• 한국군사과학기술학회지
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• 제26권1호
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• pp.22-30
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• 2023

When tracking small UAVs and drone targets in cloud clutter environments, MWIR sensors are often unable to track targets continuously. To overcome this problem, the SWIR sensor is mounted on the same gimbal. Target tracking uses sensor information fusion or selectively applies information from each sensor. In this case, parallax correction using the target distance is often used. However, it is difficult to apply the existing method to small UAVs and drone targets because the laser rangefinder's beam divergence angle is small, making it difficult to measure the distance. We propose a tracking method which needs not parallax correction of sensors. In the method, images from MWIR and SWIR sensors are captured simultaneously and a tracking error for gimbal driving is chosen by effectiveness measure. In order to prove the method, tracking performance was demonstrated for UAVs and drone targets in the real sky background using MWIR and SWIR image sensors.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1740-1741
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• 2011

This paper proposes a new linear recursive target state estimator for automotive collision warning system. The target motion is modeled in Cartesian coordinate system while the radar measurements such as range, line-of-sight angle and range rate are obtained in polar coordinate system. To solve the problem by nonlinear relation between these two coordinate system, a practical linear filter design scheme employing the predicted line-of-sight Cartesian coordinate system (PLCCS) is proposed. Especially, PLCCS can effectively incorporate range rate measurements into target tracking system. It is known that the utilization of range rate measurements enables the improvement of target tracking performance. Moreover, PLCCS based target tracking system is implemented by linear recursive filter structure and hence is more suitable scheme for the development of reliable collision warning system. The performance of the proposed method is demonstrated by computer simulations.

• 전자공학회논문지 IE
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• 제48권1호
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• pp.25-29
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• 2011

Ryu 등은 방위각 이노베이션을 효율적으로 구할 수 있는 계산식을 가진 다중표적 방위각 추적 알고리즘을 제안하였으며, 이 알고리즘은 데이터연관 문제가 발생하지 않는다는 장점을 가지고 있다. Ryu 알고리즘의 효율적인 방위각 이노베이션 계산식은 선배열센서를 사용하는 경우에 대하여 유도하였기 때문에, Ryu 알고리즘은 선배열센서에만 적용이 가능하다. 다중표적 방위각 추적 문제를 연구하는 많은 분야에서 다양한 형태의 배열센서를 사용하고 있다. 특히, 소나(Sonar)에서는 선배열센서 뿐만 아니라 원통형 배열센서도 많이 사용되고 있으며, 원통형 배열센서를 사용하는 대표적인 소나로 선체고정형 소나(Hull Mounted Sonar)가 있다. 본 논문에서 Ryu의 다중표적 방위각 추적 알고리즘을 원통형 배열센서에 적용할 수 있도록 수정하고, 다양한 컴퓨터 시뮬레이션을 통해서 수정된 알고리즘의 추적성능을 확인한다.

• 한국전자파학회논문지
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• 제26권6호
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• pp.572-580
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• 2015

저고도 비행체는 다중 경로 간섭의 영향으로 인해 계측 레이더의 RF 스킨 추적 시 고각 방향의 오차 신호 증가로 안정적인 추적 데이터를 획득할 수 없다. 이 한계를 극복하고자 본 논문에서는 레이저 추적기를 이용한 저고도 비행체 추적 기법을 제안하였다. 짧은 펄스폭과 좁은 빔 폭을 갖는 레이저의 특성을 이용하여 각도 해상도를 높이는 방법으로 다중 경로 간섭의 영향을 줄일 수 있다. 지면에 설치된 통합형 교정기와 해수면의 표적선을 대상으로 RF 스킨 추적, 비콘 추적, 레이저 추적 결과의 불확도 및 오차 신호 분석을 통해 다중경로 간섭 조건에서 레이저 추적이 RF 스킨 추적에 비해 추적 성능이 뛰어남을 확인하였다.

• 제어로봇시스템학회논문지
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• 제11권4호
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• pp.369-377
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• 2005

This paper describes the realization of a coordinates tracking algorithm for an EOTS (Electro-Optical Tracking System). The EOTS stabilizes the image sensors, tracks targets automatically, and provides navigation capability for vehicles. The coordinates tracking algorithm calculates the azimuth and the elevation angle of an EOTS using the inertial navigation system and the attitude sensors of the vehicle, so that LOS designates the target coordinates which are generated by a Radar. In the error analysis, the unexpected behaviors of an EOTS due to the time delay and deadbeat of the digital signals of the vehicle equipments are anticipated and the countermeasures are suggested. The application of this algorithm to an EOTS will improve the operational capability by reducing the time which is required to find the target and support flight especially in the night time flight and the poor weather condition.

• ETRI Journal
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• 제38권2호
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• pp.356-365
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• 2016

This research proposes a modified particle filter to increase the accuracy of vehicle tracking in a noisy and occluded medium. In our proposed method for vehicle tracking, the direction angle of a target vehicle is calculated. The angular difference between the motion direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted depending on their angular distance to the motion direction. Those particles moving in a direction similar to that of the target vehicle are assigned larger weights; this, in turn, increases their probability in a given likelihood function (part of the process of estimation of a target's state parameters). The proposed method is compared against a condensation algorithm. Our results show that the proposed method improves the stability of a particle filter tracker and decreases the particle consumption.

• 한국군사과학기술학회지
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• 제5권3호
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• pp.62-76
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• 2002

This paper describes the design of a Coordinates Tracking algorithm for EOTS and its error analysis. EOTS stabilizes the image sensors such as FLIR, CCD TV camera, LRF/LD, and so on, tracks targets automatically, and provides navigation capability for vehicles. The Coordinates Tracking algorithm calculates the azimuth and the elevation angle of EOTS using the inertial navigation system and the attitude sensors of the vehicle, so that LOS designates the target coordinates which is generated by a Radar or an operator. In the error analysis in this paper, the unexpected behaviors of EOTS that is due to the time delay and deadbeat of the digital signals of the vehicle equipments are anticipated and the countermeasures are suggested. This algorithm is verified and the error analysis is confirmed through simulations. The application of this algorithm to EOTS will improve the operational capability by reducing the time which is required to find the target and support especially the flight in a night time flight and the poor weather condition.

• 한국전자파학회논문지
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• 제28권2호
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• pp.129-138
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• 2017

본 논문에서는 지상레이다가 추적 중인 항공기로부터 획득한 수신신호를 이용하여 도플러 형상(signature)을 추출하였다. 이를 위해 펄스열(pulse train) 파형의 수학적 모델로부터 레이다의 도플러 해상도를 검증하고, 비행 중인 항공기 도플러 형상이 엔진에 대한 레이다 측각(aspect angle)과 엔진의 제원에 따라 결정됨을 보였다. 이를 확인하기 위해 비행 중인 항공기에서 반사된 레이다 수신신호를 레이다 수신신호 저장장치를 이용하여 획득하고, 수신신호로부터 도플러 형상을 추출한 후, 항공기 추적 정보로부터 엔진에 대한 레이다 측각을 추정하였다. 이들 결과를 조합하여 측각에 대한 상대 도플러 형상 차이를 확인하고, 레이다에 사용가능한 표적인식용 도플러 프로파일을 제안하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.181-184
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• 1999

Leading vehicle states are useful and essential elements in adaptive cruise control (ACC) system, collision warning (CW) and collision avoidance (CA) system, and automated highway system (AHS). There are many approaches in ACC using Kalman filter. Mostly only distance to leading vehicle and velocity difference are estimated and used for the above systems. Applications in road vehicle in curved road need to obtain more informations such as yaw angle, steering angle which can be estimated using vision system. Since vision system is not robust to environment change, we used Kalman filter to estimate distance, velocity, yaw angle, and steering angle. Application to active tracking of target vehicle is shown.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권2호
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• pp.710-726
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• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.