CFAR detectors for through wall tracking of moving targets by M-sequence UWB radar

In this paper different CFAR detectors for detection of multiple targets for UWB radar system will be described. In this paper, the cell averaging CFAR (CA-CFAR) cell averaging with greatest of (CAGO-CFAR) and ordered statistics CFAR (OS-CFAR) will be represented. The detectors outputs will be illustrated and compared. The properties of all detectors will be illustrated by real radar signal processing obtained by the measurement with the M-sequence UWB radar.

[1]  I.J. Immoreev Ultrawideband systems-features and ways of development , 2004, 2004 Second International Workshop Ultrawideband and Ultrashort Impulse Signals (IEEE Cat. No.04EX925).

[2]  Alex Pentland,et al.  Pfinder: Real-Time Tracking of the Human Body , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  M. Barnes,et al.  A moving target detection filter for an ultra-wideband radar , 2003, Proceedings of the 2003 IEEE Radar Conference (Cat. No. 03CH37474).

[4]  James D. Taylor Ultra-wideband Radar Technology , 2000 .

[5]  Ron Daisy,et al.  High-resolution through-wall imaging , 2006, SPIE Defense + Commercial Sensing.

[6]  Hermann Rohling,et al.  Radar CFAR Thresholding in Clutter and Multiple Target Situations , 1983, IEEE Transactions on Aerospace and Electronic Systems.

[7]  R. Yelf,et al.  Where is true time zero ? , 2004, Proceedings of the Tenth International Conference on Grounds Penetrating Radar, 2004. GPR 2004..

[8]  M. Aftanas,et al.  Detection and tracking of moving or trapped people hidden by obstacles using ultra-wideband pseudo-noise radar , 2008, 2008 European Radar Conference.

[9]  W. Eric L. Grimson,et al.  Learning Patterns of Activity Using Real-Time Tracking , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Rudolf Zetik,et al.  Detection and localization of persons behind obstacles using M-sequence through-the-wall radar , 2006, SPIE Defense + Commercial Sensing.

[11]  J. Rovnakova,et al.  Signal processing for through wall moving target tracking by M-sequence UWB radar , 2008, 2008 18th International Conference Radioelektronika.

[12]  Anish Arora,et al.  Towards radar-enabled sensor networks , 2006, IPSN.

[13]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice , 1993 .

[14]  Adrian E. Raftery,et al.  Principal Curve Clustering With Noise , 1997 .

[15]  Ibrahim Tekin,et al.  High resolution ultrawideband wall penetrating radar , 2007 .

[16]  Mohsen Guizani,et al.  Ultra-Wideband Wireless Communications and Networks: Shen/Ultra-Wideband Wireless Communications and Networks , 2006 .

[17]  Massimo Piccardi,et al.  Background subtraction techniques: a review , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[18]  Rudolf Mathar,et al.  Estimating position and velocity of mobiles in a cellular radio network , 1997 .

[19]  Bassem Mahafza,et al.  Radar Systems Analysis and Design Using MATLAB , 2000 .

[20]  Branko Ristic,et al.  Beyond the Kalman Filter: Particle Filters for Tracking Applications , 2004 .

[21]  Branko Ristic,et al.  Bearings-Only Tracking of Manoeuvring Targets Using Particle Filters , 2004, EURASIP J. Adv. Signal Process..

[22]  Christopher M. Bishop,et al.  Mixtures of Probabilistic Principal Component Analyzers , 1999, Neural Computation.

[23]  B. T. Fang,et al.  Simple solutions for hyperbolic and related position fixes , 1990 .

[24]  Kentaro Toyama,et al.  Wallflower: principles and practice of background maintenance , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[25]  H. Vincent Poor,et al.  An Introduction to Signal Detection and Estimation , 1994, Springer Texts in Electrical Engineering.

[26]  Mark A. Barnes,et al.  Preliminary interferometric images of moving targets obtained using a time-modulated ultra-wide band through-wall penetration radar , 2001, Proceedings of the 2001 IEEE Radar Conference (Cat. No.01CH37200).

[27]  P.K. Dutta,et al.  Towards radar-enabled sensor networks , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.