The proposed method utilizes the geometry of the positions of target-detected sensors and a line that represents the bearing of target, a line can be found by modified Zhou's method. This paper shows that the proposed method has better target position estimation performance than Zhou's and modified Zhou's method by computer simulations.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.201-204
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• 2001

디지털 카메라를 이용하여 인체의 영상을 촬영하여 3D 인체를 계측하는 영상 계측 방법을 제안한다. 영상 계측을 위해 인체 촬영 환경을 설정하고, 정면, 측면, 후면의 인체 2D 영상을 촬영하여 사영투영을 고려하여 3D 인체를 추정하는 알고리즘을 개발한다. 인체 계측의 항목 중 40항목에 대해 직접 계측, 영상 계측, 3D 계측을 3인이 교대로 시행한 결과를 비교하고 있다. 계측자별, 계측 방법별로 비교할 때, 영상 계측은 최대오차 0.44cm로 3D 계측(허용오차 0.5cm)와 유사하여, 직접 계측에 비해 우수한 성능을 나타내고 있다. 이것은 영상 계측에서 사영투영을 이용하여 인체의 3D위치를 추정하여 계측 결과를 보정하고 있기 때문이다. 또한, 계측치 이외에 계측 장비, 비용, 기동성, 인력 부담등 여러 가지면 에서도 영상 계측은 장점을 고루 갖춘 방법으로 인체 계측에 사용할 수 있는 새로운 방법으로 기대된다.

• Journal of the Korean Institute of Navigation
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• v.17 no.1
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• pp.99-105
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• 1993

Underwater acoustic positioning systems have been extensively used not only in surface position fixing but also in underwater position fixing. Recently, these systems have been applied in the field of installation and underwater inspection offshore platforms etc. But in these systems are included the fixing errors as results of a signal with noise and irregular motion of vessel by ocean waves. In this paper to improve the accuracy of the position fixing a Kalman filter is applied to the short baseline(SBL) acoustic positioning system. The optimal position obtained by the Kalman filter is compared with the raw position and it is confirmed that the former is more accurate than the latter.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.615-620
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• 2009

Nowadays, wireless infrastructures such as sensor networks are widely used in many different areas. In case of sensor networks, the wirelessly connected sensors can execute different kind of tasks in a diversity of environments, and one of the most important parameter for a successful execution of such tasks is the location information of each node. As to localization problems in WSNs, there are ToA (Timer of Arrival), RSS (Received Signal Strength), AoA (Angle of Arrival), etc. In this paper, we propose a modification of existing ToA and RSS based methods, adding a weighted average scheme to measure more precisely the distance between nodes. The comparison experiments with the traditional ToA method show that the average error value of proposed method is reduced by 0.1 cm in indoor environment ($5m{\times}7m$) and 0.6cm in outdoor environment ($10{\times}10m$).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1813-1819
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• 2011

In this research, the location positioning system supposed is concerned with range recognition technology using phase and magnitude of radio wave and adding technology of image histogram by vision. By the proposed technology, we design the radio transmitter and receiver and realize the measurement system, and save the data in disk that is earned from 900Mhz RF signal, middle frequency 450Khz of analog signal. Range information is earned the data through digital signal processing of IF signal. For the estimation of range measured, we analyze the difference between real range and measurement range, and also suggest the method to improve the measurement error using average processing and amplitude properties.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.155-161
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• 2015

As the popularity of the smartphone becomes increase, indoor smartphone positioning technology has been actively studied. The acoustic signal generated from the smartphone is received from the several microphones at the relative positioning system, and the trigger signal is proposed to mitigate the multipath effect and the effect is verified. But for the simple trigger method, there would be error occurred according to the variation of the distance or surrounding noise. In this paper, in order to resolve the problems, the dynamic trigger threshold technology is proposed and its effect is verified by the experiment.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1882-1883
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• 2007

본 논문은 근거리무선통신을 포함한 위치서비스를 위한 무선통신응용분야에 적용될 수 있는 고신뢰 고정밀 무선위치인식기술 방법을 제안한다. 제안된 위치인식방법은 양방향통신을 통해 추정된 무선태그의 신호세기 및 시간차를 측정된 거리정보를 바탕으로 상대적 위치에 대한 확률적 계산을 수행하게 되며, 측정데이터의 부정확성으로 인한 위치측정의 오차를 줄일 수 있다. 또한 제안된 고신뢰 무선측위 코아 스택을 근거리무선네트워크 형성이 가능한 2.4 GHz ISM 협대역 밴드의 ZigBee 무선비콘 및 무선태그 디바이스들에 탑재하고 실증시험을 위하여 스마트 홈 실내 환경 아래에서 $1m\;{\times}\;1m$ 의 위치인지를 가능케 하는 위치인식시스템을 구현한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.23-30
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• 2011

In the wireless sensor network(WSN), the detection of precise location of sensor nodes is essential for efficiently utilizing the sensing data acquired from sensor nodes. Among various location methods, the received signal strength (RSS) based localization scheme is mostly preferable in many applications since it can be easily implemented without any additional hardware cost. Since the RSS localization method is mainly effected by radio channel between two nodes, outlier data can be included in the received signal strength measurement specially when some obstacles move around the link between nodes. The outlier data can have bad effect on estimating the distance between two nodes such that it can cause location errors. In this paper, we propose a RSS-based localization method using Robust Statistic and Gaussian filter algorithm for enhancing the accuracy of RSS-based localization. In the proposed algorithm, the outlier data can be eliminated from samples by using the Robust Statistics as well as the Gaussian filter such that the accuracy of localization can be achieved. Through simulation, it is shown that the proposed algorithm can increase the accuracy of localization and is more robust to non gaussian noise channels.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.2
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• pp.163-171
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• 2014

Based on the GPS/IMU integration, the car navigation has unstable conditions as well as drastically reduces accuracies in urban region. Nowadays, many cars mounted the camera to record driving states. If the ground coordinates of street furniture are known, the position and attitude of camera can be determined through SPR(Single Photo Resection). Therefore, an estimated position and attitude from SPR can be applied measurements in Kalman filter for updating errors of navigation solutions from GPS/IMU integration. In this study, the GPS/IMU/SPR integration algorithm was developed in loosely coupled modes through extended Kalman filters. Also, in order to analyze performances of GPS/IMU/SPR, simulation tests were conducted in GPS signal reception environments and the GCPs (Ground Control Points) distributions. In fact, the position and attitude gathered from GPS/IMU/SPR integration are more precise than the position and attitude from GPS/IMU integration. When IPs (image points), corresponded to GCPs, were concentrated in the center of image, the position error in the optical axis respectively increased. To understand effects from SPR, we plan to carry additional test on the magnitude of GCP, IP and initial exterior orientation errors.