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Diffractive Retroreflector for Distributed Sensing

Anne R. Kroo, Olav Solgaard

TL;DR

The paper addresses remote sensing with passive, distributed nodes by encoding sensor state into the retroreflected diffraction pattern of a modified corner cube. It proposes a coherent, single-ended optical readout that interferes a reference path with a sensor-modulated path, read by a camera, enabling phase- and amplitude-based sensor state recovery without onboard electronics. The authors develop a ray-tracing near-field model, diffraction analysis, and a two-stage inverse estimator (lookup-table initialized LM) to reconstruct sensor phase from diffraction imagery, including scalable arrays. The approach promises scalable, robust, low-maintenance deployments for chemical, biological, and physical sensing in varied orientations, with potential for optimized fabrication and optically addressable encoders.

Abstract

We introduce a modified corner cube reflector that encodes information from passive optical sensors in its retroreflected diffraction pattern, enabling remote sensor-state measurement over a single-ended optical link. The design interferes a reference path and a sensor-modulated path within the retroreflected beam to produce an interferometric signal suitable for reading out phase and amplitude variations with a squarelaw camera. This enables sensor-state determination in arbitrarily oriented passive nodes, extending coherent interferometric read out of chemical, biological, and physical sensors to scalable, robust, and inert field deployments.

Diffractive Retroreflector for Distributed Sensing

TL;DR

The paper addresses remote sensing with passive, distributed nodes by encoding sensor state into the retroreflected diffraction pattern of a modified corner cube. It proposes a coherent, single-ended optical readout that interferes a reference path with a sensor-modulated path, read by a camera, enabling phase- and amplitude-based sensor state recovery without onboard electronics. The authors develop a ray-tracing near-field model, diffraction analysis, and a two-stage inverse estimator (lookup-table initialized LM) to reconstruct sensor phase from diffraction imagery, including scalable arrays. The approach promises scalable, robust, low-maintenance deployments for chemical, biological, and physical sensing in varied orientations, with potential for optimized fabrication and optically addressable encoders.

Abstract

We introduce a modified corner cube reflector that encodes information from passive optical sensors in its retroreflected diffraction pattern, enabling remote sensor-state measurement over a single-ended optical link. The design interferes a reference path and a sensor-modulated path within the retroreflected beam to produce an interferometric signal suitable for reading out phase and amplitude variations with a squarelaw camera. This enables sensor-state determination in arbitrarily oriented passive nodes, extending coherent interferometric read out of chemical, biological, and physical sensors to scalable, robust, and inert field deployments.
Paper Structure (11 sections, 10 equations, 10 figures)

This paper contains 11 sections, 10 equations, 10 figures.

Table of Contents

  1. Introduction
  2. Methods
  3. Methods Overview
  4. Ray Tracing for the Near Field Pattern
  5. Results
  6. Diffraction Patterns
  7. Phase Sensitivity
  8. Inverse Estimator Design and Optimization
  9. Arrays of Corner Cubes
  10. Discussion
  11. Back matter

Figures (10)

  • Figure 1: System design of distributed sensor system with transceiver architecture and remote corner cube sensor and close up of corner cube with embedded sensor with corresponding coordinate system.
  • Figure 2: Labeled corner reflectors with named triangular faces. (a) the regions show light exiting the CCR that hit the sensor on the numbered bounce (green-3rd, blue-2nd, red-1st). (b) naming scheme for describing bounces at normal incidence. (c) demonstration of the two unique cases of light incident a triangle in the CCR propagating through the device.
  • Figure 3: Diffraction patterns with phase variation at normal incidence - from left to right diffraction patterns from device with sensor phase values of 0, $\pi/2$, and $\pi$
  • Figure 4: Diffraction patterns with amplitude variation at normal incidence - from left to right diffraction patterns from device with sensor reflection of values of 1, 1/2, and 0 relative to the reference mirror surface
  • Figure 5: Three dimensional visualization of the diffraction pattern with linear height and logarithmic colors visualizing patterns for 0 phase shift (left) and $\pi$ phase shift (right)
  • ...and 5 more figures