IEICE TRANSACTIONS on Communications
Ghost Reduction for Multiple Angle Sensors Based on Tracking Process by Dual Hypotheses
Summary :
A ghost reduction algorithm for multiple angle sensors tracking objects under dual hypotheses is proposed. When multiple sensors and multiple objects exist on the same plane, the conventional method is unable to distinguish the real objects and ghosts from all possible pairs of measurement angle vectors. In order to resolve the issue stated above, the proposed algorithm utilizes tracking process considering dual hypotheses of real objects and ghosts behaviors. The proposed algorithm predicts dynamics of all the intersections of measurement angle vector pairs with the hypotheses of real objects and ghosts. Each hypothesis is evaluated by the residuals between prediction data and intersection. The appropriate hypothesis is extracted trough several data sampling. Representative simulation results demonstrate the effectiveness of the proposed algorithm.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E97-B No.2 pp.504-511
- Publication Date
- 2014/02/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E97.B.504
- Type of Manuscript
- PAPER
- Category
- Sensing
Authors
Kosuke MARUYAMA
Mitsubishi Electric Corp.
Hiroshi KAMEDA
Mitsubishi Electric Corp.
Keyword
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Kosuke MARUYAMA, Hiroshi KAMEDA, "Ghost Reduction for Multiple Angle Sensors Based on Tracking Process by Dual Hypotheses" in IEICE TRANSACTIONS on Communications,
vol. E97-B, no. 2, pp. 504-511, February 2014, doi: 10.1587/transcom.E97.B.504.
Abstract: A ghost reduction algorithm for multiple angle sensors tracking objects under dual hypotheses is proposed. When multiple sensors and multiple objects exist on the same plane, the conventional method is unable to distinguish the real objects and ghosts from all possible pairs of measurement angle vectors. In order to resolve the issue stated above, the proposed algorithm utilizes tracking process considering dual hypotheses of real objects and ghosts behaviors. The proposed algorithm predicts dynamics of all the intersections of measurement angle vector pairs with the hypotheses of real objects and ghosts. Each hypothesis is evaluated by the residuals between prediction data and intersection. The appropriate hypothesis is extracted trough several data sampling. Representative simulation results demonstrate the effectiveness of the proposed algorithm.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E97.B.504/_p
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@ARTICLE{e97-b_2_504,
author={Kosuke MARUYAMA, Hiroshi KAMEDA, },
journal={IEICE TRANSACTIONS on Communications},
title={Ghost Reduction for Multiple Angle Sensors Based on Tracking Process by Dual Hypotheses},
year={2014},
volume={E97-B},
number={2},
pages={504-511},
abstract={A ghost reduction algorithm for multiple angle sensors tracking objects under dual hypotheses is proposed. When multiple sensors and multiple objects exist on the same plane, the conventional method is unable to distinguish the real objects and ghosts from all possible pairs of measurement angle vectors. In order to resolve the issue stated above, the proposed algorithm utilizes tracking process considering dual hypotheses of real objects and ghosts behaviors. The proposed algorithm predicts dynamics of all the intersections of measurement angle vector pairs with the hypotheses of real objects and ghosts. Each hypothesis is evaluated by the residuals between prediction data and intersection. The appropriate hypothesis is extracted trough several data sampling. Representative simulation results demonstrate the effectiveness of the proposed algorithm.},
keywords={},
doi={10.1587/transcom.E97.B.504},
ISSN={1745-1345},
month={February},}
Copy
TY - JOUR
TI - Ghost Reduction for Multiple Angle Sensors Based on Tracking Process by Dual Hypotheses
T2 - IEICE TRANSACTIONS on Communications
SP - 504
EP - 511
AU - Kosuke MARUYAMA
AU - Hiroshi KAMEDA
PY - 2014
DO - 10.1587/transcom.E97.B.504
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E97-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 2014
AB - A ghost reduction algorithm for multiple angle sensors tracking objects under dual hypotheses is proposed. When multiple sensors and multiple objects exist on the same plane, the conventional method is unable to distinguish the real objects and ghosts from all possible pairs of measurement angle vectors. In order to resolve the issue stated above, the proposed algorithm utilizes tracking process considering dual hypotheses of real objects and ghosts behaviors. The proposed algorithm predicts dynamics of all the intersections of measurement angle vector pairs with the hypotheses of real objects and ghosts. Each hypothesis is evaluated by the residuals between prediction data and intersection. The appropriate hypothesis is extracted trough several data sampling. Representative simulation results demonstrate the effectiveness of the proposed algorithm.
ER -
English
