The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
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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In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
Citations
Cites
Micro-doppler effect in radar: phenomenon, model, and simulation study
Chen, V. C., Li, F., Ho, S.-S., & Wechsler, H. (2006) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2006.1603402 · Cited by 1,697
Self-citationRadar Systems Analysis and Design Using MATLAB
Mahafza, B. R. (2000) · Chapman & Hall/CRC eBooks · doi:10.1201/9781584888543 · Cited by 722
Time-Frequency Transforms for Radar Imaging and Signal Analysis
Chen, V. C., & Ling, H. (2002) · Cited by 711
Self-citationA global human walking model with real-time kinematic personification
Boulic, R., Magnenat‐Thalmann, N., & Thalmann, D. (1990) · The Visual Computer · doi:10.1007/bf01901021 · Cited by 504
Human walking estimation with radar
van Dorp, P., & Groen, F. C. A. (2003) · IEE Proceedings - Radar Sonar and Navigation · doi:10.1049/ip-rsn:20030568 · Cited by 262
Analysis of radar micro-Doppler with time-frequency transform
Chen, V. C. (2002) · IEEE Workshop on Statistical Signal and Array Processing · doi:10.1109/ssap.2000.870167 · Cited by 252
Self-citationElectromagnetic fields in the presence of rotating bodies
Bladel, J. V. (1976) · Proceedings of the IEEE · doi:10.1109/proc.1976.10111 · Cited by 188
Scattering by linearly vibrating objects
Kleinman, R. E., & Mack, R. B. (1979) · IRE Transactions on Antennas and Propagation · doi:10.1109/tap.1979.1142085 · Cited by 60
Time-Varying Doppler Analysis of Electromagnetic Backscattering from Rotating Objects
Chen, V. C., Lin, C.-T., & Pala, W. P. (2006) · doi:10.1109/radar.2006.1631896 · Cited by 27
Self-citationScattering by moving bodies: The quasi stationary approximation
Cooper, J. M., & Wilcox, C. H. (1980) · Mathematical Methods in the Applied Sciences · doi:10.1002/mma.1670020202 · Cited by 17
Trindade, M. A., & Sampaio, R. (2001) · Journal of the Brazilian Society of Mechanical Sciences · doi:10.1590/s0100-73862001000100005 · Cited by 14
Research works printed but not linked: 4
- Trindade, 2001, 23, 49
- Geisheimer, 2001, IEEE Asilomar Conference on Signal, Systems and Computers, 1, 834
- Geisheimer, 2002, Proc. SPIE on Radar Technology
- Chen, 2007, IEEE 2007 Int. Geoscience and Remote Sensing Symp. (IGARSS)
Cited by
Sorted by citations
Radar and RGB-Depth Sensors for Fall Detection: A Review
Cippitelli, E., Fioranelli, F., Gambi, E., & Spinsante, S. (2017) · IEEE Sensors Journal · doi:10.1109/jsen.2017.2697077 · Cited by 198
Ding, C., Hong, H., Zou, Y., Chu, H., Zhu, X., Fioranelli, F., Kernec, J. L., & Li, C. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2908758 · Cited by 185
Chen, X., Guan, J., Bao, Z., & He, Y. (2013) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2013.2246574 · Cited by 175
Chen, Z., Li, G., Fioranelli, F., & Griffiths, H. (2018) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2018.2806940 · Cited by 157
Fioranelli, F., Ritchie, M., & Griffiths, H. (2015) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2015.2439393 · Cited by 149
Metadata
- 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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