The RAPS Dome: A Conceptual Interferometric–Acoustic–Optical Sensor Architecture and Validation Protocol for Airspace Monitoring

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Authors: Marcel Krüger, Feeney Don, Tlacalelelt Mina Rodríguez acobo
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Abstract

This article is accepted by the Journal of Optics and Photonics Research (eISSN 3029-1348), 2025. This manuscript presents the RAPS Dome as aconceptual interferometric–acousticoptical sensor architecture and proposed validation protocol for passive airspace monitoring. The architecture extends the original Sensor Dome concept by integrating the Recursive Autonomous Projection System (RAPS) as a probabilistic decision layer on top of heterogeneous sensing modalities, including heterodyne interferometry, distributed acoustic sensing (DAS), EO/IR imaging, and passive RF reception. The focus of this work is on system-level architecture, signal-flow design, and decision logic rather than on experimental performance validation. Sensor nodes are assumed to operate with synchronized timing, enabling coherent comparison of vibration, Doppler, optical, and electromagnetic signatures, which are fused within a central processing stage. The RAPS layer is described as a Bayesian inference and risk-scoring framework that produces deterministic ACCEPT/REJECT decisions as part of a decision-support architecture. Analytical considerations and illustrative simulations are included to demonstrate feasibility and to motivate design choices, but they do not constitute experimental verification. All performance figures discussed in the manuscript are therefore to be understood as design targets for future experimental evaluation. The presented architecture is intended to serve as a transparent foundation for subsequent field trials, quantitative benchmarking, and comparative studies with existing airspace monitoring systems. Beyond airspace security, the same passive, multi-modal sensing framework may support future applications in environmental and infrastructure monitoring, subject to dedicated experimental validation.

Fields of Study & Subjects

Advanced Measurement and Detection Methods Target Tracking and Data Fusion in Sensor Networks Military Technology and Strategies

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
15 January 2026
Document type
Preprint