2-bit QPSK phase-shift beamforming with an ML predictor and local search achieves up to 11 dB higher average C/N0 than an unprotected GNSS receiver under strong jamming (J/S=70 dB).
A linearly convergent doubly stochastic Gauss–Seidel algorithm for solving linear equations and a certain class of over-parameterized optimization problems
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Low-Cost GNSS Anti-Jamming Through 2-Bit Phase Shift Beamforming with Machine Learning
2-bit QPSK phase-shift beamforming with an ML predictor and local search achieves up to 11 dB higher average C/N0 than an unprotected GNSS receiver under strong jamming (J/S=70 dB).