**5. References**

	- [9] Van Dorp, P.; Groen, F. (2003) Real-Time Human Walking Estimation with Radar, International Radar Symposium IRS 2003, Dresden, Germany, pp 645-650
	- [10] Lei, J.; Lu, C. (2005) Target Classification Based on Micro-Doppler Signatures, IEEE International Radar Conference 2005; Arlington, USA; pp 179-183
	- [11] Klotz, M. (2002) An Automotive Short Range High Resolution Pulse Radar Network, Phd. Thesis, Hamburg University of Technology, Hamburg, Germany
	- [12] Luebbert, U. (2005) Target Position Estimation with a Continuous Wave Radar Network, Phd. Thesis, Hamburg University of Technology, Hamburg, Germany
	- [13] Foelster, F., Rohling, H. and Meinecke, M. M. (2005) Pedestrian recognition based on automotive radar sensors, 5th European Congress on Intelligent Transportation Systems and Services 2005, Hannover, Germany
	- [14] Heuel, S.; Rohling, H. (2011) Two-Stage Pedestrian Classification in Automotive Radar Systems, International Radar Symposium IRS 2011, Leipzig, Germany
	- [15] Nalecz, M.; Rytel-Andrianik, R.; Wojtkiewicz, A. (2003) Micro-doppler analysis of signals received by FMCW radar, Proceedings of International Radar Symposium 2003, Dresden, Germany, pp. 651-656
	- [16] Duda, R. O.; Hart, P. E.; Stork, D. G. (2001) Pattern classification, Wiley, New York
	- [17] Schuermann, J. (1996) Pattern Classification A Unified View of Statistical and Neural Approaches, Wiley, New York
	- [18] Schiementz, M. (2005) Postprocessing Architecture for an Automotive Radar Network, Phd. Thesis, Hamburg University of Technology, Hamburg, Germany
	- [19] Meinecke, M.-M.; Rohling, H. (2000) Combination of LFMCW and FSK modulation principles for automotive, German Radar Symposium GRS 2000, Berlin, Germany
	- [20] Winner, H., Hakuli, S., Wolf, G., (2009), Handbuch Fahrerassistenzsysteme, Vieweg+Teubner Verlag / GWV Fachverlage GmbH, Wiesbaden, Germany
	- [21] Smart Microwave Sensors GmbH, (2012), UMRR | LCA BSD Technical Information Sheet, available at http://www.smartmicro.de/images/stories/contentimage/automotive/LCA and BSD Technical Information.pdf, Accessed: 30 August 2012
	- [22] Perry, J. (1992) Gait Analysis Normal and Pathological Function, SLACK Incorporated, ISBN 1556421923
	- [23] Foelster, F.; Ritter, H., Rohling, H. (2007) Lateral Velocity Estimation for Automotive Radar Applications, The IET International Conference on Radar Systems, Edinburgh, Great Britain
	- [24] Boser, B. E.; Guyon, I. M.; Vapnik, V. N. (1992) A training algorithm for optimal margin classifiers, In D. Haussler, editor, 5th Annual ACM Workshop on COLT, Pittsburgh, PA, pp. 144-152
	- [25] Wu, X.; Kumar, V.; Ross Quinlan, J.; Ghosh, J.; Yang, Q.; Motoda, H.; McLachlan, G. J.; Ng, A.; Liu, B., Yu, P. S. and others (2008) Top 10 algorithms in data mining, Knowledge and Information Systems, Vol. 14, No. 1., pp. 1-37
	- [26] Branko, R.; Sanjeev, A.; Nei, G. (2004) Beyond the Kalman Filter: Particle Filters For Tracking Applications, Artech House Inc.

© 2013 Sachs et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 Sachs et al., licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**ultraMEDIS – Ultra-Wideband** 

Ulrich Schwarz, Marko Helbig and Jürgen Sachs

Additional information is available at the end of the chapter

Ingrid Hilger, Katja Dahlke, Gabriella Rimkus, Christiane Geyer, Frank Seifert, Olaf Kosch, Florian Thiel, Matthias Hein, Francesco Scotto di Clemente,

The exploitation of electromagnetic interaction with matter specifically with organic tissues is a powerful method to extract information about the state of biological objects in a fast, continuous and non-destructive (i.e. painless) way. These interactions are mainly based on

One proceeds on an atomic and molecular level, which is typically described by the

reasons of possible interactions may be quite manifold. Here, in connection with ultrawideband sounding, we restrict ourselves to pure electric interactions which affect the permittivity and conductivity via the motion of free charge carriers (free electrons and ions), the Maxwell-Wagner polarization (also Maxwell-Wagner-Sillars polarization) at boundaries, reordering of dipolar molecules or oscillations on an atomic or nuclear level. We assume that

interaction mechanisms for biological tissue is given in [1], and sub-chapter 3 deals with some selected examples. The related effects are scattered over a huge frequency band covering 15…18 decades. In this paper, we limit ourselves to RF and lower microwave frequencies. Water – the key building block of life –shows dipole relaxation within the considered frequency band. Additionally, it has a very high permittivity in comparison with other natural substances. Hence, water will play an important role for UWB-sounding of biological tissue or human and animal subjects. Examples exploiting this fact are discussed in sub-chapter 5 dealing with breast cancer detection or in [2], which refers to lung edema. The frequency bands of our experiments were selected depending on physical requirements (propagation attenuation, relaxation time) and implementation issues of the sensor electrodes (e.g. antennas).

 

and conductivity

. An overview of relevant

. The physical

, permeability

all involved substances have the permeability of vacuum 0

**Sensing in Medicine** 

http://dx.doi.org/10.5772/54987

two groups of phenomena.

macroscopic quantities permittivity

**1. Introduction** 
