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

Conference paper (2020)

Authors

Fawei Yang Beijing Institute of Technology
Julien Le Kernec University of Glasgow
F. Fioranelli Microwave Sensing, Signals & Systems - EEMCS
Quanhua Liu Beijing Institute of Technology
Research Group
Microwave Sensing, Signals & Systems (EEMCS) (TU Delft)
Copyright: © 2020 Fawei Yang, Julien Le Kernec, F. Fioranelli, Quanhua Liu
DOI: https://doi.org/10.1049/icp.2021.0839
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Published Date

2020

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Microwave Sensing, Signals & Systems

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.

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