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

Sahin, Gozde
Demirekler, Mübeccel
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.