In this paper, the problem of the quantitative characterization of thermal resistance fields in a multilayer sample is addressed by using the classical front face flash method as the thermal excitation and infrared thermography (IRT) as the monitoring sensor. In this challenging problem, the complete inverse processing of a multilayer analytical model is difficult due to the lack of sensitivity of some parameters (layer thickness, depth of thermal resistance, etc.) and the expansive computational iterative processing. For these reasons, the proposed strategy is to use a simple multilayer problem where only one resistive layer is estimated. Moreover, to simplify the inverse processing often based on iterative methods, an asymptotic development method is proposed here. Regarding the thermal signal reconstruction (TSR) methods, the drawback of these methods is the inability to be quantitative. To overcome this problem, the method incorporates a calibration process originating from the complete analytical quadrupole solution to the thermal problem. This analytical knowledge allows self-calibration of the asymptotic method. From this calibration, the quantitative thermal resistance field of a sample can be retrieved with a reasonable accuracy lower than 5%.

Tectonic inheritance is a concept proved by the importance of tectonic phase’s variation during time. It is related to
reactivation in compression of old normal faults. In our study we will focus on Gafsa basin that is an example of
intracratonic chain. The tectonic data confirm that it is affected by several tectonics phases; they began with Triassic
distension continuing to Cretaceous and followed by resumption in compression according to NW-SE direction during
alpine phase. Structural reliefs observed in Gafsa Basin are interpreted according to the “fault related fold” theory, by
using the model of ‘fault propagation fold’. The applications of this model will show a decollement level within the
Triassic series. In addition, an important deformation will be identified while approaching to faults. The data elaborate
from field confirm the role of these faults in the interpretation of tectonic heritage and development of intracratonic
chains in Gafsa Basin.

In this paper, multiple signal classification and estimation of signal parameters via rotational invariance technique (ESPRIT) algorithms are proposed to estimate the direction of arrival (DOA) of multiple incident signals under known mutual coupling among elements of the antenna array. These algorithms use the same subspace based techniques to achieve the separation of the eigenvectors into two subspaces: the signal space and the noise space. However, ESPRIT only uses the signal space. The performance of subspace based DOA estimation algorithm is evaluated using uniform linear arrays of dipole elements. The simulation results show the exact number of samples and elements, signal‐to‐noise ratio and spacing between the antennas elements used are the most important parameters in the algorithms, to sustain the accuracy of the DOA of the incident signals. The problem of calculating mutual coupling coefficient of the array elements is formed into a matrix has been considered. It is shown from the simulation results that the performance of the DOA estimation techniques considering the mutual coupling effect can be improved by the proposed compensation method. The different results obtained are in good agreement with those of the literature.

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