Non-Markovian Doppler Velocimetry of Optically Propelled Microparticles in Hollow-Core Photonic Crystal Fiber

Doppler velocimetry has been widely used in many aspects of research and in applications. The conventional algorithm for tracking Doppler frequencies can induce large errors in the extracted particle velocity when the signal-to-noise ratio of the Doppler signal is low. Ambiguities in velocity identification are also present when multiple measured objects are moving at similar speeds. Here, we report non-Markovian Doppler velocimetry based on a time–frequency ridge extraction algorithm in which features of the historic trajectories are introduced to track the object's instantaneous velocity. We demonstrate the technique on optically trapped dielectric microparticles in a hollow-core photonic crystal fiber. The technique can improve the accuracy of particle velocity tracking by more than 2 orders of magnitude in the low signal-to-noise regime and is capable of resolving the issue of multiple-particle velocity extraction. The proposed technique can improve the accuracy, sensitivity, and dynamic range of Doppler velocimetry related to vast numbers of applications.