Reverse Inference in the Void Framework: Validated Recovery of Void Coordinates from Platform Behavioral Observables
Abstract
Derives and validates a 5-step inversion protocol for recovering void coordinates (O, R, α) from platform behavioral observables. Demonstrates 96.2% recovery accuracy at the void pole under 10% noise using joint least-squares refinement, compared to 20.6% for sequential inversion alone. Provides identifiability analysis showing the measurement problem is well-conditioned precisely where it matters most—high-drift platforms—and establishes formal error bounds for automated platform scoring.
Fields of Study & Subjects
Statistical and numerical algorithms
Inertial Sensor and Navigation
Control Systems and Identification
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 27 February 2026
- Language
- EN
- Document type
- Preprint