Comparative study of three algorithms for estimation of echo parameters in UWB radar module for monitoring of human movements

Abstract The research reported in this paper is related to the ultra-wide-band radar technology that may be employed in care services for elderly and disabled persons. Three algorithms for preprocessing of measurement data from an impulse radar sensor, when applied for such people monitoring, are compared with respect to the uncertainty of estimation of echo parameters. These are: an algorithm based on the maximum-envelope of the measured radar data, an algorithm based on curve-fitting in the spectrum domain of those data, and a modified CLEAN algorithm. Results of the numerical experiments performed on both semi-synthetic data and real-world data, obtained by means of an impulse-radar sensor, are demonstrated.

[1]  Aly E. Fathy,et al.  UWB micro-doppler radar for human gait analysis using joint range-time-frequency representation , 2013, Defense, Security, and Sensing.

[2]  Jian Yang,et al.  A Compact UWB Indoor and Through-Wall Radar with Precise Ranging and Tracking , 2012 .

[3]  Roman Z. Morawski Numerical determination of Marmet’s filter parameters , 1982 .

[4]  B. H. Ahmad,et al.  5.8 GHz microwave Doppler radar for heartbeat detection , 2013, 2013 23rd International Conference Radioelektronika (RADIOELEKTRONIKA).

[5]  Roman Z. Morawski,et al.  Measurement data preprocessing in a radar-based system for monitoring of human movements , 2015 .

[6]  Rafal Brzyski Low power ultrawideband radar device for close range detection of human body and bodily functions , 2015, 2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS).

[7]  O. Celik,et al.  Systematic review of Kinect applications in elderly care and stroke rehabilitation , 2014, Journal of NeuroEngineering and Rehabilitation.

[8]  Marjorie Skubic,et al.  Doppler Radar Fall Activity Detection Using the Wavelet Transform , 2015, IEEE Transactions on Biomedical Engineering.

[9]  Ram M. Narayanan,et al.  Micro-doppler radar classification of human motions under various training scenarios , 2013, Defense, Security, and Sensing.

[10]  J. Högbom,et al.  APERTURE SYNTHESIS WITH A NON-REGULAR DISTRIBUTION OF INTERFEROMETER BASELINES. Commentary , 1974 .

[11]  A. Geurts,et al.  Definition dependent properties of the cortical silent period in upper-extremity muscles, a methodological study , 2014, Journal of NeuroEngineering and Rehabilitation.

[12]  Jian Yang,et al.  Detection of breathing and heartbeat by using a simple UWB radar system , 2014, The 8th European Conference on Antennas and Propagation (EuCAP 2014).

[13]  Xin Li,et al.  A novel through-wall respiration detection algorithm using UWB radar , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[14]  James M. Keller,et al.  Radar walk detection in the apartments of elderly , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[15]  Meng Wu,et al.  Fall Detection Based on Sequential Modeling of Radar Signal Time-Frequency Features , 2013, 2013 IEEE International Conference on Healthcare Informatics.

[16]  Yevhen Yashchyshyn,et al.  Study of detection capability of Novelda impulse transceiver with external RF circuit , 2015, 2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS).