Feedback Beamforming in the Time Domain

Array signal processing enables modern sensing systems to extract spatial information, yet conventional beamforming often struggles with high sampling demands, quantization noise, and real-time constraints. In this talk, I will present a new time-domain feedback beamforming architecture designed to overcome these limitations in RADAR-like applications.
The method builds on the analogy between FIR and IIR filtering by introducing a spatial feedback loop. Assuming the target behaves as a reflective surface, the array retransmits a synthesized version of the received signal back toward the source. This feedback reinforces the spatial response and allows the system to jointly estimate both direction of arrival (DOA) and range.
I will outline the architecture and evaluate its performance through key spatial metrics, including beamwidth, sidelobe attenuation, and directivity. Results show that the feedback mechanism significantly enhances spatial performance while maintaining low computational complexity. A comparison with frequency-domain approaches also highlights the advantages of a time-domain implementation for real-time processing.
Overall, the proposed feedback beamformer demonstrates improved accuracy, stronger spatial selectivity, and suitability for fast, efficient sensing systems.

Under the supervison of Prof, Israel Cohen.