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

Metadata

Show full item record

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

Item Usage Stats

242
views

0
downloads

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

Suggestions

OpenMETU
Core

Improved Multi-Dimensional Hough Transform as a Track-Before-Detect Method Sahin, Gozde; Demirekler, Mübeccel (2014-04-25) This study proposes an improved Multi-Dimensional Hough Transform technique for the detection of low SNR targets (dim targets) in radar data. The proposed Track-Before-Detect technique improves the Multi-Dimensional Hough Transform by limiting the target's maximum velocity and incorporating the SNR values of the targets in the algorithm. In addition, the performance is enhanced by confirming the Hough Transform results with a score-based confirmation algorithm.
Detection of the Weak Targets by Using Multi Dimensional Hough Transform Based Track Before Detect Algorithm Turhan, Hasan Ihsan; Demirekler, Mübeccel (2016-05-19) This study proposes a multi-dimensional Hough transform algorithm that is improved from [1] by detecting weak targets in the high clutter. In the proposed algorithm execution time is reduced by eliminating the measurements considering speed and SNR values before the Hough transform. The skor-based track confirmation algorithm proposed in [1] is improved and tracks that belong to same target are eliminated. The proposed algorithm is tested with real data and results are presented.
A CIRCLE DETECTION APPROACH BASED ON RADON TRANSFORM Okman, O. Erman; Akar, Gözde (2013-05-31) In this paper a novel fast circle detection algorithm is proposed which depends on the spatial properties of the connected components on the image. Two 1-D transforms of each connected component is obtained by taking the Radon Transform of the image for two different directions, which are in fact the integrations of the image through horizontal and vertical directions. Circles are detected using the similarities of detected peaks on the transformed functions and the characteristics of the values in between ...
An embedding technique to determine tau tau backgrounds in proton-proton collision data Sirunyan, A. M.; et. al. (IOP Publishing, 2019-06-01) An embedding technique is presented to estimate standard model ττ backgrounds from data with minimal simulation input. In the data, the muons are removed from reconstructed μμ events and replaced with simulated tau leptons with the same kinematic properties. In this way, a set of hybrid events is obtained that does not rely on simulation except for the decay of the tau leptons. The challenges in describing the underlying event or the production of associated jets in the simulation are avoided. The technique...
An Optimal Radar Detector Threshold Adaptation for Maneuvering Targets in Clutter Aslan, Murat Samil; Saranlı, Afşar (2009-04-11) In this paper, we consider the problem of radar detector threshold optimization for maneuvering targets in clutter In the earlier works, the problem was studied in the context of the probabilistic data association filter (PDAF) for non-maneuvering targets. In this study, we have extended the ideas, which were applied to the PDAF to the interacting multiple model PDAF (IMM-PDAF) for maneuvering targets. The proposed optimization problem and its solution show better results over the traditional approaches in ...

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.