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비행장애물 회피를 위한 라이다 기반 송전선 고속탐지 및 적용가능성 분석
이미진,이임평,Lee, Mijin,Lee, Impyeong 한국공간정보학회 2014 한국공간정보학회지 Vol.22 No.1
송전선은 항공사고를 야기하는 대표적인 장애물로써 인지되며, 비행 중 충돌회피를 위해 송전선의 실시간 탐지는 아주 중요하다. 최근 들어 이러한 비행장애물 회피를 위해 기상조건에 영향을 덜 받으며 주야에 관계없이 데이터 획득이 가능한 라이다의 활용이 증가하고 있다. 이에 본 연구에서는 라이다 데이터를 이용하여 비행장애물 회피를 위해 송전선을 고속으로 탐지하는 방법을 개발하였다. 제안된 방법은 먼저 지표면에서 반사된 점을 필터링 과정을 통해 제거하여 비지면점을 추출하고, 이중에서 분산 행렬의 고유값 비율을 이용하여 선형적으로 분포하는 점들을 추출하고, 마지막으로 송전탑(기둥)이나 굴뚝같이 수직방향으로 선형적으로 분포하는 점들이나 길이가 작은 선형점들을 제거한다. 구현된 알고리즘의 성능을 검증하기 위해 송전선이 포함된 영역에서 취득된 실측 및 시뮬레이션 데이터에 적용하였다. 탐지성능은 약 80%정도로 분석되었고, 처리시간은 평균 0.2초가 소요되었다. 향후 제시된 방법을 다양한 시험환경에 대해 실험을 수행하여 개선한다면, 비행장애물 회피용 시스템에 효과적으로 활용될 것을 판단된다. Power lines are one of the main obstacles causing an aircraft crash and thus their realtime detection is significantly important during flight. To avoid such flight obstacles, the use of LIDAR has been recently increasing thanks to its advantages that it is less sensitive to weather conditions and can operate in day and night. In this study, we suggest a fast method to detect power lines from LIDAR data for flight obstacle avoidance. The proposed method first extracts non-ground points by eliminating the points reflected from ground surfaces using a filtering process. Second, we calculate the eigenvalues for the covariance matrix from the coordinates of the generated non-ground points and obtain the ratio of eigenvalues. Based on the ratio of eigenvalues, we can classify the points on a linear structure. Finally, among them, we select the points forming horizontally long straight as power-line points. To verify the algorithm, we used both real and simulated data as the input data. From the experimental results, it is shown that the average detection rate and time are 80% and 0.2 second, respectively. If we would improve the method based on the experiment results from the various flight scenario, it will be effectively utilized for a flight obstacle avoidance system.
가이거모드 영상 LADAR 시스템의 시뮬레이션과 성능예측
김성준,이임평,이영철,Kim, Seongjoon,Lee, Impyeong,Lee, Youngcheol 한국군사과학기술학회 2012 한국군사과학기술학회지 Vol.15 No.5
LADAR systems can rapidly acquire 3D point clouds by sampling the target surfaces using laser pulses. Such point clouds are widely used for diverse applications such as DSM/DTM generation, forest biomass estimation, target detection, wire avoidance and so on. Many kinds of LADAR systems have been developed with their respective purposes and applications. Particularly, Geiger mode imaging LADAR systems are increasingly utilized since they are energy efficient thank to extremely sensitive detectors incorporated into the systems. The purpose of this research is the performance assessment of a Geiger mode imaging LADAR system based on simulation with the real system parameters. We thus developed a simulation method of such a LADAR system by modeling its geometric, radiometric, optic and electronic aspects. Based on the simulation, we performed the performance assessment of a newly designed system to derive the outlier ratio and false alarm rate expected during its operation in almost real environment with reasonable system parameters. The proposed simulation and performance assessment method will be effectively utilized for system design and optimization, and test data generation.
항공라이다데이터를 이용한 히스토그램 기반의 평균수목고도 추정
이미진(Lee, Mijin),황세란(Hwang, Seran),이임평(Lee, Impyeong) 한국측량학회 2012 한국측량학회 학술대회자료집 Vol.2012 No.4
As the necessity of forest conservation and management has been increased, various studies on measuring forest biomass have been actively performed. In this study, for forest biomass measurement, we estimated mean tree heights from airborne LIDAR data. We grouped the LIDAR data into a grid, and generated a histogram of point heights for each cell. By analyzing the histogram, we estimated the maximum and mean tree heights, and the mean crown height. We applied this method to the LIDAR data acquired from a mixed forest area and compared the results with field measurements. The estimated mean tree heights were underestimated by about 0.6 m and the mean crown height showed the RMSE of 2m. The proposed method will be effectively utilized for the accurate determination of forest biomass.