• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.598-601
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• 1995

This paper proposes a federated Kalman filter approach which utilizes information from multiple sensors and variable estimation model. Compared with the decentralized Kalman filter, the algorithm proposed in this paper demonstrates much better tracking performance in both maneuvering and constant velocity movement of the target.

• Transactions on Electrical and Electronic Materials
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• v.14 no.4
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• pp.187-192
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• 2013

Because of the importance of small target detection in infrared images, many studies have been carried out in this area. Using a Kalman filter and mean shift algorithm, this study proposes an algorithm to track multiple small moving targets even in cases of target disappearance and appearance in serial infrared images in an environment with many noises. Difference images, which highlight the background images estimated with a background estimation filter from the original images, have a relatively very bright value, which becomes a candidate target area. Multiple target tracking consists of a Kalman filter section (target position prediction) and candidate target classification section (target selection). The system removes error detection from the detection results of candidate targets in still images and associates targets in serial images. The final target detection locations were revised with the mean shift algorithm to have comparatively low tracking location errors and allow for continuous tracking with standard model updating. In the experiment with actual marine infrared serial images, the proposed system was compared with the Kalman filter method and mean shift algorithm. As a result, the proposed system recorded the lowest tracking location errors and ensured stable tracking with no tracking location diffusion.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.124-131
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• 2019

This study presents an imaging algorithm that can provide an image of a moving target in a multiple-input-multiple-output radar environment where multiple transmitting and receiving radars are fixed on the ground. The proposed algorithm, which is based on polar format processing using plane wave approximation, is shown to provide an unaliased image by using multiple transmitting radars even when the distances between the receiving radars are relatively large. We derive the conditions necessary to deploy the transmitting radars by which the resolution of the reconstructed image can be improved, while simultaneously reducing aliasing artifacts. Moreover, we offer a means of separating out each transmitting radar target echo. Finally, the performance of the proposed system is verified through a simulation.

• Journal of Advanced Navigation Technology
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• v.2 no.1
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• pp.43-52
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• 1998

In this paper, we have investigated the effects of geographic information on the performance of multiple ground target tracking system using multiple sensors. Geographic information is utilized in two cases: association and masking target measurement. Virtually no improvement is observed to the overall performance of tracking system when we applied mobility to the association procedure. Masking target measurement based on mobility produces desirable result that the number of false tracks is reduced. Since geographic information can be regarded as an additional sensor in sensor fusion paradigm, careful usage is required.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.1
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• pp.67-74
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• 2013

Nonlinear guidance law combined with a pseudo pursuit guidance is proposed, to perform stationary target observation mission. Multiple UAVs are considered, with waypoint constraint. The whole guidance is divided into two steps: firstly, waypoint approach, with specified incidence angle; and secondly, loitering around the stationary target. Geometric approach is used to consider the constraint on the waypoint, and a specified phase angle between the loitering UAV and the approaching UAV. In the waypoint approach step, UAVs fly to the waypoint using the pseudo pursuit guidance law. After passing the waypoint, UAVs turn around the target, using a distance error dynamics-based guidance law. Numerical simulations are performed, to verify the performance of the proposed guidance law.

• Proceedings of the KSME Conference
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• 2004.11a
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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.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.110-119
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• 1998

In this paper we discuss an algorithm to discriminate a garget under track against multiple acoustic counter-measure (ACM) sources, based on sequential testings of multiple hypotheses. The ACM sources are separated from the target under track and generate, while drifting, measurements with false range and Doppler information. The purpose of the ACM is to mislead the target tracking and to help the true target evade a pursuer. The proposed algorithm uses as a test statistic a function of the innovation sequences from extended Kalman filters to estimate the target dynamics and the drifting positions of the ACM sources. results of numerical experimenats are presented to show a performance profile of the proposed algorithm.

• 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 IKEEE
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• v.11 no.4
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• pp.137-144
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• 2007

Fire Control System(FCS) errors can be classified as hardware errors and software errors, and one of the software errors is from target tracking filter which estimates target's location, velocity, acceleration, and so on. It affects function of ballistic calculation equipment significantly. For gun to form predicted hitting point accurately and enhance hitting rate, we need status information of target's future location. Target tracking filter algorithms consist of Single Singer Model, Fixed Gain filter algorithm, IMM, PBIMM and so on. This paper will design IMM tracking filer, which is going to be! applied to domestic warship. Target tracking filter using CV model, Song model and CRT model for IMM tracking filter is made, and tracking ability is analyzed through Monte-Carlo simulation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.11
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• pp.878-883
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• 2018

A jamming design scheme to disturb target position estimation of a bistatic multiple-input multiple-output(MIMO) radar system is presented. The proposed method exploits the received signals from distributed multiple electronic sensors and combines them to produce a jamming signal. The proposed algorithm can eliminate the target by transmitting the delayed sum or the weighted sum of the received senor signals. Simulation results confirm the performance of the proposed method.