Hi, I am Usman and I am looking to apply to GNU Radio for this year's Google Summer of Code.
I am a final year bachelor student at National University of Science and Technology, Pakistan. My final year project is on using passive radars for indoor human motion sensing, during which I have gained extensive familiarity with USRP B200 and GNU Radio. Currently, I am working on a machine learning project that uses deep learning (CNN) to detect signal modulation for 11 modulation schemes. This research is inspired from this <https://arxiv.org/abs/1602.04105> work with the exception that we are developing an extensive dataset for various indoor and outdoor environments and we plan to open source this data in around a week. As a part of GSOC 2017, I want to mainly extend *gr-radar *and develop various signal processing modules of impact to users. I will be writing a detailed proposal in a few days but for now I have the following ideas: - Computing cross-ambiguity function and providing 3D visualisation - Adaptive filter implementation to remove the direct transmitted signal in case of passive radar systems which have reference and surveillance antennas - Batched cross correlation implementation in real time with overlaps between batches to ensure continuity - Angle of arrival estimation (although I recently found out about https://github.com/kit-cel/gr-specest which does something similar) I am also very interested in extending the machine learning capabilities of GNU Radio and create OOT modules that allow users to import models from *scikit-learn *(such as decision trees and KNNs) and *tensorflow *(such as CNN and LSTM). Ideally, I want to implement these signal processing and machine learning techniques together in a single module as I believe they go hand-in-hand. I am also open to any other ideas. Please let me know if there is any feedback as I write the first proposal draft! Best, -- Usman
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