• 제어로봇시스템학회논문지
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• 제22권2호
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• pp.133-138
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• 2016

This paper describes the track initiation and target-tracking filter for ship tracking in a marine environment by using Light Detection And Ranging (LiDAR). LiDAR with three-dimensional scanning capability is more useful for target tracking in the short to medium range compared to RADAR. LiDAR has rotating multi-beams that return point clouds reflected from targets. Through preprocessing the cluster of the point cloud, the center point can be obtained from the cloud. Target tracking is carried out by using the center points of targets. The track of the target is initiated by investigating the normalized distance between the center points and connecting the points. The regular track obtained from the track initiation can be maintained by the target-tracking filter, which is commonly used in radar target tracking. The target-tracking filter is constructed to track a maneuvering target in a cluttered environment. The target-tracking algorithm including track initiation is experimentally evaluated in a sea-trial test with several boats.

• 대한전기학회논문지
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• 제41권4호
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• pp.411-421
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• 1992

In the conventional track while scan (TWS) system, there are two major functions to be performed : detection and tracking. These two functions are normally designed and optimised independently. So TWS algorithm ignores the available decision features that can help in resolving the plot-to-track association ambiguity. Therefore conventional TWS system cna't track the targets in a densed multi-target environment. This paper presents a new TWS algorithm for multi-target track to solve the existing TWS system problem in clutter environment. The algorithm proposed in this paper is derived by modifying the part of joint probabilistic data association (JPDA) algotithm to get the one to one correspondence instead of multiple correspondence and combined with maneuvering detection logic so that it could also track the low maneuvering targets. Simulations to confirm the performance are done in crossing, parallel and maneuvering target. The proposed algorithm was successfully tracking targets above target situations.

• 한국군사과학기술학회지
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• 제9권3호
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• pp.33-40
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• 2006

In towed array passive sonar system, sonar operators cannot detect and track the all targets simultaneously in the omni-directional area by just Operator Initiated Tracking(OIT). In this paper, omni-directional automatic target detection and tracking algorithm is described and optimize the parameters through ocean data to overcome the drawbacks of OITs. The algorithm is verified through sea trials with submarines.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(4)
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• pp.159-162
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• 2001

In this Paper, a new multi-sensor single-target tracking method in cluttered environment is proposed. Unlike the established methods such as probabilistic data association filter (PDAF), the proposed method intends to reflect the information in detection phase into parameters in tracking so as to reduce uncertainty due to clutter. This is achieved by first modifying the Bayes risk in Bayesian detection criterion to incorporate the likelihood of measurements from multiple sensors. The final estimate is then computed by taking a linear combination of the likelihood and the estimate of measurements. We develop the procedure and discuss the results from representative simulations.

• Journal of Communications and Networks
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• 제15권2호
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• pp.164-172
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• 2013

We consider the problem of secure and robust clustering for quantized target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose a new method for jointly activating the best group of candidate sensors that participate in data aggregation, detecting the malicious sensors and estimating the target position. Firstly, we select the appropriate group in order to balance the energy dissipation and to provide the required data of the target in the WSN. This selection is also based on the transmission power between a sensor node and a cluster head. Secondly, we detect the malicious sensor nodes based on the information relevance of their measurements. Then, we estimate the target position using quantized variational filtering (QVF) algorithm. The selection of the candidate sensors group is based on multi-criteria function, which is computed by using the predicted target position provided by the QVF algorithm, while the malicious sensor nodes detection is based on Kullback-Leibler distance between the current target position distribution and the predicted sensor observation. The performance of the proposed method is validated by simulation results in target tracking for WSN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.1166-1179
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• 2013

In wireless sensor network (WSN) environments, environmental noises are generated by, for example, small passing animals, crickets chirping or foliage blowing and will interfere target detection if the noises are higher than the sensor threshold value. For accurate tracking by acoustic WSNs, these environmental noises should be filtered out before initiating track. This paper presents the effect of environmental noises on target tracking and proposes a new algorithm for the noise mitigation in acoustic WSNs. We find that our noise mitigation algorithm works well even for targets with sensing range shorter than the sensor separation as well as with longer sensing ranges. It is also found that noise duration at each sensor affects the performance of the algorithm. A detection algorithm is also presented to account for the Doppler effect which is an important consideration for tracking higher-speed ground targets. For tracking, we use the weighted sensor position centroid to represent the target position measurement and use the Kalman filter (KF) for tracking.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.114-119
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• 1991

An input estimation technique for tracking filter(CHP algorithm) suggested by Y.T. Chan et. al. has bad performance for low maneuvering targets. In this paper, two maneuver detection algorithms are applied to Singer's target model. First, an CHP input estimation technique is applied to 9 state target model. Second, we construct a maneuver detection and correction technique using pseudo acceleration measurements, which are derived directly from measurements. These two filters have good performance for even the low maneuvering targets.

• 한국항공우주학회지
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• 제30권2호
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• pp.75-82
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• 2002

불확실한 측정값 근원의 문제에서는 표적을 최적으로 탐지해내는 것이 유용하다. 본 논문에서는 클러터 환경에서 표적을 추적하는 경우에 탐지확률 및 오경보확률과 동시에 탐지문턱값 처리에 따른 추적오차를 살펴보고, 문턱값과 표적추적 유효화영역의 최적화 알고리즘을 제안한다. 제안한 알고리즘은 시뮬레이션을 통해 상태추정오차공분산의 측면에서 성능을 분석한다.

• 한국인터넷방송통신학회논문지
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• 제21권1호
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• pp.61-68
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• 2021

과거의 레이다는 임무 특성에 맞게 사격통제레이다, 탐지레이다, 추적레이다, 영상획득 레이다 등으로 구분되어 운영해왔다. 하지만 다기능 레이다는 표적 탐지, 추적, 피아식별, 재머 탐지 및 대응 등 단일 시스템 안에서 다양한 임무를 수행한다. 때문에 한정된 자원으로 다기능 레이다를 운용하기 위한 효율적인 자원관리는 필수적이다. 특히 탐지된 표적의 추적을 위한 표적 위협도와 이를 바탕으로 추적주기를 선정하는 방법은 중요한 이슈다. 위협표적을 집중으로 추적하다보면 다른 영역에서 탐지된 표적을 효율적으로 관리할 수 없고 탐지에 집중을 하면 추적성능이 저하될 수 있다. 때문에 효과적인 스케줄링이 필수적이다. 본 논문에서는 다기능 레이다 스케줄링 방안인 TaP(Time and Priority)알고리즘과 이를 구성하기 위한 소프트웨어적 설계 방법에 대해 제안한다.

• 대한임베디드공학회논문지
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• 제16권5호
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• pp.163-169
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• 2021

In this paper, we implemented a deep learning-based automatic object tracking and handy motion control drone system and analyzed the performance of the proposed system. The drone system automatically detects and tracks targets by analyzing images obtained from the drone's camera using deep learning algorithms, consisting of the YOLO, the MobileNet, and the deepSORT. Such deep learning-based detection and tracking algorithms have both higher target detection accuracy and processing speed than the conventional color-based algorithm, the CAMShift. In addition, in order to facilitate the drone control by hand from the ground control station, we classified handy motions and generated flight control commands through motion recognition using the YOLO algorithm. It was confirmed that such a deep learning-based target tracking and drone handy motion control system stably track the target and can easily control the drone.