A Kalman Filter Approach to Automated Mid-Infrared Beam Mapping: Quantum Cascade Laser Far-Field Patterns

Abstract

Mid-infrared (mid-IR) beams continue to be an important area of study for their applications in trace gas detection and communications, and detailed knowledge of the far-field pattern is critical for remote sensing applications. A novel algorithm for mapping the far-field pattern of mid-IR beams has been developed. The algorithm is based on the Kalman filter, a state estimation tool from robotics. The software and hardware to implement the algorithm, including a three-axis automated stage, have been constructed. Testing of the algorithm was performed by mapping the far-field of a lambda=8000nm quantum cascade laser, demonstrating proper algorithm functionality and producing a far-field pattern map in a 50mm x 50mm x 90mm cube.