no code implementations • 11 May 2023 • Moshe Levy-Israel, Igal Bilik, Joseph Tabrikian
Presence of multipath leads to misspecification in the radar data model, resulting in estimation performance degradation, which cannot be reliably predicted by conventional performance bounds.
no code implementations • 7 Jan 2023 • Stefan Feintuch, Joseph Tabrikian, Igal Bilik, Haim H. Permuter
Therefore, this work proposes a neural network (NN) based DOA estimation approach for spatial spectrum estimation in multi-source scenarios with a-priori unknown number of sources in the presence of non-Gaussian spatially-colored interference.
no code implementations • 21 Oct 2022 • Stefan Feintuch, Haim H. Permuter, Igal Bilik, Joseph Tabrikian
This work addresses the problem of range-Doppler multiple target detection in a radar system in the presence of slow-time correlated and heavy-tailed distributed clutter.
no code implementations • 26 Jun 2019 • Daniel Brodeski, Igal Bilik, Raja Giryes
While camera and LiDAR processing have been revolutionized since the introduction of deep learning, radar processing still relies on classical tools.