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Human and animal classification using Doppler radar
Dissertation (MEng)--University of Pretoria, 2017.
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| Other Authors: | |
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2018
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| _version_ | 1867613475583295488 |
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| access_status_str | Open Access |
| author2 | De Villiers, Johan Pieter |
| author_browse | De Villiers, Johan Pieter |
| author_facet | De Villiers, Johan Pieter |
| collection | Thesis |
| dc_rights_str_mv | © 2018 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MEng)--University of Pretoria, 2017. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/66252 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:36:44.480Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/66252 Human and animal classification using Doppler radar De Villiers, Johan Pieter vaneeden.willem@gmail.com Van Eeden, Willem Daniel UCTD Radar Classification Doppler Hidden Markov models (HMM) Gaussian mixture models (GMM) Dissertation (MEng)--University of Pretoria, 2017. South Africa is currently struggling to deal with a significant poaching and livestock theft problem. This work is concerned with the detection and classification of ground based targets using radar micro- Doppler signatures to aid in the monitoring of borders, nature reserves and farmlands. The research starts of by investigating the state of the art of ground target classification. Different radar systems are investigated with respect to their ability to classify targets at different operating frequencies. Finally, a Gaussian Mixture Model Hidden Markov Model based (GMM-HMM) classification approach is presented and tested in an operational environment. The GMM-HMM method is compared to methods in the literature and is shown to achieve reasonable (up to 95%) classification accuracy, marginally outperforming existing ground target classification methods. Electrical, Electronic and Computer Engineering MEng Unrestricted 2018-08-17T09:42:49Z 2018-08-17T09:42:49Z 2005/03/18 2017 Dissertation Van Eeden, WD 2017, Human and animal classification using Doppler radar, MEng Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/66252> A2018 http://hdl.handle.net/2263/66252 en © 2018 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Radar Classification Doppler Hidden Markov models (HMM) Gaussian mixture models (GMM) Human and animal classification using Doppler radar |
| title | Human and animal classification using Doppler radar |
| title_full | Human and animal classification using Doppler radar |
| title_fullStr | Human and animal classification using Doppler radar |
| title_full_unstemmed | Human and animal classification using Doppler radar |
| title_short | Human and animal classification using Doppler radar |
| title_sort | human and animal classification using doppler radar |
| topic | UCTD Radar Classification Doppler Hidden Markov models (HMM) Gaussian mixture models (GMM) |
| url | http://hdl.handle.net/2263/66252 |