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Distributed Conjugate Gradient with Novel Stopping for Fast Adaptive Array Processing

Year: 2026

Type: conference-paper

Abstract: Large, wideband, fully digital arrays are essential for continuous wide-area surveillance, enabling multibeam adaptive beamforming, broad spectrum coverage, and RF resilience. Their potential, however, is limited by high data rates and scalability issues with traditional processing approaches. This paper proposes a distributed conjugate gradient algorithm for adaptive array processing, leveraging distributed architectures and a novel stopping criterion that triggers early termination based on the interference rank. This approach minimizes iterations, enhances scalability, reduces inter-processor bandwidth, and enables on-array processing. Use-cases in adaptive beamforming and clutter mitigation are demonstrated.

Source: IEEE Radar Conference (RadarConf)

DOI: 10.1109/radarconf2663773.2026.11675423

Authors: Brian Nowakowski, Aaron Ewall-Wice, Mathias Wanner, Gil Raz, R. K. Prasanth

Institution: Systems and Technology Research (United States)

Language: English

Topic: Direction-of-Arrival Estimation Techniques

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7208770476

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Cites: 11

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Related to: 10