Target Discrimination Against Clutter Based on Unsupervised Clustering and Sequential Monte Carlo Tracking

Target Discrimination Against Clutter Based on Unsupervised Clustering and Sequential Monte Carlo Tracking

abstract: The radar performance of detecting a target and estimating its parameters can deteriorate rapidly in the presence of high clutter. This is because radar measurements due to clutter returns can be falsely detected as if originating from the actual target. Various data association methods...

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Bibliographic Details
Other Authors: Freeman, Matthew Gregory (Author)
Format: Dissertation
Language:English
Published: 2016
Subjects:
Electrical engineering
Systems science
Clutter
Machine Learning
Radar
Sequential Monte Carlo Methods
Target Tracking
Unsupervised Clustering
Online Access:http://hdl.handle.net/2286/R.I.41269

Internet

http://hdl.handle.net/2286/R.I.41269

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