Improved displacement sensing by spectral processing of laser self-mixing interferometry signal phase

In Laser self-mixing interferometry (SMI), phase unwrapping methods are widely utilized for high-resolution displacement measurements. In this work, a Time-frequency signal processing (TFSP) method for SMI based displacement retrieval is analyzed. Its limitations are identified, and an improved and more robust version of TFSP is proposed for enhanced resolution and better sensing in a non-ideal situation. By rectifying the phase inversion errors present in TFSP, the proposed work can process the laser phase more efficiently than TFSP. Furthermore, the proposed work can also accommodate significant amplitude fading of laser feedback signal by applying the Hilbert transform based signal processing technique, making it robust than TFSP.The proposed work demonstrates that the Hilbert processing technique and improved phase estimation shows approximately 90% improvement over the TFSP method for simulated SMI signals from different feedback regimes and amplitude variations. Additionally, experimental results for various C values indicate an average improvement of around 29% compared to TFSP.Lastly, FPGA based emulation of ITFSP is performed for embedded sensing applications. While operating at 180 MHz, the ITFSP can measure a maximum target velocity of 4.5 m/s.The development of such a robust and high-resolution method is a critical step towards a compact laser-based sensor for highresolution applications, even for non-cooperative targets and rough environments causing laser light fading.