Shape feature aided target detection method for micro-drone surveillance radar

Fawei Yang, Julien Le Kernec, Francesco Fioranelli, Quanhua Liu*

*Corresponding author for this work

Research output: Contribution to conferencePaperScientificpeer-review

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Abstract

This paper presents a shape feature aided target detection method for micro-drone surveillance radar in order to mitigate the false alarms caused by the ground clutter. The method consists of a segmentation threshold selection method based on target measurements and a shape-feature extraction method based on Hu moments. Then the performance of the proposed method is verified experimentally using a real radar system. Field experiment using DJI phantom 3 is conducted, and the measured data is analysed. The results show that although there exist some limitations, the proposed method has good performance on eliminating the false alarms caused by the strong ground clutter in micro-drone detection and improving the target tracking accuracy.

Original languageEnglish
Pages390-395
Number of pages6
DOIs
Publication statusPublished - 2020
EventIET International Radar Conference 2020, IET IRC 2020 - Virtual, Online
Duration: 4 Nov 20206 Nov 2020

Conference

ConferenceIET International Radar Conference 2020, IET IRC 2020
CityVirtual, Online
Period4/11/206/11/20

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Feature aided
  • Micro-drone detection
  • Shape feature extraction

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