• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.479-482
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• 2004

In this article we consider a single maneuvering target Tracking algorithm in the presence of missing measurements and high clutter environments for multi-sensor target tracking problem. The tracking algorithm is based on the Particle filtering method to predict and update target states. Proposed is the AMM-PF(Auxiliary Multiple Model Particle Filter)[2] method for maneuvering target tracking to improve performance in track estimate and maintenance with a high level of uncertainty. The algorithm we propose is compared to the Extended Kalman Filter(EKF). A simulation study is included.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.517-523
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• 2011

The estimation filter in radar systems must track targets' position within low tracking error. In the Multi-Function Radar(MFR), ${\alpha}-{\beta}$ filter and Kalman filter are widely used to track single or multiple targets. However, due to target maneuvering, these filters may not reduce tracking error, therefore, may lost target tracks. In this paper, a target tracking filter based on particle filtering algorithm is proposed for the MFR. The advantage of this method is that it can track targets within low tracking error while targets maneuver and reduce impoverishment of particles by the proposed resampling method. From the simulation results, the improved tracking performance is obtained by the proposed filtering algorithm.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.139-144
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• 2005

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.

• 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.6 no.2
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• pp.173-180
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• 2000

During the last decade many researches have been working on multiple target tracking problem in the area of radar application, Various approaches have been proposed to solve the tracking problem and the concept of sensor fusion was established as an effort. In this paper utilization of geographic information for ground target tracking is investigated and performance comparison with the results of applying sensor fusion is described. Geographic information is used in three aspects: association masking target measurement and re-striction of removing true target. Simulation results indicate that using two sensors shows better performance with respect to tracking but a single with geographic information is a winner in reducing the number of false tracks.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.1
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• pp.75-84
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• 2008

A new automatic small target detection and tracking algorithm for the real-time IR surveillance system is presented. The automatic target detection and tracking algorithm of the real-time systems, requires low complexity and robust tracking performance in the cluttered environment. Linear-array and parallel-scan IR systems usually suffer from severe scan noise caused by the detector non-uniformity. After the spatial filtering and thresholding, this scan noise still remains as high amplitude clutter which degrades the target detection rate and tracking performance. In this paper, we propose a new feature which consists of area and validity information of a measurement. By adopting this feature to the measurements selection and track confirmation, we can increase the target detection rate and reduce both the track loss rate and false track rate. From the experimental results, we can validate the feasibility of the proposed method in the noisy IR images.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1245-1254
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• 2011

This paper proposes a target tracking algorithm for wheeled mobile robots using in various fields. For the stable tracking, we apply a vision system to a mobile robot which can extract targets through image processing algorithms. Furthermore, this paper presents an algorithm to position the mobile robot at the desired location from the target by estimating its relative position and attitude. We show the problem in the tracking method using the Position-Based Visual Servo(PBVS) control, and propose a tracking method, which can achieve the stable tracking performance by combining the PBVS control with Image-Based Visual Servo(IBVS) control. When the target is located around the outskirt of the camera image, the target can disappear from the field of view. Thus the proposed algorithm combines the control inputs with of the hyperbolic form the switching function to solve this problem. Through both simulations and experiments for the mobile robot we have confirmed that the proposed visual servo control method is able to enhance the stability compared to of the method using only either PBVS or IBVS control method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.62-72
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• 1993

The phased array antenna has the ability to perform adaptive sampling by directing the radar beam without inertia in any direction. The adaptive sampling capability of the phased array antenna allows each sampling time interval to be varied for each target, depending on the acceleration of each target at any time. In this paper we design a three dimensional adaptive target tracking algorithm for the phased array radar system with a given set of measurement parameters. The tracking algorithm avoids taking unnecessarily frequent samples, while keeping the angular prediction error within a fraction of antenna beamwidth so that the probability of detection will not be degraded during a track updata illuminations. In our algorithm, the target model and the sampling rate are selected depending on the target range and the target maneuver status which is determined by a maneuver level detector. A detailed simulation is conducted to test the validity of our tracking algorithm for target trajectories under various conditions of maneuver.

• 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.