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Using Micro-Doppler radar signals for human gait detection
Thesis (MScEng)--Stellenbosch University, 2014.
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2014
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| _version_ | 1867614054838697984 |
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| access_status_str | Open Access |
| author | Alzogaiby, Adel |
| author2 | Van Rooyen, G-J. |
| author_browse | Alzogaiby, Adel Van Rooyen, G-J. |
| author_facet | Van Rooyen, G-J. Alzogaiby, Adel |
| author_sort | Alzogaiby, Adel |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MScEng)--Stellenbosch University, 2014. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/86652 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:45:56.159Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/86652 Using Micro-Doppler radar signals for human gait detection Alzogaiby, Adel Van Rooyen, G-J. Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Doppler radar Dissertations -- Electrical and electronic engineering Gait in humans Detectors Radar targets Tracking radar Image systems UCTD Theses -- Electrical and electronic engineering Thesis (MScEng)--Stellenbosch University, 2014. ENGLISH ABSTRACT: This work entails the development and performance analysis of a human gait detection system based on radar micro-Doppler signals. The system consists of a tracking functionality and a target classifier. Target micro-Doppler signatures are extracted with Short-Time Fourier Transform (STFT) based spectrogram providing a high-resolution signatures with the radar that is used. A feature extraction mechanism is developed to extract six features from the signature and an artificial neural network (A-NN) based classifier is designed to carry out the classification process. The system is tested on real X-band radar data of human subjects performing six activities. Those activities are walking and speed walking, walking with hands in pockets, marching, running, walking with a weapon, and walking with arms swaying. The multiclass classifier was designed to discriminate between those activities. High classification accuracy of 96% is demonstrated. AFRIKAANSE OPSOMMING: Hierdie werk behels die ontwikkeling, en analise van werksverrigting, van ’n menslike stapdetekor gebaseer op radar-mikrodoppleranalise. Die stelsel bestaan uit ’n teikenvolger en -klassifiseerder. Die mikrodoppler-kenmerke van ’n teiken word met behulp van die korttyd-Fourier-transform onttrek, en verskaf hoe-resolusie-kenmerke met die radar wat vir die implementering gebruik word. ’n Kenmerkontrekkingstelsel is ontwikkel om ses kenmerke vanuit die spektrogram te onttrek, en ’n kunsmatige neurale netwerk word as klassifiseerder gebruik. Die stelsel is met ’n X-band radar op werklike menslike beweging getoets, terwyl vrywilligers ses aktiwiteite uitgevoer het: loop, loop (hand in die sakke), marsjeer, hardloop, loop met ’n wapen, loop met arms wat swaai. Die multiklas-klassifiseerder is ontwerp om tussen hierdie aktiwiteite te onderskei. ’n Hoe klassifiseringsakkuraatheid van 96% word gedemonstreer. 2014-04-16T17:31:02Z 2014-04-16T17:31:02Z 2014-04 Thesis http://hdl.handle.net/10019.1/86652 en_ZA Stellenbosch University xiv, 83 p. : ill. application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Doppler radar Dissertations -- Electrical and electronic engineering Gait in humans Detectors Radar targets Tracking radar Image systems UCTD Theses -- Electrical and electronic engineering Alzogaiby, Adel Using Micro-Doppler radar signals for human gait detection |
| title | Using Micro-Doppler radar signals for human gait detection |
| title_full | Using Micro-Doppler radar signals for human gait detection |
| title_fullStr | Using Micro-Doppler radar signals for human gait detection |
| title_full_unstemmed | Using Micro-Doppler radar signals for human gait detection |
| title_short | Using Micro-Doppler radar signals for human gait detection |
| title_sort | using micro doppler radar signals for human gait detection |
| topic | Doppler radar Dissertations -- Electrical and electronic engineering Gait in humans Detectors Radar targets Tracking radar Image systems UCTD Theses -- Electrical and electronic engineering |
| url | http://hdl.handle.net/10019.1/86652 |
| work_keys_str_mv | AT alzogaibyadel usingmicrodopplerradarsignalsforhumangaitdetection |