Abstract
Ultra wide band (UWB), can be used to detect human target hidden by walls. Information theoretic algorithms like entropy, relative entropy and mutual information are proven methods that can be applied to data collected by various sensors for detecting target. In this paper, we propose to use entropy and relative entropy to detect target. Breathing motion in human will cause periodic changes in the received signal at a distance where target is located. Relative entropy can detect the change in histogram quickly. After applying weight using relative entropy, we can apply entropy based detection. We conducted study in three different kinds of walls. When target is behind gypsum wall, accurate detection can be achieved by applying this method. We can identify the human behind the brick wall as well. However, human was undetected using this algorithm while hidden by wooden doors.
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Acknowledgements
This work was supported in part by U.S. Office of Naval Research under Grants N00014-13-1-0043, N00014-11-1-0071, N00014-11-1-0865, and U.S. National Science Foundation under Grants CNS-1247848, CNS-1116749, CNS-0964713.
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Maherin, I., Liang, Q. (2015). Human Detection Through Wall using Information theory. In: Mu, J., Liang, Q., Wang, W., Zhang, B., Pi, Y. (eds) The Proceedings of the Third International Conference on Communications, Signal Processing, and Systems. Lecture Notes in Electrical Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-319-08991-1_16
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DOI: https://doi.org/10.1007/978-3-319-08991-1_16
Publisher Name: Springer, Cham
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