NDLI: Multisensor track-to-track association for tracks with dependent errors

Content Provider	IEEE Xplore Digital Library
Author	Bar-Shalom, Y. Huimin Chen
Copyright Year	2004
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Connecticut Univ., Storrs, CT, USA (Bar-Shalom, Y.; Huimin Chen)
Abstract	The problem of track-to-track association has been considered until recently in the literature only for pairwise associations. In view of the extensive recent interest in multisensor data fusion, the need to associate simultaneously multiple tracks has arisen. This is due primarily to bandwidth constraints in real systems, where it is not feasible to transmit detailed measurement information to a fusion center but, in many cases, only local tracks. As it has been known in the literature, tracks of the same target obtained from independent sensors are still dependent due to the common process noise. This paper derives the likelihood function for the track-to-track association problem from multiple sources, which forms the basis for the cost function used in a multidimensional assignment algorithm that can solve such a large scale problem where many sensors track many targets. While a recent work derived the likelihood function under the assumption that the track errors are independent, the present paper incorporates the (unavoidable) dependence of these errors.
Starting Page	2674
Ending Page	2679
File Size	165024
Page Count	6
File Format	PDF
ISBN	0780386825
ISSN	01912216
DOI	10.1109/CDC.2004.1428864
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-12-14
Publisher Place	Bahamas
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Target tracking Cost function Multidimensional systems State estimation Estimation error USA Councils Bandwidth Large-scale systems Sensor systems Sensor phenomena and characterization
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Multisensor Track-to-Track Association for Tracks with Dependent Errors (2004)

Performance evaluation of multisensor track-to-track fusion

Track association and fusion with heterogeneous local trackers

Bayesian model selection for multisensor track-to-track association and track fusion

Simulations studies of multisensor track association and fusion methods

State estimation with feedback information in a hybrid multisensor system

Exact multisensor dynamic bias estimation with local tracks

Metrics for Feature-Aided Track Association

Bayesian model selection for multisensor track-to-track.

Multisensor track-to-track association for tracks with dependent errors

Similar Documents

Multisensor Track-to-Track Association for Tracks with Dependent Errors (2004)

Performance evaluation of multisensor track-to-track fusion

Track association and fusion with heterogeneous local trackers

Bayesian model selection for multisensor track-to-track association and track fusion

Simulations studies of multisensor track association and fusion methods

State estimation with feedback information in a hybrid multisensor system

Exact multisensor dynamic bias estimation with local tracks

Metrics for Feature-Aided Track Association

Bayesian model selection for multisensor track-to-track.

Multisensor track-to-track association for tracks with dependent errors