Fully-analog array signal processor using 3D aperture engineering

2026-03-01

AI Summary

This work addresses the fundamental limitations of conventional array signal processing—constrained by two-dimensional apertures, low design precision, and inefficient computational architectures—which hinder突破 beyond the Rayleigh diffraction limit and restrict both angular resolution and the number of resolvable sources. To overcome these challenges, the paper proposes a fully analog array signal processor (FASP), introducing a novel three-dimensional aperture engineering framework based on deeply cascaded metasurfaces. Operating entirely in the analog domain, FASP enables parallel super-resolution direction-of-arrival estimation, source number detection, and multi-channel separation. Through multidimensional synthetic aperture training, neural-enhanced physical modeling, and analog-domain channel response orthogonalization, the system achieves approximately N-fold enhancement in angular resolution within the 36–41 GHz band, accurately resolves ten concurrent sources, suppresses radar interference by 20 dB, and increases communication capacity by 13.5×.

Technology Category

• Search and Optimization: Metareasoning and Metaheuristics
• Machine Learning: Hardware-aware ML
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Responsible Web: Measurement, analysis, and circumvention of Web censorship
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

The rapid progress in radar and communication places increasing demands on low-latency and energy-efficiency array signal processing methods. There is an emerging direction of constructing analog computing processors for directly processing electromagnetic (EM) waves. However, the existing methods are constrained by 2D physical aperture and imprecise design process with inefficient computing architecture, resulting in limited sensing resolution and number of separated sources. Here, we present a fully-analog array signal processor (FASP) using 3D aperture engineering framework to perform super-resolution direction-of-arrival estimation, source number estimation, and multi-channel source separation in parallel for both coherent and incoherent sources. 3D aperture engineering is realized by constructing deep cascaded metasurface layers so that the diffractive propagation from oblique incident fields can be layer-wise modulated and piecewise encoded for perceiving EM fields far exceeding physical aperture limits. The multi-dimensional synthetic aperture (MSA) training is developed to characterize the metasurface modulation and optimize the neuro-augmented physical model for extending system aperture and generating high-order nonlinear angular response. FASP orthogonalizes the array response vectors of communication channels to map them into antenna detectors in the analog domain. The $N$-layer FASP has the capability to achieve ~N times higher angular resolution than the Rayleigh diffraction limit. Experiments further validate the source number estimation and independent channel separation of 10-target that can suppress radar jamming signals by ~20 dB and enhance channel communication capacity by 13.5 times at 36~41 GHz. FASP heralds a paradigm shift in signal processing for super-resolution optics, advanced radar, and 6G communications.

Problem

• array signal processing
• super-resolution
• direction-of-arrival estimation
• source separation
• analog computing

Innovation

• 3D aperture engineering
• fully-analog signal processing
• metasurface cascade
• super-resolution DOA estimation
• multi-dimensional synthetic aperture