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Stationary planar-surface target detection in an unknown indoor environment

Published online by Cambridge University Press:  25 March 2015

Honghui Yan ,
Qiaozhen Liu  and
Reiner S. Thomä
Honghui Yan*
Affiliation:
Electronic Measurement Research Lab, Institute for Information Technology, Ilmenau University of Technology, Ilmenau 98693, Germany
Qiaozhen Liu
Affiliation:
Beijing Institute of Astronautical Systems Engineering, Beijing 100076, China
Reiner S. Thomä
Affiliation:
Electronic Measurement Research Lab, Institute for Information Technology, Ilmenau University of Technology, Ilmenau 98693, Germany
*
Corresponding author: H. Yan, Email: [email protected]
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Abstract

It is difficult to detect a stationary object in practice, especially in an unknown indoor environment, because (a) there is no distinct speed difference between the targets and the background; (b) responses of the targets are contaminated by dense unknown clutter; (c) a priori knowledge of the background is not always available for some scenarios. In this paper, a set of ultra-wideband sensors are used to detect a stationary target with a planar diffuse surface. It is shown that, the relative spectrum-shifts of the data after data-projection operation, are closely connected to the illumination-angle differences. Based on this, a detector is designed, and the location and the orientation of the target are determined. In order to mitigate the influence of clutters, a “time-shift & accumulation” scheme is designed to enhance the signal. As a consequence, the signal-to-interference-and-noise ratio is increased. In addition, results from measurement in a realistic indoor environment are provided.

Keywords

Radar signal processing and system modelingRadar applicationsStationary target detection
Type
Research Paper
Information
International Journal of Microwave and Wireless Technologies , Volume 8 , Issue 3: Journee Nationale des Micro-ondes (JNM) 2015 , May 2016 , pp. 603 - 613
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2015 

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References

REFERENCES

[1]Scheer, W.L.M.J.A. (ed.): Principles of Modern Radar, vol. III of Radar Applications, SciTech Publishing, an imprint of the IET, Edison, NJ, 2014.Google Scholar
[2]Moura, J.M.F.; Jin, Y.: Time reversal imaging by adaptive interference canceling. IEEE Trans. Signal Process., 56 (1) (2008), 233–247.Google Scholar
[3]Varslot, T.; Yazici, B.; Yarman, C.-E.; Cheney, M.; Scharf, L.: Time-reversal waveform preconditioning for clutter rejection, in Proc. Int. Waveform Diversity and Design Conf., 2007, 330–334.Google Scholar
[4]Borcea, L.; Papanicolaou, G.; Tsogka, C.; Berryman, J.: Imaging and time reversal in random media. Inverse Probl., 18 (2002), 1247.Google Scholar
[5]Zhang, W.; Hoorfar, A.; Li, L.: Through-the-wall target localization with time reversal music method. Progress Electromagn. Res., 106 (2010), 75–89.Google Scholar
[6]Wang, L.J.Z.H.F.: Experimental investigation of selective localization by decomposition of the time reversal operator and subspace-based technique. IET Radar, Sonar Navig., 2 (6) (2008), 426–434.Google Scholar
[7]van den Bos, A.: The multivariate complex normal distribution-a generalization. IEEE Trans. Inf. Theory, 41 (2) (1995), 537–539.Google Scholar
[8]Kobayashi, H.; Mark, B.L.; Turin, W.: Probability, Random Processes, and Statistical Analysis, Cambridge University Press, Cambridge, UK, 2012.Google Scholar
[9]Poor, H.V.: An Introduction to Signal Detection and Estimation, Chapter III, 2nd ed., Springer-Verlag, New York, 1994.CrossRefGoogle Scholar
[10]Zetik, R.; Sachs, J.; Thoma, R.S.: Uwb short-range radar sensing – the architecture of a baseband, pseudo-noise UWB radar sensor. IEEE Instrum. Meas. Mag., 10 (2) (2007), 39–45.Google Scholar
[11]Prati, C.; Rocca, F.: Improving slant-range resolution with multiple SAR surveys. IEEE Trans. Aerosp. Electron. Syst., 29 (1) (1993), 135–143.Google Scholar