Title page for E-project-101608-152650

Project Type MQP

Submission date 2008-10-16

Authors
Matthew J Connor, ECE
Kathleen L Haas, MA
Alexander Volfson, MAC

URN E-project-101608-152650

Center MIT Lincoln Laboratory

Sponsor MIT Lincoln Laboratory

Title Multiple Target Tracking

Advisors
Clancy, Edward A., EE
Abraham, Jon P, MA

Availability unrestricted

Abstract
Due to radar's range measurement accuracy, Range Time plots are used to represent radar data. When objects' tracks cross on a Range Time plot, it is uncertain which track belongs to which target. An analysis of the frequency and angle of these crossings was performed. Mathematical analysis concluded that in certain situations, only one type of crossing can result. Further Monte Carlo simulations were used to study these crossing statistics in other situations.
In addition, it was examined how well targets could be tracked through an individual crossing. The probabilities of correct track association were calculated as a function of a variety of factors. Given our models and assumptions, sensor fusion of Range Time and Range Doppler analysis substantially improved crossing classification.

Files
Group31Final.pdf

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Project Type	MQP
Submission date	2008-10-16
Authors	Matthew J Connor, ECE Kathleen L Haas, MA Alexander Volfson, MAC
URN	E-project-101608-152650
Center	MIT Lincoln Laboratory
Sponsor	MIT Lincoln Laboratory
Title	Multiple Target Tracking
Advisors	Clancy, Edward A., EE Abraham, Jon P, MA
Availability	unrestricted
Abstract Due to radar's range measurement accuracy, Range Time plots are used to represent radar data. When objects' tracks cross on a Range Time plot, it is uncertain which track belongs to which target. An analysis of the frequency and angle of these crossings was performed. Mathematical analysis concluded that in certain situations, only one type of crossing can result. Further Monte Carlo simulations were used to study these crossing statistics in other situations. In addition, it was examined how well targets could be tracked through an individual crossing. The probabilities of correct track association were calculated as a function of a variety of factors. Given our models and assumptions, sensor fusion of Range Time and Range Doppler analysis substantially improved crossing classification.
Files	Group31Final.pdf