Spectrogram-based methods for human identification in single-channel SAR data

被引:0
|
作者
Guerbuez, Sevgi Zubeyde [1 ]
Melvin, William L. [2 ]
Williams, Douglas B. [1 ]
机构
[1] Georgia Inst Technol, Elek & Bilgisayar Muhendisligi Bolumu, Atlanta, GA 30332 USA
[2] Georgia Inst Technol, Georgia Tech Arastrma Enstitusu, Atlanta, GA 30332 USA
来源
2007 IEEE 15TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS, VOLS 1-3 | 2007年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Radar offers unique advantages over other sensors, such as visual or seismic sensors, for human target detection and identification. Radar can operate far away from potential targets, and functions during the daytime as well as nighttime in virtually all weather conditions. In this paper, we examine the problem of human target detection and identification using single-channel synthetic aperture radar (SAR) data. A 12-point human model, together with kinematic equations of motion for each body part, is used to calculate the expected target return and spectrogram. The unique characteristics of the human spectrogram are analysed and used to design a prototype for an automated gender discrimination scheme. Simulation results show a 83.97% detection rate for males and 91.11% detection rate for females. Inherent deficiencies of spectrogram-based methods are discussed. Future work will focus on the development of an alternative solution for overcoming these deficiencies.
引用
收藏
页码:1248 / +
页数:2
相关论文
共 50 条
  • [11] Ground Moving Target Indication Based on Optical Flow in Single-Channel SAR
    Wang, Zhirui
    Sun, Xian
    Diao, Wenhui
    Zhang, Yue
    Yan, Menglong
    Lan, Lan
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2019, 16 (07) : 1051 - 1055
  • [12] Self-denoising method for OCT images with single spectrogram-based deep learning
    Wu, Xiupin
    Gao, Wanrong
    Bian, Haiyi
    OPTICS LETTERS, 2023, 48 (19) : 4945 - 4948
  • [13] Identification of Elephant Rumbles in Seismic Infrasonic Signals Using Spectrogram-Based Machine Learning
    Vidunath, Janitha
    Shamal, Chamath
    Hiroshan, Ravindu
    Gamlath, Udani
    Edussooriya, Chamira U. S.
    Munasinghe, Sudath R.
    APPLIED SYSTEM INNOVATION, 2024, 7 (06)
  • [14] Integration of Automatic Identification System (AIS) Data and Single-Channel Synthetic Aperture Radar (SAR) Images by SAR-Based Ship Velocity Estimation for Maritime Situational Awareness
    Graziano, Maria Daniela
    Renga, Alfredo
    Moccia, Antonio
    REMOTE SENSING, 2019, 11 (19)
  • [15] Simulation of multi-channel SAR raw data based on real single channel SAR data
    Zhang, Huansheng
    Yang, Ruliang
    PROCEEDINGS OF 2006 CIE INTERNATIONAL CONFERENCE ON RADAR, VOLS 1 AND 2, 2006, : 1741 - +
  • [16] Simulation of Multi-channel SAR Raw Data Based on Real Single Channel SAR Data
    Zhang, Huansheng
    Yang, Ruliang
    2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, 2006, : 3055 - 3058
  • [17] Statistical modeling methods of single-channel complex-valued SAR images for ship detection
    Leng X.
    Ji K.
    Xiong B.
    Kuang G.
    Journal of Radars, 2020, 9 (03) : 477 - 496
  • [18] Velocity Estimation of Maritime Targets in Spaceborne Single-Channel SAR images: Methods and Performance Assessment
    Testa, Alejandro
    Morando, Elena
    Pastina, Debora
    Zavagli, Massimo
    Santi, Fabrizio
    Pratola, Chiara
    Corvino, Michela
    2023 24TH INTERNATIONAL RADAR SYMPOSIUM, IRS, 2023,
  • [19] A Stochastic Model of Calcium Puffs Based on Single-Channel Data
    Cao, Pengxing
    Donovan, Graham
    Falcke, Martin
    Sneyd, James
    BIOPHYSICAL JOURNAL, 2013, 105 (05) : 1133 - 1142
  • [20] Inositol trisphosphate receptor and ion channel models based on single-channel data
    Gin, Elan
    Wagner, Larry E.
    Yule, David I.
    Sneyd, James
    CHAOS, 2009, 19 (03)