Through-Wall Imaging With UWB Radar System - KEMT FEI TUKE

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4.2 Measurements of the Wall Parameters by Reflectometry 56 Z[m] 0.6 0.7 0.8 0.9 1.0 1.1 1.2 Z X = 1.73 m Z = 1.0 m 0.5 m Antennas movement 1.6 m 3 m 0.4 m Brick wall �rw= 3.4 1 m Metal plate 0.67 m 0.64 m Fig. 4.1.12: SAR measurement - Scenario 2. 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 a) X[m] Z[m] 0.6 0.7 0.8 0.9 1.0 1.1 1.2 X X = 1.6 m Z = 1.0 m 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 X[m] Fig. 4.1.13: Migrated images - Scenario 2. a) Method with simple wall compensation. b) Proposed method with precise TOA estimation. 4.2 Measurements of the Wall Parameters by Reflectometry Precise SAR imaging of objects, detection of the moving person behind the wall, or non-destructive testing of the state or quality of walls constructions in civil engineering with UWB radar requires the knowledge of wall parameters like thickness, permittivity, and conductivity. Their use in data processing produces more precise and realistic results, as we have shown in Section 4.1. The more precise the wall parameters are known the better the complex algorithms for SAR imaging [1] or detection of moving persons [114] could be enhanced. The measurement of the wall parameters is challenge in a real environment especially when there is access only from one side of the wall. In this section, an effective and fast algorithm for wall parameters estimation that can be used in practice is presented. For that purpose the magnitudes and the time positions of reflections from inner and outer interfaces of the wall are extracted from the data. A new scanning method that b)
4.2 Measurements of the Wall Parameters by Reflectometry 57 we propose significantly reduces the clutter caused by objects in the measurement environment such as reflections from other walls, the ceiling, the floor and antenna crosstalk. The algorithm was tested on 13 different types of walls with various permittivity, conductivity and thickness. A handheld M-sequence UWB radar with horn and circular antennas was used for data gathering. The proposed method is very robust and the error of the thickness estimation was less than 10% for most of the measured walls. The whole measurement could be handled by one person. The wall parameter estimation runs in real time and is fully automated. 4.2.1 Conventional Methods for Wall Parameters Estimation There are several methods for estimation the wall parameters. They could be estimated most precisely when the wall is placed in between the antennas [102, 103,40]. However, this is not practical especially in case of terrorists or fire since it is meaningless for the intended applications to measure the wall from both sides. A further approach uses different standoff distances for wall parameters estimation in [141, 142]. A small object, that has to be visible from at least two antenna positions, has to be situated behind the wall what is impractical as well. Moreover, the wall parameters would be estimated incorrectly if the position of this object is estimated even with very little inaccuracy. Methods [141,142] were tested only on simulated data. SAR image de-smearing or auto-focusing were also used [8, 95]. However, the blurring of SAR images is practically very small and mostly lost in noise. Most of all the position of an object is changing significantly when the wall parameters are unknown as it has been shown in Section 4.1.7. This method was also tested only on simulated data. By representing the wall reflections in the Laplace domain, the pole positions can be used for wall parameter estimation using Prony’s method [72]. However, even small noise would shift the pole positions significantly. Therefore, the approach is only useful for simulations. A model based solution of an inverse problem was also proposed. It solves iteratively the wave equations using Green’s function [89, 14]. These methods are very complicated, require huge computation power as well as the time and most of them were tested only on simulated data. In this section a new method for estimation of thickness, permittivity, and conductivity of a wall is introduced. The main attention was paid to develop a practical estimation method that could be used in the real environment. The measurement is carried out from one side of the wall, thus there is no need to enter a danger area. The measurement process is very fast and easy to handle. A positioning system is not required. The processing of the proposed algorithm does not take more than 2 seconds on a standard laptop with 1.8 GHz Intel processor in MATLAB.
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TECHNICAL UNIVERSITY OF KOˇSICE Fa
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Acknowledgement I give a sincere gr
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CONTENTS v 3 Goals of Dissertation
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LIST OF FIGURES vii List of Figures
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LIST OF FIGURES ix 4.4.3 Aquarium f
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LIST OF FIGURES xi List of Symbols
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LIST OF FIGURES xiii kx - Horizonta
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Chapter 1 Introduction 1.1 Motivati
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1.3 Thesis Organization 3 In additi
Page 19 and 20: Chapter 2 State Of The Art 2.1 UWB
Page 21 and 22: 2.2 Through-Wall Radar Basic Model
Page 23 and 24: 2.3 SAR Scanning 9 and shall remain
Page 25 and 26: 2.4 Calibration and Preprocessing 1
Page 27 and 28: 2.4 Calibration and Preprocessing 1
Page 29 and 30: 2.5 Radar Imaging Methods Overview
Page 55 and 56: Chapter 4 Selected Research Methods
Page 57 and 58: 4.1 Through-Wall TOA Estimation 43
Page 69: 4.1 Through-Wall TOA Estimation 55
Page 73 and 74: 4.2 Measurements of the Wall Parame
Page 81 and 82: 4.3 Highlighting of a Building Cont
Page 91 and 92: 4.4 Measurements of the Practical S
Page 99 and 100: 5.1 Conclusion and Future Work 85 5
Page 101 and 102: 50 100 150 200 250 300 350 400 Z 45
Page 103 and 104: 50 100 150 200 250 300 350 400 Z 45
Page 105 and 106: 50 100 150 200 250 300 350 400 Z 45
Page 107 and 108: 50 100 150 200 250 300 350 400 Z 45
Page 109 and 110: Z [cm] Z [cm] 50 100 150 200 250 30
Page 111 and 112: Z [cm] 50 100 150 200 250 300 b) Em
Page 113 and 114: BIBLIOGRAPHY 99 [13] T. W. Barrett,
Page 115 and 116: BIBLIOGRAPHY 101 [46] G. Derveaux,
Page 117 and 118: BIBLIOGRAPHY 103 [81] S. Kidera, T.
Page 119 and 120: BIBLIOGRAPHY 105 [115] J. Sachs, M.
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BIBLIOGRAPHY 107 [150] O. Yilmaz, S
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Through-Wall Imaging With UWB Radar System - KEMT FEI TUKE

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