Simulation of Rosette Scanning Infrared Seeker and Counter-Countermeasure Using K-Means Algorithm
Summary :
The rosette-scanning infrared seeker (RSIS) is a tracker that a single infrared detector scans the total field of view (TFOV) in a rosette pattern, and then produces 2D image about a target. Since the detected image has various shapes in accordance with the target position in the TFOV, it is difficult to determine a precise target position from the obtained image. In order to track this type of target, therefore, we propose an efficient tracking method using the K-means algorithm (KMA). The KMA, which classifies image clusters and calculates their centers, is used to cope with an countermeasure (CM) such as an IR flare. To evaluate the performance of the RSIS using the KMA dynamically, we simulate the RSIS in the various conditions, and discuss the tracking results.
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- IEICE TRANSACTIONS on Fundamentals Vol.E82-A No.6 pp.987-993
- Publication Date
- 1999/06/25
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- Online ISSN
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- Type of Manuscript
- Special Section PAPER (Special Section of Papers Selected from 1998 International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC '98))
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Surng-Gabb JAHNG, Hyun-Ki HONG, Jong-Soo CHOI, "Simulation of Rosette Scanning Infrared Seeker and Counter-Countermeasure Using K-Means Algorithm" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 6, pp. 987-993, June 1999, doi: .
Abstract: The rosette-scanning infrared seeker (RSIS) is a tracker that a single infrared detector scans the total field of view (TFOV) in a rosette pattern, and then produces 2D image about a target. Since the detected image has various shapes in accordance with the target position in the TFOV, it is difficult to determine a precise target position from the obtained image. In order to track this type of target, therefore, we propose an efficient tracking method using the K-means algorithm (KMA). The KMA, which classifies image clusters and calculates their centers, is used to cope with an countermeasure (CM) such as an IR flare. To evaluate the performance of the RSIS using the KMA dynamically, we simulate the RSIS in the various conditions, and discuss the tracking results.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_6_987/_p
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@ARTICLE{e82-a_6_987,
author={Surng-Gabb JAHNG, Hyun-Ki HONG, Jong-Soo CHOI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Simulation of Rosette Scanning Infrared Seeker and Counter-Countermeasure Using K-Means Algorithm},
year={1999},
volume={E82-A},
number={6},
pages={987-993},
abstract={The rosette-scanning infrared seeker (RSIS) is a tracker that a single infrared detector scans the total field of view (TFOV) in a rosette pattern, and then produces 2D image about a target. Since the detected image has various shapes in accordance with the target position in the TFOV, it is difficult to determine a precise target position from the obtained image. In order to track this type of target, therefore, we propose an efficient tracking method using the K-means algorithm (KMA). The KMA, which classifies image clusters and calculates their centers, is used to cope with an countermeasure (CM) such as an IR flare. To evaluate the performance of the RSIS using the KMA dynamically, we simulate the RSIS in the various conditions, and discuss the tracking results.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - Simulation of Rosette Scanning Infrared Seeker and Counter-Countermeasure Using K-Means Algorithm
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 987
EP - 993
AU - Surng-Gabb JAHNG
AU - Hyun-Ki HONG
AU - Jong-Soo CHOI
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E82-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 1999
AB - The rosette-scanning infrared seeker (RSIS) is a tracker that a single infrared detector scans the total field of view (TFOV) in a rosette pattern, and then produces 2D image about a target. Since the detected image has various shapes in accordance with the target position in the TFOV, it is difficult to determine a precise target position from the obtained image. In order to track this type of target, therefore, we propose an efficient tracking method using the K-means algorithm (KMA). The KMA, which classifies image clusters and calculates their centers, is used to cope with an countermeasure (CM) such as an IR flare. To evaluate the performance of the RSIS using the KMA dynamically, we simulate the RSIS in the various conditions, and discuss the tracking results.
ER -
English
