Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Multi-dimensional hough transform based on unscented transform as a method of track-before-detect /
Download
index.pdf
Date
2014
Author
Şahin, Gözde
Metadata
Show full item record
Item Usage Stats
233
views
249
downloads
Cite This
Track-Before-Detect (TBD) is the problem where target state estimation and detection occur simultaneously, and is a suitable method for the detection of low-SNR targets in unthresholded sensor data. In this thesis, a new Multi-Dimensional Hough Transform (MHT) technique based on Unscented Transform is proposed for the detection of dim targets in radar data. MHT is a TBD method that fuses Hough Transform results obtained on (x-t), (y-t) and (x-y) domains in order to detect a constant velocity target. The proposed study models Hough Transform results in (x-t) and (y-t) domains by Gaussians and transforms these Gaussians to (x-y) domain by using Unscented Transform for this purpose. Moreover, the algorithm is modified to make use of the intensity 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 under heavy clutter and eliminate possible false trajectories. The study examines the performance of the proposed algorithm using target existence and estimation accuracy. The algorithm’s susceptibility to clutter and varying SNR levels is also tested in the simulations.
Subject Keywords
Radar.
,
Tracking radar.
,
Hough transform.
,
Target acquisition.
,
Signal processing.
URI
http://etd.lib.metu.edu.tr/upload/12617435/index.pdf
https://hdl.handle.net/11511/23632
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
Multi-Ellipsoidal Extended Target Tracking With Variational Bayes Inference
Tuncer, Barkın; Orguner, Umut; Özkan, Emre (2022-01-01)
In this work, we propose a novel extended target tracking algorithm, which is capable of representing a target or a group of targets with multiple ellipses. Each ellipse is modeled by an unknown symmetric positive-definite random matrix. The proposed model requires solving two challenging problems. First, the data association problem between the measurements and the sub-objects. Second, the inference problem that involves non-conjugate priors and likelihoods which needs to be solved within the recursive fil...
Posterior Cram'er-Rao Lower Bounds for Extended Target Tracking with Random Matrices
Sarıtaş, Elif; Orguner, Umut (2016-07-08)
This paper presents posterior Cram'er-Rao lower bounds (PCRLB) for extended target tracking (ETT) when the extent states of the targets are represented with random matrices. PCRLB recursions are derived for kinematic and extent states taking complicated expectations involving Wishart and inverse Wishart distributions. For some analytically intractable expectations, Monte Carlo integration is used. The bounds for the semi-major and minor axes of the extent ellipsoid are obtained as well as those for the exte...
Interacting multiple model probabilistic data association filter using random matrices for extended target tracking
Özpak, Ezgi; Orguner, Umut; Department of Electrical and Electronics Engineering (2018)
In this thesis, an Interacting Multiple Model – Probabilistic Data Association (IMM-PDA) filter for tracking extended targets using random matrices is proposed. Unlike the extended target trackers in the literature which use multiple alternative partitionings/clusterings of the set of measurements, the algorithm proposed here considers a single partitioning/clustering of the measurement data which makes it suitable for applications with low computational resources. When the IMM-PDA filter uses clustered mea...
Posterior Cramér-Rao lower bounds for extended target tracking with random matrices
Sarıtaş, Elif; Orguner, Umut (2016-08-04)
This paper presents posterior Cramér-Rao lower bounds (PCRLB) for extended target tracking (ETT) when the extent states of the targets are represented with random matrices. PCRLB recursions are derived for kinematic and extent states taking complicated expectations involving Wishart and inverse Wishart distributions. For some analytically intractable expectations, Monte Carlo integration is used. The bounds for the semi-major and minor axes of the extent ellipsoid are obtained as well as those for the exten...
Multi-target particle filter based track before detect algorithms for spawning targets /
Eyili, Mehmet; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2014)
In this work, a Track Before Detect (TBD) approach is proposed for tracking and detection of the spawning targets on the basis of raw radar measurements. The principle of this approach is mainly constructed by multi-model particle filter method. In contrast to the related works in the literature, a novel reduced order dynamic model is introduced and the information about bearing angle derived from the radar measurements is not used in this model to improve the efficiency of the particle filter. Moreover, a ...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
G. Şahin, “Multi-dimensional hough transform based on unscented transform as a method of track-before-detect /,” M.S. - Master of Science, Middle East Technical University, 2014.
