Doppler signatures of radar backscattering from objects with micro motions
Abstract
Radar backscattering from objects with micro-motions is subject to Doppler modulations that help determine dynamic properties of objects and provide useful information about the objects. Doppler modulations represented by joint time–frequency analysis provide useful time-varying Doppler characteristics and, thus, add additional time-dimension information to exploit motion characteristics. The author discusses how to simulate radar backscattering from objects with rigid body motions and objects with non-rigid body motions, and how to analyse, interpret and characterise Doppler signatures of objects that undergo these micro-motions. Precession heavy top and human locomotion are used as examples of rigid and non-rigid body motions, respectively. Radar micro-Doppler signatures derived from these motions illustrate the potential of the joint time–frequency analysis for exploiting kinetic and dynamic properties of objects.
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The embedded application of the millimeter-wave (mmW) radar-based human activity classification applies an acceleration method of the convolutional neural network (CNN) on the FPGA hardware.
“The embedded application of the millimeter-wave (mmW) radar-based human activity classification applies an acceleration method of the convolutional neural network (CNN) on the FPGA hardware.”
From Embedded Intelligence on FPGA: Survey, Applications and Challenges (2021) · cites this paper as [74]
The characterization of time-frequency is used to represent the human micro-Doppler (mD) signals, where micromotions of targets causes the frequency modulation in radar echoes.
“The characterization of time-frequency is used to represent the human micro-Doppler (mD) signals, where micromotions of targets causes the frequency modulation in radar echoes.”
From Embedded Intelligence on FPGA: Survey, Applications and Challenges (2021) · cites this paper as [74]
The mmW radar is appropriate to be used due to the short wavelength where it benefits the mD measurement in time-frequency domains by causing wide dynamic range of mD frequency corresponding to human gait patterns.
“The mmW radar is appropriate to be used due to the short wavelength where it benefits the mD measurement in time-frequency domains by causing wide dynamic range of mD frequency corresponding to human gait patterns.”
From Embedded Intelligence on FPGA: Survey, Applications and Challenges (2021) · cites this paper as [74]
Human activity classification makes use of the time-frequency that representation of mD signals because of the uniqueness for different targets with micromotions.
“Human activity classification makes use of the time-frequency that representation of mD signals because of the uniqueness for different targets with micromotions [74].”
From Embedded Intelligence on FPGA: Survey, Applications and Challenges (2021) · cites this paper as [74]
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Zenaldin, M., & Narayanan, R. M. (2015) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2176760 · Cited by 4 · see citing works
Research on micro-motion modulation characteristics of multi-rotor aircraft's rotors
Chen, Y., Shao-dong, L., & Yang, J. (2016) · CIE International Conference on Radar (RADAR) · doi:10.1109/radar.2016.8059201 · Cited by 3 · see citing works
A Fast Bistatic ISAR Imaging Approach for Rapidly Spinning Targets via Exploiting SAR Technique
Yang, Z., Li, D., Tan, X., Liu, H., & Liao, G. (2020) · Remote Sensing · doi:10.3390/rs12132077 · Cited by 3 · see citing works
An Adaptive Filtering Algorithm Based on Range-Doppler Information Guidance
Li, Z., Zhang, J., Li, B., & Yu, J. (2023) · IEEE Access · doi:10.1109/access.2023.3344631 · Cited by 3 · see citing works
- Authors
- Chen, V. C.
- Affiliations
- United States Naval Research Laboratory (US)
- Corresponding author
- Chen, V.C.
- Venue
- IET Signal Processing
- Published
- 2008-09-04
- Volume
- 2
- Issue
- 3
- Pages
- 291-300
- ISSN
- 1751-9675 (ISSN-L)
- 1751-9683
- OpenAlex
- W2128331885
- Cited by
- 146
- References
- 11
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 4 · 2023: 8 · 2022: 11 · 2021: 9 · 2020: 11 · 2019: 11 · 2018: 8 · 2017: 12 · 2016: 14 · 2015: 10 · 2014: 8 · 2013: 10 · 2012: 10
- FWCI
- 9.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IET Signal Processing (publishedVersion)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Advanced SAR Imaging Techniques
- Physical Sciences › Engineering › Aerospace Engineering › Radar Systems and Signal Processing
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Ocean Waves and Remote Sensing
- Keywords
- radar micro-Doppler signatures, radar backscatter, micromotion, time-frequency analysis, rigid body motion, human locomotion, Doppler modulation, radar target characterization
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