• 한국군사과학기술학회지
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• 제19권1호
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• pp.9-15
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• 2016

Source localization has developed in various fields of signal processing including radar, sonar, and wireless communication, etc. Source localization can be found by estimating the time difference of arrival between the each of sensors. Several methods like the NLS(Nonlinear Least Square) cost function have been proposed in order to improve the performance of time delay estimation. In this paper, we propose a clustering method using the four sensors with the same aperture as previous methods of using the three sensors. Clustering method can be improved the source localization performance by grouping similar estimated values. The performance of source localization using clustering method is evaluated by Monte Carlo simulation.

• 한국군사과학기술학회지
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• 제17권2호
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• pp.182-188
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• 2014

Source localization is an important problem in the field of sonar and radar, etc. For the purpose of source localization, two or more spatially separated sensors are often used to measure the time difference of arrivals of a radiating source whose transmitted signal waveform is unknown. The NLS(Nonlinear Least Square) cost function with curve fitting method was proposed recently, which provide robust source localization performance by reducing estimation ambiguity. However, even this algorithm shows degraded performance in a multipath environment. To estimates source localization correctly, source localization algorithm that eliminate the effect of multipath signals is required. In this paper, PMP(Power Matching Procedure) is added to the algorithm, which provides improved source localization performance by properly cutting out the effect of multipath signals. Through simulation the performance of the proposed source localization algorithm is verified.

• 전기학회논문지
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• 제67권9호
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• pp.1197-1201
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• 2018

In this paper, a Doppler radar for a localization of a human motion is demonstrated. In the system, we used a $8{\times}8$ phased array antenna using metamaterial phase shifters for easy and precise control of antenna beam pattern. Scanning area is a circular sector with an inscribed angle of $60^{\circ}$ and a diameter of 45m. This area is divided with 15 designated area and each area is scanned for 0.2 second. When there is a motion in a designated area, we are able to detect a frequency shift due to a Doppler effect. In this way it is possible to detect the location of motion. The experiment shows that 78% of position accuracy. The remaining 22% occurred the surroundings of the designated area.

• 자동차안전학회지
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• 제9권3호
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• pp.24-30
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• 2017

This paper presents the development of laser scanner based static obstacle detection algorithm for vehicle localization on lane lost section. On urban autonomous driving, vehicle localization is based on lane information, GPS and digital map is required to ensure. However, in actual urban roads, the lane data may not come in due to traffic jams, intersections, weather conditions, faint lanes and so on. For lane lost section, lane based localization is limited or impossible. The proposed algorithm is designed to determine the lane existence by using reliability of front vision data and can be utilized on lane lost section. For the localization, the laser scanner is used to distinguish the static object through estimation and fusion process based on the speed information on radar data. Then, the laser scanner data are clustered to determine if the object is a static obstacle such as a fence, pole, curb and traffic light. The road boundary is extracted and localization is performed to determine the location of the ego vehicle by comparing with digital map by detection algorithm. It is shown that the localization using the proposed algorithm can contribute effectively to safe autonomous driving.

• 한국군사과학기술학회지
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• 제18권6호
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• pp.711-720
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• 2015

Recently many studies of Radar systems mounted on ground vehicles for autonomous driving, SLAM (Simultaneous localization and mapping) and collision avoidance have been reported. Since several pixels per an object may be generated in a close-range radar application, a width of an object can be estimated automatically by various signal processing techniques. In this paper, we tried to attempt to develop an algorithm to estimate obstacle width using Radar images. The proposed method consists of 5 steps - 1) background clutter reduction, 2) local peak pixel detection, 3) region growing, 4) contour extraction and 5)width calculation. For the performance validation of our method, we performed the test width estimation using a real data of two cars acquired by commercial radar system - I200 manufactured by Navtech. As a result, we verified that the proposed method can estimate the widths of targets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5527-5545
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• 2019

Through-wall ultra-wide band (UWB) radar has been considered as one of the preferred and non-contact technologies for the targets detection owing to the better time resolution and stronger penetration. The high time resolution is a result of a larger of bandwidth of the employed UWB pulses from the radar system, which is a useful tool to separate multiple targets in complex environment. The article emphasised on human subject localization and detection. Human subject usually can be detected via extracting the weak respiratory signals of human subjects remotely. Meanwhile, the range between the detection object and radar is also acquired from the 2D range-frequency matrix. However, it is a challenging task to extract human respiratory signals owing to the low signal to clutter ratio. To improve the feasibility of human respiratory signals detection, a new method is developed via analysing the standard deviation based kurtosis of the collected pulses, which are modulated by human respiratory movements in slow time. The range between radar and the detection target is estimated using joint time-frequency analysis (JTFA) of the analysed characteristics, which provides a novel preliminary signature for life detection. The breathing rates are obtained using the proposed accumulation method in time and frequency domain, respectively. The proposed method is validated and proved numerically and experimentally.

• 한국산학기술학회논문지
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• 제19권2호
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• pp.117-124
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• 2018

본 논문은 KM-SAM 다기능레이더용 축류형 송풍기에 대한 국산화 개발 내용을 서술하고 있다. KM-SAM 다기능레이더는 중/저고도 위협표적을 탐지 및 추적하는 핵심 장비로 지속적인 외부 환경의 영향을 받는다. 이러한 장비의 원활한 운용을 위해서는 내부 온도 및 습기를 조절하는 송풍기가 필수적이며, 현재까지 다기능레이더용 송풍기는 전량 해외업체 수입에 의존하고 있다. 이러한 문제점 해결을 위해 국산화 개발 연구가 제안되었으며, 국산화 개발은 원제작사와 체계장비 규격 등 관련 기술자료 검토를 통한 요구도 분석, 시제품 설계, 성능시험 및 환경시험을 통한 설계요구조건 검증 등을 포함한다. 송풍기는 가이드 베인이 있는 축류형 팬으로 구성되고 모터는 최대 970 CFM의 풍량과 4.8 IWG 풍압을 발생하도록 제작되었다. 또한 신뢰성 있는 데이터 획득을 위해 AC 전원 공급기, 팬 성능시험기 및 데이터 수집 장비를 구축하여 시험평가를 수행하였으며, 시제품 모두 수입품 대비 동등수준 이상의 설계 요구도 검증이 이루어졌다.

• ETRI Journal
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• 제40권3호
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• pp.376-388
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• 2018

In through-the-wall radar imaging (TWRI), the presence of front and side walls causes multipath propagation, which creates fake targets called multipath ghosts. They populate the scene and reduce the probability of correct target detection, classification, and localization. In modern TWRI, specular multipath exploitation has received considerable attention for reducing the effects of multipath ghosts. However, this exploitation is challenged by the requirements of the reflecting geometry, which is not always available. Currently, the demand for a high radar image resolution dictates the use of a large aperture and wide bandwidth. This results in a large amount of data. To tackle this problem, compressive sensing (CS) is applied to TWRI. With CS, only a fraction of the data are used to produce a high-quality image, provided that the scene is sparse. However, owing to multipath ghosts, the scene sparsity is highly deteriorated; hence, the performance of the CS algorithms is compromised. This paper presents and discusses the adverse effects of multipath ghosts in TWRI. It describes the physical formation of ghosts, their challenges, and existing suppression techniques.

• 한국군사과학기술학회지
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• 제17권6호
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• pp.810-820
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• 2014

Recently many studies of Radar systems mounted on ground vehicles for autonomous driving, SLAM (Simultaneous localization and mapping) and collision avoidance are reported. In near field, several hits per an object are generated after signal processing of Radar data. Hence, clustering is an essential technique to estimate their shapes and positions precisely. This paper proposes a method of grouping hits in range-doppler domains into clusters which represent each object, according to the pre-defined rules. The rules are based on the perceptual cues to separate hits by object. The morphological connectedness between hits and the characteristics of SNR distribution of hits are adopted as the perceptual cues for clustering. In various simulations for the performance assessment, the proposed method yielded more effective performance than other techniques.

• 제어로봇시스템학회논문지
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• 제16권12호
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• pp.1159-1166
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• 2010

Today, detecting the location of moving object has been traced as various methods in our world. In this paper, we preset the system to improve the estimation accuracy utilizing detail localization using radar sensor based on WSN and situational awareness for a calibration (context aware) database, Rail concept. A variety of existing location tracking method has a problem with receiving of data and accuracy as tracking methodology, and since these located data are the only data to be collected for location tracing, the context aware or monitering as the surrounding environment is limited. So, in this paper, we enhanced the distance aware accuracy using radar sensor utilizing the Doppler effect among the distance measuring method, estimated the location using the Triangulation algorithm. Also, since we composed the environment data(temperature, illuminancem, humidity, noise) to entry of the database, it can be utilized in location-based service according to the later action information inference and positive context decision. In order to verify the validity of the suggested method, we give a few random situation and built test bed of designed node, and over the various test we proved the utilizing the context information through route tracking of moving and data processing.