Multi-target DoA estimation with a single Rydberg atomic receiver by spectral analysis of spatially-resolved fluorescence

2026-01-30

AI Summary

This work addresses the limitations of conventional Rydberg atom-based receivers, which struggle with multi-target broadband direction finding due to array complexity, single-target assumptions, and narrowband response. The authors propose an imaging-based spectral estimation (ISE) method that transforms direction-of-arrival estimation into a spectral analysis problem by spatially resolving the fluorescence distribution in a vapor cell. By leveraging a strong local oscillator to linearize the atomic absorption response, a one-to-one mapping between spatial frequency and incident angle is established. High-resolution spectral estimation is then achieved via Prony’s method. This approach enables, for the first time in a single Rydberg receiver, simultaneous multi-target, broadband, and high-precision direction finding, surpassing the unit-cell length constraint and approaching the Cramér–Rao lower bound, thereby offering a new paradigm for continuous-aperture sensing and holographic MIMO systems.

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services

Abstract

Rydberg-based Direction-of-Arrival (DoA) estimation has been hampered by the complexity of receiver arrays and the single-target, narrow-band limitations of existing single-receiver methods. This paper introduces a novel approach that addresses these limitations. We demonstrate that by spatially resolving the fluorescence profile along the vapor cell, the multi-target problem can be effectively solved. Our approach hinges on the insight that by superimposing incoming signals with a strong local oscillator (LO), the complex atomic absorption pattern is linearized into a simple superposition of sinusoids. In this new representation, each spatial frequency uniquely and directly maps to the DoA of a target. This reduces the multi-target challenge into a spectral estimation problem, which we address using Prony's method. Our approach, termed Imaging-based Spectral Estimation (ISE), inherently supports multi-target detection and restores the full broadband capability of the sensor by removing the restrictive cell-length dependency. This development also shows potential for realizing multi-channel Rydberg receivers and the continuous-aperture sensing required for holographic multiple-input multiple-output (MIMO). We develop a comprehensive theoretical model, derive the Cramer-Rao Lower Bound (CRLB) as a performance benchmark, and present simulations validating the effectiveness of the approach to resolve multiple targets.

Problem

• Direction-of-Arrival estimation
• Rydberg atomic receiver
• multi-target detection
• broadband sensing
• spatially-resolved fluorescence

Innovation

• Rydberg atoms
• Direction-of-Arrival estimation
• spatially-resolved fluorescence
• spectral estimation
• multi-target detection