Mode-noise-based high-resolution depth imaging LiDAR

In this work, we demonstrate a high-range-resolution LiDAR detection scheme based on mode noise characteristics. This approach achieves millimeter-level point-cloud imaging at low sampling rates below 100 MHz, effectively reducing the dependence of high-resolution ranging on high sampling rate digitization and broad tuning bandwidths, thus significantly lowering system costs. The proposed scheme eliminates the need for external modulation and has minimal requirements for the laser linewidth. By employing an unbalanced interferometer, the system exploits intrinsic laser frequency fluctuations, converting them into broadband and sufficiently intense mode noise suitable for ranging. Through differential processing, the two time-delayed mode noise signals undergo coherent cancellation, which yields pronounced frequency dips at specific locations within the power spectrum. Theoretical analysis reveals a direct relationship between the center frequencies of these dips and the relative time delay. By utilizing nonlinear curve fitting to extract the dip profiles, we achieve high-precision center frequency extraction, enabling direct distance retrieval in the frequency domain. Experimentally, the system achieves millimeter-level ranging performance at an exceptionally low sampling rate of only 61.5 MHz. Specifically, the ranging accuracy was measured to be 1.3 mm at a detection distance of 7 m and 3.07 mm at 20 m while successfully resolving adjacent targets separated by a small gap of 4 mm.