Data Presentation and Preprocessing 2.1 IR Data in .NET

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2. Data Presentation and Preprocessing 2.1 IR Data
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Our concern is only a passive IR sensor, which observes and measures heat without being in contact with the source of it. Therefore, the principle of IR mine detection is very simple. Objects (in our case mines), having different materials and thus different thermal characteristics than their surroundings, can be detected by IR sensors under some conditions. Namely, mines become hotter and colder faster than their surroundings, meaning that the daily evolution of IR mine signatures can be observed.
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Data Presentation and Preprocessing
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Consequently, depending on the time of the day, a mine can appear in an IR image as lighter (warmer) than its surroundings, as darker (colder), or it cannot be noticed due to having reached thermal equilibrium with the surroundings. In addition, the IR contrast between an object and its surroundings decreases strongly with the depth, so an IR sensor is most often used for direct detection of surface-laid mines. Indirect detection of buried mines is either due to the surface effect (disturbed soil due to recent burial of mines) or due to the volume effect (the presence of a long-buried mine changes the heat and water flow conditions above the mine) [11]. Since the IR images result from simple and known operational principles and the images are almost purely representing radiated energy, some classical noise reduction tools are applied in the preprocessing step [11]. Note that most of the mines are thin cylinders and that in general, due to some burial angle, they appear as ellipses in the IR images.
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2.2 GPR Data
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Earth materials are mostly nonmagnetic and the change in conductivity mainly affects absorption of the GPR signal by the medium. Thus, it is usually the permittivity contrast that leads to a reflection of the electromagnetic waves radiated by the transmit antenna of the GPR and the detection of backscattered echoes by its receiving antenna.
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2.2.1 Types of GPR Data Presentation
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A common presentation of the signals obtained by GPR is in the form of scans: A-, B- and C-scans (adopted from acoustic terminology), and data processing can be applied to any of them. A single amplitude time waveform, with the GPR antennas at a given fixed position, is referred to as an A-scan. A B-scan presents an ensemble of A-scans gathered along one axis, or, in other words, it is a twodimensional (2D) image representing a vertical slice in the ground. Note that reflections from a point scatterer located below the surface are present in a broad region of a B-scan, due to the poor directivity of the transmitting and the receiving antenna. Finally, a C-scan is a three-dimensional (3D) data set resulting from collecting multiple parallel B-scans, hence recording the data over a regular grid in the soil surface plane. Usually, a C-scan is represented as a horizontal slice of this 3D data set by plotting its amplitudes at a given time.
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2.2.2 A-scan Preprocessing Methods
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In order to use the information on energy contained in an A-scan, the weakening of the signal with the depth should be compensated. Another problem that should be overcome is the strong reflection at the air/ground interface, that, besides strongly biasing the energy contained in each A-scan, often hides reflections from objects buried just below or placed just above the surface. While propagating from the transmitter towards a buried object and being scattered back to the receiver, the electromagnetic waves of the GPR are subject to some losses [12,13]. In particular, the deeper the object is buried, the higher the losses introduced by the soil are. In order to compensate for these attenuations in function of R or, more directly, of time t, a Time-Varying Gain (TVG) is introduced, by which a fixed gain of X dB per second (or per meter) is added to the raw signal s, so the amplified signal in the time domain is: sTVG t = s t 10 20
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The optimal value of TVG strongly depends on the type of GPR used, on the type and characteristics of the soil, on the level of moisture and on the depth range of interest, so it is usually chosen to meet the operational requirements. Its values can typically vary from 0.1 dB/ns up to 100 dB/ns.
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