• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권5호
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• pp.1711-1725
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• 2014

Multi-target tracking is the main purpose of many video surveillance applications. Recently, multi-target tracking based on the particle filter method has achieved robust results by using the data association process. However, this method requires many calculations and it is inadequate for real time applications, because the number of associations exponentially increases with the number of measurements and targets. In this paper, to reduce the computational cost of the data association process, we propose a novel multi-target tracking method that excludes particle samples in the overlapped predictive region between the target to track and marginal targets. Moreover, to resolve the occlusion problem, we define an occlusion mode with the normal dynamic mode. When the targets are occluded, the mode is switched to the occlusion mode and the samples are propagated by Gaussian noise without the sampling process of the particle filter. Experimental results demonstrate the robustness of the proposed multi-target tracking method even in occlusion.

• 한국군사과학기술학회지
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• 제15권3호
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• pp.343-349
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• 2012

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.

• 전기학회논문지
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• 제56권10호
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• pp.1826-1835
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• 2007

In this paper, we present a new approach for automatic detection and tracking for multiple targets. We combine a highest probability data association(HPDA) algorithm for target detection with a particle filter for multiple target tracking. The proposed approach evaluates the probabilities of one-to-one assignments of measurement-to-track and the measurement with the highest probability is selected to be target- originated, and the measurement is used for probabilistic weight update of particle filtering. The performance of the proposed algorithm for target tracking in clutter is compared with the existing clustering algorithm and the sequential monte carlo method for probability hypothesis density(SMC PHD) algorithm for multi-target detection and tracking. Computer simulation studies demonstrate that the HPDA algorithm is robust in performing automatic detection and tracking for multiple targets even though the environment is hostile in terms of high clutter density and low target detection probability.

• 한국해양공학회지
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• 제28권5호
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• pp.429-439
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• 2014

The target echoes contain information on the target such as the orientation, kinematics, and internal structure, as well as the external geometrical shape of the target. In addition, the pattern of the target echoes depends on the arrangement of the transmitters and receivers in space. Therefore, the study of the target echoes in a multi-static SONAR system can be useful for detecting and tracking submerged objects using an underwater surveillance system. For this purpose, an acoustic measuring system for multi-static target echoes was designed and tested in an acoustic water tank. Some preliminary data are presented and discussed.

• 한국컴퓨터정보학회논문지
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• 제21권11호
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• pp.31-38
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• 2016

In this paper, we propose multi-scale infrared target detection algorithm with varied filter size using integral image. Filter based target detection is widely used for small target detection, but it doesn't suit for large target detection depending on the filter size. When there are multi-scale targets on the sky background, detection filter with small filter size can not detect the whole shape of the large targe. In contrast, detection filter with large filter size doesn't suit for small target detection, but also it requires a large amount of processing time. The proposed algorithm integrates the filtering results of varied filter size for the detection of small and large targets. The proposed algorithm has good performance for both small and large target detection. Furthermore, the proposed algorithm requires a less processing time, since it use the integral image to make the mean images with different filter sizes for subtraction between the original image and the respective mean image. In addition, we propose the implementation of real-time embedded system using FPGA.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 추계학술대회
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• pp.696-701
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• 2004

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion, have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• 품질경영학회지
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• 제41권3호
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• pp.413-421
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• 2013

Purpose: System availability and life cycle cost are often used to evaluate the system performance and is influenced by the operation and maintenance characteristic. In this paper, we propose the method to improve life cycle cost and satisfy the target availability through redundancy allocation. Methods: We consider the redundancy is available at all items in multi level system. Thus, we assume that sub-assembly, module, components can be duplicated. Simulation and genetic algorithm are employed to optimize redundancy allocation. Results: Target availability is higher, the life cycle cost is increased. In addition, the items for redundancy are selected at higher level in multi level system if target availability is higher. Conclusion: We could know that target availability affects the duplication number of items and the selection of redundancy items. For further study, we will consider new optimization algorithms to compare with the proposed GA algorithm and improve optimization performance.

• 제어로봇시스템학회논문지
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• 제17권8호
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• pp.783-789
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• 2011

Target tracking performance improvement using multi-sensor data fusion is a challenging work. However, biases in the measurements should be removed before various data fusion techniques are applied. In this paper, a bias removing algorithm using measurement data from multi-radar tracking systems is proposed and evaluated by computer simulation. To predict bias estimation performance in various geometric relations between the radar systems and target, a system observability index is proposed and tested via computer simulation results. It is also studied that target tracking which utilizes multi-sensor data fusion with bias-removed measurements results in better performance.

• 제어로봇시스템학회논문지
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• 제21권1호
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• pp.7-13
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• 2015

Unmanned air vehicles (UAVs) are getting popular not only as a private usage for the aerial photograph but military usage for the surveillance, reconnaissance and supply missions. For an UAV to successfully achieve these kind of missions, geolocation (localization) must be implied to track an interested target or fly by reference. In this research, we adopted multi-sensor fusion (MSF) algorithm to increase the accuracy of the geolocation and verified the algorithm using two multicopter UAVs. One UAV is equipped with an optical camera, and another UAV is equipped with an optical camera and a laser range finder. Throughout the experiment, we have obtained measurements about a fixed ground target and estimated the target position by a series of coordinate transformations and sequential Kalman filter. The result showed that the MSF has better performance in estimating target location than the case of using single sensor. Moreover, the experimental result implied that multi-sensor geolocation algorithm is able to have further improvements in localization accuracy and feasibility of other complicated applications such as moving target tracking and multiple target tracking.

• 융합신호처리학회논문지
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• 제12권2호
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• pp.76-82
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• 2011

본 논문은 다중 해상도 영상에서 3차 페이싯 모델을 이용하여 적외선 영상의 원거리에 위치하고 있는 초소형 표적의 위치와 크기를 검출하기 위한 방법을 제안한다. 먼저, 원 영상을 점차 축소하여 여려 단계의 다중 해상도의 영상들로 구성한다. 각 단계에서의 다중 해상도 영상들에 대해 페이싯 모델과 국부 극대 조건을 적용하여 초소형 표적의 위치를 검출한다. 다중 해상도 영상에서 각 페이싯 모델의 국부 극대값을 의미하는 $D_2$값 중 최대 크기를 가지는 위치를 표적의 위치라고 평가한다. 이 경우 각 단계의 다중 해상도 영상들에 대해 크기가 다른 표적의 검출이 가능하게 된다. 본 논문에서 제안한 초소형 표적 검출 방법은 초소형 표적이 있는 다양한 적외선 영상에서 실험하였다. 기존의 페이싯 모델을 이용한 방법에서는 하나의 마스크만 적용시킨 것에 반해 제안된 방법은 하나의 마스크를 다중 해상도 영상에서 적용하였다. 고정된 마스크를 다중 해상도 영상에 적용함으로써 마스크의 크기를 달리하는 효과를 확인하였고 그에 따라 검출하는 표적의 크기도 다름을 확인하였다. 이를 이용해서 표적의 위치뿐만 아니라 크기도 검출할 수 있음을 확인하였다.