Progress and Prospects of Radar Target Detection and Recognition Technology for Flying Birds and Unmanned Aerial Vehicles

Flying birds and Unmanned Aerial Vehicles (UAVs) are typical “low, slow, and small” targets with low observability. The need for effective monitoring and identification of these two targets has become urgent and must be solved to ensure the safety of air routes and urban areas. There are many types...

Full description

Saved in:
Bibliographic Details
Published inJournal of radars = Lei da xue bao Vol. 9; no. 5; pp. 803 - 827
Main Authors Xiaolong CHEN, Weishi CHEN, Yunhua RAO, Yong HUANG, Jian GUAN, Yunlong DONG
Format Journal Article
LanguageChinese
English
Published China Science Publishing & Media Ltd. (CSPM) 01.10.2020
Subjects
deep learning
features extraction
flying bird and unmanned aerial vehicle (uav) target
micro-doppler
radar target detection
target recognition
Online AccessGet full text

Cover

More Information
Summary:Flying birds and Unmanned Aerial Vehicles (UAVs) are typical “low, slow, and small” targets with low observability. The need for effective monitoring and identification of these two targets has become urgent and must be solved to ensure the safety of air routes and urban areas. There are many types of flying birds and UAVs that are characterized by low flying heights, strong maneuverability, small radar cross-sectional areas, and complicated detection environments, which are posing great challenges in target detection worldwide. “Visible (high detection ability) and clear-cut (high recognition probability)” methods and technologies must be developed that can finely describe and recognize UAVs, flying birds, and “low-slow-small” targets. This paper reviews the recent progress in research on detection and recognition technologies for rotor UAVs and flying birds in complex scenes and discusses effective detection and recognition methods for the detection of birds and drones, including echo modeling and recognition of fretting characteristics, the enhancement and extraction of maneuvering features in ubiquitous observation mode, distributed multi-view features fusion, differences in motion trajectories, and intelligent classification via deep learning. Lastly, the problems of existing research approaches are summarized, and we consider the future development prospects of target detection and recognition technologies for flying birds and UAVs in complex scenarios.
ISSN:2095-283X
DOI:10.12000/JR20068