Range parameterized bearings only tracking using particle filter

Download

index.pdf

Date

2012

Author

Arslan, Ali Erkin

Metadata

Show full item record

Item Usage Stats

148
views

45
downloads

In this study, accurate target tracking for bearings-only tracking problem is investigated. A new tracking filter for this nonlinear problem is designed where both range parameterization and Rao-Blackwellized (marginalized) particle filtering techniques are used in a Gaussian mixture formulation to track both constant velocity and maneuvering targets. The idea of using target turn rate in the state equation in such a way that marginalization is possible is elaborated. Addition to nonlinear nature, unobservability is a major problem of bearings-only tracking. Observer trajectory generation to increase the observability of the bearings-only tracking problem is studied. Novel formulation of observability measures based on mutual information between the state and the measurement sequences are derived for the problem. These measures are used as objective functions to improve observability. Based on the results obtained better understanding of the required observer trajectory for accurate bearings-only target tracking is developed.

Subject Keywords

Observers (Control theory)., Trajectory optimization., Bearings (Machinery)., Target practice., Nonlinear systems.

URI

http://etd.lib.metu.edu.tr/upload/12614888/index.pdf
https://hdl.handle.net/11511/22045

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Fully-Automatic Target Detection and Tracking for Real-Time, Airborne Imaging Applications Alkanat, Tunc; Tunali, Emre; Oz, Sinan (2015-03-14) In this study, an efficient, robust algorithm for automatic target detection and tracking is introduced. Procedure starts with a detection phase. Proposed method uses two alternatives for the detection phase, namely maximally stable extremal regions detector and Canny edge detector. After detection, regions of interest are evaluated and eliminated according to their compactness and effective saliency. The detection process is repeated for a predetermined number of pyramid levels where each level processes a...
Particle filter based track before detect algorithm for tracking of dim moving targets Sabuncu, Murat; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2012) In this study Track Before Detect (TBD) approach will be analysed for tracking of dim moving targets. First, a radar setup is presented in order to introduce the radar range equation and signal models. Then, preliminary information is given about particle filters. As the main algorithm of this thesis, a multi-model particle filter method is developed in order to solve the non-linear non-Gaussian Bayesian estimation problem. Probability of target existence and RMS estimation accuracy are defined as the perfo...
Target tracking with input estimation Gazioğlu, Ersen; Demirbaş, Kerim; Department of Electrical and Electronics Engineering (2005) In this thesis, the target tracking problem with input estimation is investigated. The estimation performance of the optimum decoding based smoothing algorithm and a target tracking scheme based on the Kalman filter is compared by performing simulations. The advantages and the disadvantages of these algorithms are presented.
Surface Vessel Tracking in Airborne Infrared Imagery Cakiroglu, Ahmet; Ulusoy, İlkay (2019-01-01) Visual target tracking has been studied for decades and still remains a challenging problem. Ship tracking on infrared images has numerous challenges compared to conventional target tracking such as fast changing of appearance. Rapid appearance change caused by the manoeuvring movement of the target of image acquiring platform, confusion and occlusion caused by the active countermeasures employed by the target and disguise by cooling systems causes the target tracking algorithms to have low performance. In ...
Distributed Target Tracking with Propagation Delayed Measurements Orguner, Umut (2009-07-09) This paper presents a framework for making distributed target tracking under significant signal propagation delays between the target and the sensors. Each sensor considered makes estimation using its own measurements compensating for the involved signal propagation delay using a deterministic sampling based algorithm proposed previously. Since the individual sensor readings might not be enough to localize the target, the sensors have to share their estimates with each other at specific time instants and co...

Citation Formats

A. E. Arslan, “Range parameterized bearings only tracking using particle filter,” Ph.D. - Doctoral Program, Middle East Technical University, 2012.