Avian detection and identification with high-resolution radar

被引:0
|
作者
Zhang, Qun [1 ]
Zeng, Yue-sheng [1 ]
He, Yuan-qiao [1 ]
Luo, Ying [1 ]
机构
[1] Air Force Engn Univ, Inst Telecommun Engn, Xian 710077, Peoples R China
来源
2008 IEEE RADAR CONFERENCE, VOLS. 1-4 | 2008年
关键词
bird strike; frequency-stepped chirp signal; micro-Doppler;
D O I
暂无
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Bird strike hazards take place frequently in the world without prediction, destroying the expensive aircrafts, killing the pilots and the passengers, and bringing people disaster and sorrow. The conventional visual techniques don't work at night or on the foggy and rainy days; even the weather radars couldn't identify the birds accurately for its low resolution. In this paper, a novel method of avian detection and identification based on ISAR feature extraction techniques is proposed. The paper mainly discussed some key problems in feature extraction of ISAR targets. The method of imaging and micro-Doppler feature extraction based on frequency-stepped chirp radar is discussed. Parameters of the radar for avian detection and identification are designed. Then, imaging and micro-Doppler feature extraction is applied in avian detection and identification. Finally, some problems to study later are also discussed.
引用
收藏
页码:111 / 116
页数:6
相关论文
共 50 条
  • [41] A Mode-Switchable Photonic Radar System for Aerial LSS Targets Detection and Classification
    Selvi, Amalorpava
    Babu, S. P. K.
    Raja, Arockia Bazil
    IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2025, 61 (02) : 3470 - 3482
  • [42] Target Detection and Classification of Small Drones by Deep Learning on Radar Micro-Doppler
    Bjorklund, Svante
    Wadstromer, Niclas
    2019 INTERNATIONAL RADAR CONFERENCE (RADAR2019), 2019, : 233 - 238
  • [43] Person Identification Based on Fine-Grained Micro-Doppler Signatures and UWB Radar
    He, Yuan
    Guo, Hanbin
    Zhang, Xinqi
    Li, Runlong
    Lang, Yue
    Yang, Yang
    IEEE SENSORS JOURNAL, 2023, 23 (18) : 21421 - 21432
  • [44] Human Detection by Deep Neural Networks Recognizing Micro-Doppler Signals of Radar
    Kwon, Jihoon
    Lee, Seungeui
    Kwak, Nojun
    2018 15TH EUROPEAN RADAR CONFERENCE (EURAD), 2018, : 198 - 201
  • [45] Ballistic missile detection via micro-Doppler frequency estimation from radar return
    Liu, Lihua
    McLernon, Des
    Ghogho, Mounir
    Hu, Weidong
    Huang, Jian
    DIGITAL SIGNAL PROCESSING, 2012, 22 (01) : 87 - 95
  • [46] Research of Target Detection and Classification Techniques Using Millimeter-Wave Radar and Vision Sensors
    Wang, Zhangjing
    Miao, Xianhan
    Huang, Zhen
    Luo, Haoran
    REMOTE SENSING, 2021, 13 (06)
  • [47] Resolving multiple targets with micro-motions based on time-frequency feature with low-resolution radar
    Huang X.-H.
    He X.
    Xin Y.-L.
    Chen Z.-P.
    Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2010, 32 (10): : 2342 - 2347
  • [48] Robust Classification Scheme for Airplane Targets With Low Resolution Radar Based on EMD-CLEAN Feature Extraction Method
    Du, Lan
    Wang, Baoshuai
    Li, Yanbing
    Liu, Hongwei
    IEEE SENSORS JOURNAL, 2013, 13 (12) : 4648 - 4662
  • [49] Radar-Based Fall Detection Using Deep Machine Learning: System Configuration and Performance
    Diraco, Giovanni
    Leone, Alessandro
    Siciliano, Pietro
    SENSORS AND MICROSYSTEMS, 2018, 457 : 257 - 268
  • [50] Heart ID: Human Identification Based on Radar Micro-Doppler Signatures of the Heart Using Deep Learning
    Cao, Peibei
    Xia, Weijie
    Li, Yi
    REMOTE SENSING, 2019, 11 (10)