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Peng Lei, Jun Wang, Jinping Sun Beijing University of Aeronautics and Astronautics IGARSS 2011, Vancouver, Canada July 26, 2011 Radar Micro-Doppler Analysis and Rotation Parameter Estimation for Rigid Targets with Complicated Micro-Motions
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],IGARSS 2011
Introduction ,[object Object],[object Object],IGARSS 2011 mD effect micro-motions attitude dynamics limb/respiratory movement engine vibration/ wheel rotation … micro-motion parameters classification EXPLORE
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],IGARSS 2011
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Spectral Analysis of MD Frequency kinematic equations IGARSS 2011 moments of inertia initial rotation state attitude angles (at any time t ) Rot ( t ) signal model mD echoes constant linear time variant
Spectral Analysis of MD Frequency ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],IGARSS 2011 rotation parameters precession of a gyroscope from http://en.wikipedia.org/wiki/Precession
[object Object],[object Object],[object Object],Spectral Analysis of MD Frequency IGARSS 2011
[object Object],[object Object],[object Object],Spectral Analysis of MD Frequency IGARSS 2011 linear sum of four sinusoidal components
[object Object],Spectral Analysis of MD Frequency IGARSS 2011 ,[object Object],[object Object]
[object Object],[object Object],Estimation Methodology IGARSS 2011 radar mD echoes spectrogram time-frequency sequence spectral estimation rotation parameters Time-frequency analysis (Short Time Fourier Transform) Formation of mD time-frequency sequence Spectral estimation STFT mapping RELAX
[object Object],[object Object],[object Object],[object Object],Estimation Methodology IGARSS 2011 t f g ( t i ) h ( t m , f n ) time frequency two-dimensional (2D) matrix data time amplitude one-dimensional (1D) sampled data t time frequency t f r ( t k ) 1D sequence data
[object Object],[object Object],Estimation Methodology IGARSS 2011 frequency amplitude
[object Object],Simulation Results IGARSS 2011 micro-motion trajectory in 3D space theoretical mD frequency carrier frequency 5 GHz PRF 2 kHz radar-to-target direction (0.578, 0.578, 0.578) moments of inertia (108, 108, 23) kg·m 2 initial rotational velocities (1, 1, 26) rad/s scatterer position (0.4, 0.3, -0.5) m
[object Object],Simulation Results IGARSS 2011 when SNR>13dB, accuracy >98% 1. theoretical values – calculation results 2. ideal values – simulation results under noise-free condition 3. estimation values – Monte-Carlo results at given SNR level
[object Object],Simulation Results IGARSS 2011 when SNR>13dB, accuracy >91%
[object Object],[object Object],[object Object],[object Object],Conclusion IGARSS 2011
IGARSS 2011

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IGARSS2011-1538-Presentation-PPT-File_P.Lei.ppt

  • 1. Peng Lei, Jun Wang, Jinping Sun Beijing University of Aeronautics and Astronautics IGARSS 2011, Vancouver, Canada July 26, 2011 Radar Micro-Doppler Analysis and Rotation Parameter Estimation for Rigid Targets with Complicated Micro-Motions
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Editor's Notes

  1. Here, the “radar” generally refers to the microwave and laser sensors. Although the mD effect is similar to the well-known Doppler phenomenon in theory, the special dynamics, micro-motion, should be our focus in some related research.
  2. It could be represented by this nonlinear least-square fitting problem, as this equation.