Performance analysis of the Karhunen–Loève Transform for artificial and astrophysical transmissions: denoizing and detection

In this work, we propose a new method of computing the Karhunen–Loève Transform (KLT) applied to complex voltage data for the detection and noise level reduction in astronomical signals. We compared this method with the standard KLT techniques based on the Toeplitz correlation matrix and we conducted a performance analysis for the detection and extraction of astrophysical and artificial signals via Monte Carlo (MC) simulations. We applied our novel method to a real data study-case: the Voyager 1 telemetry signal. We evaluated the KLT performance in an astrophysical context: our technique provides a remarkable improvement in computation time and MC simulations show significant reconstruction results for signal-to-noise ratio (SNR) down to −10 dB and comparable results with standard signal detection techniques. The application to artificial signals, such as the Voyager 1 data, shows a notable gain in SNR after the KLT

Performance analysis of the Karhunen–Loève Transform for artificial and astrophysical transmissions: denoizing and detection

In this work, we propose a new method of computing the Karhunen–Loève Transform (KLT) applied to complex voltage data for the detection and noise level reduction in astronomical signals. We compared this method with the standard KLT techniques based on the Toeplitz correlation matrix and we conducted a performance analysis for the detection and extraction of astrophysical and artificial signals via Monte Carlo (MC) simulations. We applied our novel method to a real data study-case: the Voyager 1 telemetry signal. We evaluated the KLT performance in an astrophysical context: our technique provides a remarkable improvement in computation time and MC simulations show significant reconstruction results for signal-to-noise ratio (SNR) down to −10 dB and comparable results with standard signal detection techniques. The application to artificial signals, such as the Voyager 1 data, shows a notable gain in SNR after the KLT

A real-time FFT-KLT implementation for SETI research at the Sardinia Radio Telescope

The Search for ExtraTerrestrial Intelligence (SETI) is a project whose goal is to find possible life signatures emitted (intentionally or unintentionally) by possible civilizations from other habitable planets. Historically, the narrow-band FFT approach has been used, since a quasi-monochromatic signal is the most probable signal one would use to send a message to another world, that is in the case of intentionally- transmitted signals. Nevertheless, we could receive an unintentionally-transmitted signal as well. In that case, it would most certainly not be a quasi-monochromatic signal, but would probably be similar (with a wider bandwidth, of the order of MHz) to the signals that we use for conventional communications on Earth. The Kahrunen-Loève Transform (KLT) is a powerful algorithm for such a kind of research. However, a real-time implementation of the KLT has thus far not worked due to a lack of technological resources. We describe a hardware-software infrastructure at the Sardinia Radio Telescope (SRT) that, in real-time, makes it possible to perform the KLT in parallel to the FFT

A real-time KLT implementation for radio-SETI applications

SETI, the Search for ExtraTerrestrial Intelligence, is the search for radio signals emitted by alien civilizations living in the Galaxy. Narrow-band FFT-based approaches have been preferred in SETI, since their computation time only grows like N*lnN, where N is the number of time samples. On the contrary, a wide-band approach based on the Kahrunen-Lo`eve Transform (KLT) algorithm would be preferable, but it would scale like N*N. In this paper, we describe a hardware-software infrastructure based on FPGA boards and GPU-based PCs that circumvents this computation-time problem allowing for a real-time KLT