Wykaz obszarów badawczych związanych z tagiem Signal-processing:
| # | Obszar badawczy | Dziedzina naukowa |
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| 1 |
Research Area of the Research Group on Radar Imaging Techniques, lead by dra hab. inż. Piotr Samczyński, prof. WUT, specializes in digital signal processing for the creation of two-dimensional (2D) and three-dimensional (3D) radar images using the synthetic aperture technique (SAR – Synthetic Aperture Radar) and the inverse SAR technique (ISAR – Inverse SAR). This research team has developed a number of demonstrators of radar technologies, both active and passive SAR / ISAR, covering a wide spectrum of operating frequencies, from low VHF through the C, X, K and W bands and ending with sub-millimeter bands (THz). Other areas of research also include: signal processing in multi-band active-passive radar systems, recognition of radar signal signatures, radio-targeting of radio-communication and radar emissions, and radio-electronic warfare techniques.
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| 2 |
“Capacitively coupled impedance tomography for anatomical and functional imaging” To date, electrical impedance tomography (EIT) using sinusoidal excitation has been regarded as the most promising electrical imaging technique for diagnostic medical applications. However, the high impedance at the electrode-skin contact remains a significant challenge, hindering both the development and practical implementation of this technology. To address these limitations, an alternative approach utilizing non-contact electrodes and pulse excitation will be explored. This method will involve signal shape analysis to determine both components of admittance. Such data will enable the reconstruction of images depicting electrical permittivity and conductivity. Capacitively coupled electrical tomography will be investigated using numerical and physical lung phantoms, with a focus on regional ventilation distribution. Key metrics such as measurement sensitivity, contrast, and spatial-temporal resolution of the resulting images will be evaluated. Non-linear iterative algorithms and deep learning techniques will be employed for image reconstruction. Real measurements will be conducted using a simplified thorax phantom designed to simulate the respiratory cycle. A prototype flexible sensor incorporating surface electrodes will be developed, along with a mechanical-electrical lung phantom. Measurements will be carried out using the 32-channel electrical capacitance tomograph EVT4, which was designed and constructed at ZEJiM.
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