Classification and modeling of human activities using empirical mode decomposition with S-band and millimeter-wave micro-Doppler radars

Dustin P. Fairchild, Ram Mohan Narayanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

The ability to identify human movements can be an important tool in many different applications such as surveillance, military combat situations, search and rescue operations, and patient monitoring in hospitals. This information can provide soldiers, security personnel, and search and rescue workers with critical knowledge that can be used to potentially save lives and/or avoid a dangerous situation. Most research involving human activity recognition is focused on using the Short-Time Fourier Transform (STFT) as a method of analyzing the micro-Doppler signatures. Because of the time-frequency resolution limitations of the STFT and because Fourier transform-based methods are not well-suited for use with non-stationary and nonlinear signals, we have chosen a different approach. Empirical Mode Decomposition (EMD) has been shown to be a valuable time-frequency method for processing non-stationary and nonlinear data such as micro-Doppler signatures and EMD readily provides a feature vector that can be utilized for classification. For classification, the method of a Support Vector Machine (SVMs) was chosen. SVMs have been widely used as a method of pattern recognition due to their ability to generalize well and also because of their moderately simple implementation. In this paper, we discuss the ability of these methods to accurately identify human movements based on their micro-Doppler signatures obtained from S-band and millimeter-wave radar systems. Comparisons will also be made based on experimental results from each of these radar systems. Furthermore, we will present simulations of micro-Doppler movements for stationary subjects that will enable us to compare our experimental Doppler data to what we would expect from an "ideal" movement.

Original languageEnglish (US)
Title of host publicationRadar Sensor Technology XVI
DOIs
StatePublished - Dec 1 2012
EventRadar Sensor Technology XVI - Baltimore, MD, United States
Duration: Apr 23 2012Apr 25 2012

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8361
ISSN (Print)0277-786X

Other

OtherRadar Sensor Technology XVI
CountryUnited States
CityBaltimore, MD
Period4/23/124/25/12

Fingerprint

S band
Millimeter Wave
Doppler
Millimeter waves
millimeter waves
Fourier transforms
Radar systems
Decomposition
decomposition
Decompose
Support vector machines
signatures
Modeling
Short-time Fourier Transform
radar
Patient monitoring
rescue operations
Signature
Radar
Pattern recognition

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Fairchild, D. P., & Narayanan, R. M. (2012). Classification and modeling of human activities using empirical mode decomposition with S-band and millimeter-wave micro-Doppler radars. In Radar Sensor Technology XVI [83610X] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8361). https://doi.org/10.1117/12.922448
Fairchild, Dustin P. ; Narayanan, Ram Mohan. / Classification and modeling of human activities using empirical mode decomposition with S-band and millimeter-wave micro-Doppler radars. Radar Sensor Technology XVI. 2012. (Proceedings of SPIE - The International Society for Optical Engineering).
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Fairchild, DP & Narayanan, RM 2012, Classification and modeling of human activities using empirical mode decomposition with S-band and millimeter-wave micro-Doppler radars. in Radar Sensor Technology XVI., 83610X, Proceedings of SPIE - The International Society for Optical Engineering, vol. 8361, Radar Sensor Technology XVI, Baltimore, MD, United States, 4/23/12. https://doi.org/10.1117/12.922448

Classification and modeling of human activities using empirical mode decomposition with S-band and millimeter-wave micro-Doppler radars. / Fairchild, Dustin P.; Narayanan, Ram Mohan.

Radar Sensor Technology XVI. 2012. 83610X (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8361).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Fairchild DP, Narayanan RM. Classification and modeling of human activities using empirical mode decomposition with S-band and millimeter-wave micro-Doppler radars. In Radar Sensor Technology XVI. 2012. 83610X. (Proceedings of SPIE - The International Society for Optical Engineering). https://doi.org/10.1117/12.922448