Micro-Doppler parameter estimation from a fraction of the period

被引:23
|
作者
Thayaparan, T. [1 ]
Stankovic, L. J. [2 ]
Dakovic, M. [2 ]
Popovic, V. [2 ]
机构
[1] Def R&D Canada Ottawa, Ottawa, ON K1A 0Z4, Canada
[2] Univ Montenegro, Podgorica 81000, Montenegro
关键词
FEATURE-EXTRACTION; TARGETS;
D O I
10.1049/iet-spr.2009.0093
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Radar micro-Doppler (m-D) signatures are of great potential for identifying properties of unknown targets. All the techniques developed for extracting m-D features for the past decade rely primarily on the assumption that the time series of the signal contains at least one oscillation or more during the coherent integration time or imaging time. However, many applications in real-world scenarios involve short duration signals and often require the detection and the estimation of m-D characteristics. Short duration signals may contain only a fraction of an oscillation. In this study, the authors develop two techniques to estimate the m-D parameters from a fraction of the period. In these scenarios, the coherent integration will cover only 1/4 and 1/2 of the oscillation. The performance of the proposed methods are evaluated using both synthetic and experimental data.
引用
收藏
页码:201 / 212
页数:12
相关论文
共 50 条
  • [41] Genetic algorithm for rigid body reconstruction after micro-Doppler removal in the radar imaging analysis
    Stankovic, LJubisa
    Popovic-Bugarin, Vesna
    Radenovic, Filip
    SIGNAL PROCESSING, 2013, 93 (07) : 1921 - 1932
  • [42] Time-frequency signatures of micro-Doppler phenomenon for feature extraction
    Chen, VC
    Lipps, R
    WAVELET APPLICATIONS VII, 2000, 4056 : 220 - 226
  • [43] Discrimination Method of Ship and Corner Reflector Based on Micro-Doppler Feature
    Tao, Zhiyu
    Fu, Qiang
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING, INFORMATION SCIENCE & APPLICATION TECHNOLOGY (ICCIA 2016), 2016, 56 : 324 - 329
  • [44] Multiple walking human recognition based on radar micro-Doppler signatures
    Sun ZhongSheng
    Wang Jun
    Zhang YaoTian
    Sun JinPing
    Yuan ChangShun
    Bi YanXian
    SCIENCE CHINA-INFORMATION SCIENCES, 2015, 58 (12) : 1 - 13
  • [45] SEPARATION OF MULTIPLE MICRO-DOPPLER COMPONENTS VIA PARAMETRIC SPARSE RECOVERY
    Li, Gang
    Zhang, Rui
    Rao, Wei
    Wang, Xiqin
    2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2013, : 2978 - 2981
  • [46] Micro-Doppler feature extraction of micro-rotor UAV under the background of low SNR
    He, Weikun
    Sun, Jingbo
    Zhang, Xinyun
    Liu, Zhenming
    JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2022, 33 (06) : 1127 - 1139
  • [47] Continuous Human Motion Recognition Using Micro-Doppler Signatures in the Scenario With Micro Motion Interference
    Zhao, Running
    Ma, Xiaolin
    Liu, Xinhua
    Li, Fangmin
    IEEE SENSORS JOURNAL, 2021, 21 (04) : 5022 - 5034
  • [48] Extraction of Global and Local Micro-Doppler Signature Features From FMCW Radar Returns for UAV Detection
    Oh, Beom-Seok
    Lin, Zhiping
    IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2021, 57 (02) : 1351 - 1360
  • [49] A UAV classification system based on FMCW radar micro-Doppler signature analysis
    Oh, Beom-Seok
    Guo, Xin
    Lin, Zhiping
    EXPERT SYSTEMS WITH APPLICATIONS, 2019, 132 : 239 - 255
  • [50] Separation of micro-Doppler signals based on time frequency filter and Viterbi algorithm
    Li, Po
    Wang, De-Chun
    Wang, Lu
    SIGNAL IMAGE AND VIDEO PROCESSING, 2013, 7 (03) : 593 - 605