liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
On Information Measures based on Particle Mixture for Optimal Bearings-only Tracking
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2009 (English)Report (Other academic)
Abstract [en]

In this work we consider a target tracking scenario where a moving observer with a bearings-only sensor is tracking a target. The tracking performance is highly dependent on the trajectory of the sensor platform, and the problem is to determine how it should maneuver for optimal tracking performance.The problem is considered as a stochastic optimal control problem and two sub-optimal control strategies are presented based on the Information filter and the determinant of the information matrix as the optimization objective. Using the determinant of the information matrix as an objective function in the planning problem is equivalent to using differential entropy of the posterior target density when it is Gaussian. For the non-Gaussian case, an approximation of the differential entropy of a density represented by a particle mixture is proposed. Furthermore, a gradient approximation of the differential entropy is derived and used in a stochastic gradient search algorithm applied to the planning problem.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2009. , 17 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2884
Keyword [en]
Bearings-only tracking, Particle filter, Differential entropy
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-55839ISRN: LiTH-ISY-R-2884OAI: oai:DiVA.org:liu-55839DiVA: diva2:316700
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-10-02Bibliographically approved
In thesis
1. Tracking and Planning for Surveillance Applications
Open this publication in new window or tab >>Tracking and Planning for Surveillance Applications
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Vision and infrared sensors are very common in surveillance and security applications, and there are numerous examples where a critical infrastructure, e.g. a harbor, an airport, or a military camp, is monitored by video surveillance systems. There is a need for automatic processing of sensor data and intelligent control of the sensor in order to obtain efficient and high performance solutions that can support a human operator. This thesis considers two subparts of the complex sensor fusion system; namely target tracking and sensor control.The multiple target tracking problem using particle filtering is studied. In particular, applications where road constrained targets are tracked with an airborne video or infrared camera are considered. By utilizing the information about the road network map it is possible to enhance the target tracking and prediction performance. A dynamic model suitable for on-road target tracking with a camera is proposed and the computational load of the particle filter is treated by a Rao-Blackwellized particle filter. Moreover, a pedestrian tracking framework is developed and evaluated in a real world experiment. The exploitation of contextual information, such as road network information, is highly desirable not only to enhance the tracking performance, but also for track analysis, anomaly detection and efficient sensor management. Planning for surveillance and reconnaissance is a broad field with numerous problem definitions and applications. Two types of surveillance and reconnaissance problems are considered in this thesis. The first problem is a multi-target search and tracking problem. Here, the task is to control the trajectory of an aerial sensor platform and the pointing direction of its camera to be able to keep track of discovered targets and at the same time search for new ones. The key to successful planning is a measure that makes it possible to compare different tracking and searching tasks in a unified framework and this thesis suggests one such measure. An algorithm based on this measure is developed and simulation results of a multi-target search and tracking scenario in an urban area are given. The second problem is aerial information exploration for single target estimation and area surveillance. In the single target case the problem is to control the trajectory of a sensor platform with a vision or infrared camera such that the estimation performance of the target is maximized. The problem is treated both from an information filtering and from a particle filtering point of view. In area exploration the task is to gather useful image data of the area of interest by controlling the trajectory of the sensor platform and the pointing direction of the camera. Good exploration of a point of interest is characterized by several images from different viewpoints. A method based on multiple information filters is developed and simulation results from area and road exploration scenarios are presented.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2012. 252 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1432
Keyword
target tracking, sensor control, planning, surveillance, vision sensor
National Category
Control Engineering Signal Processing
Identifiers
urn:nbn:se:liu:diva-76883 (URN)978-91-7519-941-2 (ISBN)
Public defence
2012-06-07, Signalen, Hus B, Campus Valla, Linköping universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2012-04-23 Created: 2012-04-23 Last updated: 2012-05-04Bibliographically approved

Open Access in DiVA

fulltext(528 kB)160 downloads
File information
File name FULLTEXT01.pdfFile size 528 kBChecksum SHA-512
e46381c1c7154f5df55776c314a924fe786e97b1c07a986a64d0170c9e83a8512118598e7bb0433e676b1726179d7e2a0503484fdfa2ac41236e9047c92e1eb6
Type fulltextMimetype application/pdf

Authority records BETA

Skoglar, PerOrguner, UmutGustafsson, Fredrik

Search in DiVA

By author/editor
Skoglar, PerOrguner, UmutGustafsson, Fredrik
By organisation
Automatic ControlThe Institute of Technology
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 160 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 165 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf