Multi-dimensional hough transform based on unscented transform as a method of track-before-detect /

Şahin, Gözde
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.


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...
Multitarget tracking performance metric: deficiency aware subpattern assignment
Oksuz, Kemal; CEMGİL, ALİ TAYLAN (2018-03-01)
Multitarget tracking is a sequential estimation problem where conditioned on noisy sensor measurements, state variables of several targets need to be estimated recursively. In this study, the authors propose a novel performance measure for multitarget tracking named as Deficiency Aware Subpattern Assignment (DASA), that can be used to consistently compare algorithms in a broad spectrum of formulations ranging from conventional data association methods to random finite set based multitarget tracking algorith...
Target localization methods for frequency - only MIMO radar
Kalkan, Yılmaz; Baykal, Buyurman; Department of Electrical and Electronics Engineering (2012)
This dissertation is focused on developing the new target localization and the target velocity estimation methods for frequency-only multi-input, multi-output (MIMO) radar systems with widely separated antennas. If the frequency resolutions of the transmitted signals are enough, only the received frequencies and the Doppler shifts can be used to find the position of the target. In order to estimate the position and the velocity of the target, most multistatic radars or radar networks use multiple independen...
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...
Citation Formats
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.