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복잡한 환경에서 다중표적추적을 위한 고속 트랙병합 기법
이승연,윤주홍,이석재,정영헌,최덕선,Lee, Seung-Youn,Yoon, Joo-Hong,Lee, Seok-Jae,Jung, Young-Hun,Choe, Tok-Son 한국군사과학기술학회 2012 한국군사과학기술학회지 Vol.15 No.4
In this paper, we proposed a method of fast track merging which is the foundation of track to track association technique. The existing method of track merging is performed throughout comparison between tracks to tracks. Therefore, it has heavy calculation time. In our research, we developed a method for fast clustering by using nearest neighbor measurement identification. The simulation results show that the proposed method is more faster than previous method about 3.3%. We expect that this method could be effectively used in multi-target tracking particularly in heavy clutter environment.
이승연,Lee, Seung-Youn 한국군사과학기술학회 2010 한국군사과학기술학회지 Vol.13 No.3
Adequate segmentation of target objects from the background plays an important role for the performance of automatic target recognition(ATR) system. This paper presents a new segmentation algorithm using fuzzy thresholding to extract a target. The proposed algorithm consists of two steps. In the first step, the region of interest(ROI) including the target can be automatically selected by the proposed robust method based on the frame difference of each image sensor. In the second step, fuzzy thresholding with a proposed membership function is performed within the only ROI selected in the first step. The proposed membership function is based on the similarity of intensity and the adjacency of target area on each image. Experimental results applied to real CCD/IR images show a good performance and the proposed algorithm is expected to enhance the performance of ATR system using multi-sensors.
이승연,곽동민,성기열,Lee, Seung-Youn,Kwak, Dong-Min,Sung, Gi-Yeul 한국군사과학기술학회 2010 한국군사과학기술학회지 Vol.13 No.4
The ability to navigate autonomously in off-road terrain is the most critical technology needed for Unmanned Ground Vehicles(UGV). In this paper, we present a method for vision-based terrain cover classification using DCT features. To classify the terrain, we acquire image from a CCD sensor, then the image is divided into fixed size of blocks. And each block transformed into DCT image then extracts features which reflect frequency band characteristics. Neural network classifier is used to classify the features. The proposed method is validated and verified through many experiments and we compare it with wavelet feature based method. The results show that the proposed method is more efficiently classify the terrain-cover than wavelet feature based one.
다중빔 방식의 FMCW 레이더 표적신호 시뮬레이터 개발
이승연,최덕선,정영헌,이석재,윤주홍,Lee, Seung-Youn,Choe, Tok-Son,Jung, Young-Hun,Lee, Seok-Jae,Yoon, Joo-Hong 한국군사과학기술학회 2012 한국군사과학기술학회지 Vol.15 No.3
To detect targets for autonomous navigation of unmanned ground vehicle, mounted sensors are required to work all-weather condition. In this point of view, the FMCW radar is quietly appropriate. In this paper, we present development results of target signal simulator for multi-beam type FMCW radar. A target signal simulator make pseudo target signals which simulates multiple moving targets. And we describe how to make hit information for each target in multi-beam type radar. The developed methods are utilized for target tracking device. Moreover it can be applied to similar target signal simulator.