• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.530-535
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• 2016

In this paper, the TTSE (Target size and Triangulation-based target Size Estimator) algorithm is proposed to estimate static target size in an imaging environment. The target size information is an important factor for accurate imaging target tracking. However, the imaging sensor cannot generate distance between the missile and target to calculate the target size. To overcome the problem, we propose the TTSE algorithm, which is based on target size and triangulation. The proposed method performance is tested in a target intercept scenario. The experiment results show that the proposed algorithm has better performance than the conventional algorithm (ET-TSE) for accurate CCD target size estimation.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.29-36
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• 2014

In this paper, a novel MBE (Model Based target size Estimator) is presented for SDIIR (Strap Down Imaging Infrared) seekers. The target tracking requires the target size information for which residual range between target and missile should be provided. Unfortunately, in general, the missile with passive sensor such as IIR (Imaging Infrared), CCD (Coupled Charging Device) cannot obtain range information. To overcome the problem, the proposed method enables the SDIIR seeker to estimates target size by using target size model and track the target. The performance of proposed method is tested at IIR target tracking of target intercept scenario. The experiment results show that the proposed algorithm has the relatively good performance.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.843-848
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• 2015

In this paper, The ARR-TSE (Automatic Range Restore - Triangulation based target Size Estimator) algorithm is presented for IIR (Imaging Infrared) seeker. The target size is important information for the IIR target tracking. The TSE (Triangulation based target Size Estimator) algorithm has suitable performance to estimate target size for static IIR target. but, the performance of the algorithm can be decreased by noise. In order to decrease influence of noise, we propose the ARR-TSE algorithm. The performance of proposed method is tested at target intercept scenario. The simulation results show that the proposed algorithm has the accurate target size estimating performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5624-5638
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• 2016

A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.836-842
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• 2015

In this paper, the target size and model based target size estimator (TMBE) algorithm is presented for iimaging infrared (IIR) seeker. At the imaging seeker, target size information is important factor for accurate tracking. The model based target size estimator filter (MBEF) algorithm was proposed to estimate target size at imaging infrared seeker. But, the model based target size estimator filter algorithm need to know relative distance from the target. In order to overcome the problem, we propose target size and model based target size estimator filter (TMBEF) algorithm which based on the target size. The performance of proposed algorithm is tested at target intercept scenario. The experiment results show that the proposed algorithm has the accurate target size estimating performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1377-1389
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• 2016

This paper presents a target model update scheme for the mean-shift tracking with background weighted histogram. In the scheme, the target candidate histogram is corrected by considering the back-projection weight of each pixel in the kernel after the best target candidate in the current frame image is chosen. In each frame, the target model is updated by the weighted average of the current target model and the corrected target candidate. We compared our target model update scheme with the previous ones by applying several test sequences. The experimental results showed that the object tracking accuracy was greatly improved by using the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.842-848
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• 2014

In this paper, an improved method RMBE (Resizable Model Based target size Estimator) is presented for SDIIR (Strap Down Imaging Infrared) seekers. At the target engaging scenario, the IIR target measurement is separated by various parts. In this case, target object changing is important to accurate target intercept. Therefore, we need robust target size estimator. Our proposed method resize estimated target size with MC-1 (Markov Chain I) for accurate target size estimation. The performance of proposed method is tested at IIR target tracking of target intercept scenario. The experiment results show that the proposed RMBE has improved performance than MBE.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1964-1981
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• 2014

An improved Mean-Shift (MS) tracker called joint CB-LBWH, which uses a combined weighted-histogram scheme of CBWH (Corrected Background-Weighted Histogram) and LBWH (likelihood-based Background-Weighted Histogram), is presented. Joint CB-LBWH is based on the notion that target representation employs both feature saliency and confidence to form a compound weighted histogram criterion. As the more prominent and confident features mean more significant for tracking the target, the tuned histogram by joint CB-LBWH can reduce the interference of background in target localization effectively. Comparative experimental results show that the proposed joint CB-LBWH scheme can significantly improve the efficiency and robustness of MS tracker when heavy occlusions and complex scenes exist.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.2
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• pp.114-120
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• 2008

In the vision-based recovery phase, a terminal guidance for the blended-wing UAV requires visual information of high accuracy. This paper presents the light source target design and detection algorithm for vision-based UAV recovery. We propose a recovery target design with red and green LEDs. This frame provides the relative position between the target and the UAV. The target detection algorithm includes HSV-based segmentation, morphology, and blob processing. These techniques are employed to give efficient detection results in day and night net recovery operations. The performance of the proposed target design and detection algorithm are evaluated through ground-based experiments.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.3
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• pp.320-331
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• 2019

In this paper, we propose a method of TMA(Target Motion Analysis) performance improvement using target elevation tracking and fusion in conformal array sonar. One of the most important characteristics of conformal array sonar is to detect a target elevation by a vertical beam. It is possible to get a target range to maximize advantages of the proposed TMA technology using this characteristic. And the proposed techniques include target tracking, target fusion, calculation of target range by multipath as well as TMA. A simulation study demonstrates the outstanding performance of proposed techniques.