Abstract
Comparison of two different signal processing techniques, i.e., fast Fourier transform (FFT) and Hilbert–Huang transform (HHT) is carried out to detect breathing frequency of a human target hiding behind a wall. Experimental setup with the help of vector network analyzer (VNA) and antenna is used to collect data. After obtaining the location of breathing signal using standard deviation (SD), breathing frequency is detected by FFT and HHT methods. It is observed that values of breathing frequency obtained in the results are in the acceptable range and HHT-based method produces less harmonic distortions than FFT method.
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Acknowledgments
We would like to thank UGC, New Delhi, Govt. of India, for financial support under major research project (MRP F.No. 43-306/2014) (SR) dated 05 Sep, 2015.
The authors would like to thank Head of Department Prof. Dr. N. P. Jawarkar; Principal of the institute, Dr. H. B. Nanvala; and Management, Janata Shikshan Prasarak Mandal and Pusad, for providing facilities and encouragement.
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Gaikwad, A.N. (2020). Comparison of Different Signal Processing Techniques Used for Extraction of Breathing Frequency of Human Being Hidden Behind a Wall. In: Iyer, B., Deshpande, P., Sharma, S., Shiurkar, U. (eds) Computing in Engineering and Technology. Advances in Intelligent Systems and Computing, vol 1025. Springer, Singapore. https://doi.org/10.1007/978-981-32-9515-5_1
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DOI: https://doi.org/10.1007/978-981-32-9515-5_1
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