Human Polarimetric Micro-Doppler

被引:2
作者
Tahmoush, Dave [1 ]
Silvious, Jerry [1 ]
机构
[1] USA, Res Lab, Adelphi, MD 20783 USA
来源
RADAR SENSOR TECHNOLOGY XV | 2011年 / 8021卷
关键词
Radar; micro-Doppler; polarimetric; MODEL;
D O I
10.1117/12.883444
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Modern radars can pick up target motions other than just the principle target Doppler; they pick out the small micro-Doppler variations as well. These can be used to visually identify both the target type as well as the target activity. We model and measure some of the micro-Doppler motions that are amenable to polarimetric measurement. Understanding the capabilities and limitations of radar systems that utilize micro-Doppler to measure human characteristics is important for improving the effectiveness of these systems at securing areas. In security applications one would like to observe humans unobtrusively and without privacy issues, which make radar an effective approach. In this paper we focus on the characteristics of radar systems designed for the estimation of human motion for the determination of whether someone is loaded. Radar can be used to measure the direction, distance, and radial velocity of a walking person as a function of time. Detailed radar processing can reveal more characteristics of the walking human. The parts of the human body do not move with constant radial velocity; the small micro-Doppler signatures are time-varying and therefore analysis techniques can be used to obtain more characteristics. Looking for modulations of the radar return from arms, legs, and even body sway are being assessed by researchers. We analyze these techniques and focus on the improved performance that fully polarimetric radar techniques can add. We perform simulations and fully polarimetric measurements of the varying micro-Doppler signatures of humans as a function of elevation angle and azimuthal angle in order to try to optimize this type of system for the detection of arm motion, especially for the determination of whether someone is carrying something in their arms. The arm is often bent at the elbow, providing a surface similar to a dihedral. This is distinct from the more planar surfaces of the body and allows us to separate the signals from the arm (and knee) motion from the rest of the body. The double-bounce can be measured in polarimetric radar data by measuring the phase difference between HH and VV. Additionally, the cross-pol and co-pol Doppler signatures are analyzed, showing that the HH polarization may perform better on dismounts in open grass.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] UAV Micro-Doppler Signature Analysis
    Herr, Daniel B.
    Kramer, Thomas J.
    Gannon, Zeus
    Tahmoush, Dave
    [J]. 2020 IEEE RADAR CONFERENCE (RADARCONF20), 2020,
  • [22] Micro-Doppler Gesture Recognition using Doppler, Time and Range Based Features
    Ritchie, Matthew
    Jones, Aaron M.
    [J]. 2019 IEEE RADAR CONFERENCE (RADARCONF), 2019,
  • [23] Combined High Range Resolution and Micro-Doppler Analysis of Human Gait
    Cammenga, Z. A.
    Smith, G. E.
    Baker, C. J.
    [J]. 2015 IEEE INTERNATIONAL RADAR CONFERENCE (RADARCON), 2015, : 1038 - 1043
  • [24] Human Micro-Doppler Signature Extraction in the Foliage-penetration Environment
    Zhang, Jun
    Jin, Tian
    He, Yuan
    Qiu, Lei
    Zhou, Zhimin
    [J]. 2016 21ST INTERNATIONAL CONFERENCE ON MICROWAVE, RADAR AND WIRELESS COMMUNICATIONS (MIKON), 2016,
  • [25] Multiple walking human recognition based on radar micro-Doppler signatures
    SUN ZhongSheng
    WANG Jun
    ZHANG YaoTian
    SUN JinPing
    YUAN ChangShun
    BI YanXian
    [J]. ScienceChina(InformationSciences), 2015, 58 (12) : 177 - 189
  • [26] Advanced Radar Micro-Doppler Simulation Environment for Human Motion Applications
    Ishak, Karim
    Appenrodt, Nils
    Dickmann, Juergen
    Waldschmidt, Christian
    [J]. 2019 IEEE RADAR CONFERENCE (RADARCONF), 2019,
  • [27] Parameter Estimation Method of Walking Human Based on Radar Micro-Doppler
    Sun, Zhongsheng
    Wang, Jun
    Sun, Jinping
    Lei, Peng
    [J]. 2017 IEEE RADAR CONFERENCE (RADARCONF), 2017, : 567 - 570
  • [28] Multiple walking human recognition based on radar micro-Doppler signatures
    Sun ZhongSheng
    Wang Jun
    Zhang YaoTian
    Sun JinPing
    Yuan ChangShun
    Bi YanXian
    [J]. SCIENCE CHINA-INFORMATION SCIENCES, 2015, 58 (12) : 1 - 13
  • [29] Human Micro-Doppler Signature Classification in the Presence of a Selection of Jamming Signals
    Dhulashia, Dilan
    Ritchie, Matthew
    Vishwakarma, Shelly
    Chetty, Kevin
    [J]. 2021 IEEE RADAR CONFERENCE (RADARCONF21): RADAR ON THE MOVE, 2021,
  • [30] Detection of moving human micro-Doppler signature in forest environments with swaying tree components by wind
    Kilic, Ozlem
    Garcia-Rubia, Jose M.
    Nghia Tran
    Vinh Dang
    Quang Nguyen
    [J]. RADIO SCIENCE, 2015, 50 (03) : 238 - 248