| Summary: | This thesis optimizes a previously developed direct signal suppression (DSS) algorithm for single-channel passive radar that uses radio-astronomical sources (e.g., the sun and Jupiter’s radio emissions) as ambient noises, as we first noted at the IGARSS 2023 IEEE Symposium. Such passive radars can be used in extreme environments such as polar regions to measure ice sheet thickness and space-based experiments as a low-resource solution. To optimize the DSS algorithm, we estimate the direct signal and perform Wiener deconvolution, focusing on echo peak power (α) and delay time (τ) in the impulse response function construction. Although only a minor increase in signal-to-noise ratio (SNR) was achieved compared to the previous approach, the results highlight the significant losses in SNR if the estimation of the phase (τ) is not accurate. On the other hand, the amplitude of the impulse response has a negligible impact on SNR compared to the correct phase estimation. The latter part of this thesis focuses on the Total Electron Content (TEC) of Earth’s ionosphere over Greenland and explores its variations across different timescales, including daily, yearly, and solar cycles. Based on these calculations, the phase difference and the time delay generated due to the TEC are presented. Significantly, the study evaluates the potential impact of inadequately accounting for TEC on the SNR of a space-based single-channel passive radar orbiting in a Low Earth Orbit (LEO) above Greenland. Approved for public release. Distribution is unlimited. Ipopliarhos, Hellenic Navy
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