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Normalized Rayleigh Likelihood를 활용한 표적신호세기정보 적용 다중표적추적 기술
김수진,정영헌,김성준,Kim, Sujin,Jung, Younghun,Kim, Seongjoon 한국군사과학기술학회 2017 한국군사과학기술학회지 Vol.20 No.4
This paper presents a multiple target tracking system using Normalized Rayleigh likelihood of amplitude information of target. Although many studies of Radar systems using amplitude information have been studied, they are focused on single target tracking. This paper proposes the multiple target tracking using amplitude information as well as kinematic information from Radar sensor. The amplitude information are applied in generating the association probability of joint probabilistic data association(JPDA) algorithm through the normalized Rayleigh likelihood. It is verified that the proposed system can enhance the track maintenance and tracking accuracy, especially, in the target crossing case.
이동물체 탐지를 위한 레이다 데이터의 거리-도플러 클러스터링 기법
김성준,양동원,정영헌,김수진,윤주홍,Kim, Seongjoon,Yang, Dongwon,Jung, Younghun,Kim, Sujin,Yoon, Joohong 한국군사과학기술학회 2014 한국군사과학기술학회지 Vol.17 No.6
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.
무인차량 자율주행을 위한 레이다 영상의 정지물체 너비추정 기법
김성준,양동원,김수진,정영헌,Kim, Seongjoon,Yang, Dongwon,Kim, Sujin,Jung, Younghun 한국군사과학기술학회 2015 한국군사과학기술학회지 Vol.18 No.6
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.