A Multi-Dimensional Hough Transform Algorithm Based on Unscented Transform as a Track-Before-Detect Method

Date

2014-07-10

Author

Sahin, Gozde
Demirekler, Mübeccel

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this study, a new Multi-Dimensional Hough Transform technique is proposed for the detection of dim targets in radar data. Multi-Dimensional Hough Transform is a Track-Before-Detect method that fuses Hough Transform results obtained on (x-t), (y-t) and (x-y) domains. The proposed study models Hough Transform results in (x-t) and (y-t) domains by Gaussians and transforms these Gaussians to (x-y) domain using Unscented Transform. This improves the computational efficiency significantly without degrading performance. Moreover, the algorithm is modified to make use of the echo amplitude values of the radar data and the prior knowledge of target's maximum speed. Lastly, a score-based track confirmation algorithm is proposed to increase the performance and detect the track location.

Subject Keywords

Track-before-detect, Multi-dimensional Hough transform, Hough transform, Unscented transform, Score-based track confirmation

URI

https://hdl.handle.net/11511/52532

Conference Name

17th International Conference on Information Fusion (FUSION)

Collections

Graduate School of Natural and Applied Sciences, Conference / Seminar

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Citation Formats

G. Sahin and M. Demirekler, “A Multi-Dimensional Hough Transform Algorithm Based on Unscented Transform as a Track-Before-Detect Method,” presented at the 17th International Conference on Information Fusion (FUSION), Salamanca, SPAIN, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52532.