Fast Living-Body Localization Algorithm for MIMO Radar in Multipath Environment

A fast living-body localization algorithm using time-differential channel suitable for multipath environments is introduced. In this method, a time-differential channel is calculated from the difference among the observed channels that correspond to known biological activities such as respiration and heartbeat. The living-body locations are estimated by applying 2-D multiple signal classification to the correlation matrix calculated from the time-differential channels. Experiments were carried out in an indoor environment, and the results show that the proposed localization algorithm could well estimate multiple device-free living-bodies simultaneously. The experimental results demonstrate that the locations of up to three persons could be estimated faster, within a few seconds, and more accurately than the conventional method. One, two or three targets yield 90% values of localization errors of 0.23, 0.41, and 1.29 m, respectively.

[1]  Naoki Honma,et al.  Localizing multiple target using bistatic MIMO radar in multi-path environment , 2014, 2014 IEEE International Workshop on Electromagnetics (iWEM).

[2]  Naoki Honma,et al.  Experimental Evaluation of Estimating Living-Body Direction Using Array Antenna for Multipath Environment , 2014, IEEE Antennas and Wireless Propagation Letters.

[3]  Yide Wang,et al.  Polynomial root finding technique for joint DOA DOD estimation in bistatic MIMO radar , 2010, Signal Process..

[4]  T. Ohira,et al.  Reactance domain MUSIC algorithm for electronically steerable parasitic array radiator , 2004, IEEE Transactions on Antennas and Propagation.

[5]  Rob Miller,et al.  3D Tracking via Body Radio Reflections , 2014, NSDI.

[6]  Takashi Miwa,et al.  Localization of Living-Bodies Using Single-Frequency Multistatic Doppler Radar System , 2009, IEICE Trans. Commun..

[7]  Naoki Honma,et al.  Localizing living body using bistatic MIMO radar in multi-path environment , 2014, The 8th European Conference on Antennas and Propagation (EuCAP 2014).

[8]  P. Stoica,et al.  MIMO Radar Signal Processing , 2008 .

[9]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[10]  Fadel Adib,et al.  Multi-Person Motion Tracking via RF Body Reflections , 2014 .

[11]  Naoki Honma,et al.  Estimating Living-Body Location Using Bistatic MIMO Radar in Multi-Path Environment , 2015, IEICE Trans. Commun..

[12]  Yoichi Hori,et al.  Detection of Abnormal Action Using Image Sequence for Monitoring System of Aged People , 2002 .

[13]  Naoki Honma,et al.  Antenna Array Calibration for Living-Body Radar , 2016, IEEE Antennas and Wireless Propagation Letters.

[14]  Naoki Honma,et al.  Evaluation of fast human localization and tracking using MIMO radar in multi-path environment , 2016, 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[15]  Emil Jovanov,et al.  Issues in wearable computing for medical monitoring applications: a case study of a wearable ECG monitoring device , 2000, Digest of Papers. Fourth International Symposium on Wearable Computers.

[16]  Naoki Honma,et al.  Fast estimation algorithm for living body radar , 2014, 2014 International Symposium on Antennas and Propagation Conference Proceedings.

[17]  Jun Li,et al.  Multitarget Identification and Localization Using Bistatic MIMO Radar Systems , 2008, EURASIP J. Adv. Signal Process..