Fig. 1. Multichannel time-domain wavelength division multiplexing (TWDM) FMCW LiDAR. (a) Schematic layout of the application of the TWDM-FMCW LiDAR. EDFA, erbium-doped optical fiber amplifier; SMF, single-mode fiber; CIR, circulator; COL_1-N, collimator; BPD, balanced photodetector; DSO, digital sampling oscilloscope; FPC, fiber polarization controller. (b) Schematic diagram of LiDAR measurement signal waveform. The upper image is the original measurement signal, and the lower image is the time-domain wavelength division multiplexed measurement signal. (c) Principle of the FMCW LiDAR measurement and schematic diagram of frequency variation. The solid line represents the local oscillator light signal, and the dashed line represents the returned light signal. B represents the modulation bandwidth, T represents the period duration, Δt represents the time delay caused by distance, and Δf_D represents the frequency shift of the returned light signal caused by the Doppler effect, resulting in two beat frequency signals within one scanning period, denoted as f_up and f_down, respectively. (d) Principle of MEMS optical switch and photos of device’s exterior and interior configurations.

Fig. 2. Illustration of the time-domain wavelength division multiplexing technology combined with the optical switch. The continuous time-domain switching of the optical switch divides the FMCW into multiple non-overlapping measurement channels. By adjusting the switching period, the bandwidth of the TWDM channels can be modified.

Fig. 3. Multifunctional high-precision laser coherent ranging. (a) Experimental setup. The measurement path employs a Fizeau common-path interferometer structure, with a semi-transparent, semi-reflective thin-film coated on the fiber end face, providing 50% transmission and 50% reflection of the light intensity. The XL-80 laser interferometer measurements serve as the accuracy reference. CIR, circulator; COL, fiber collimator; PBS, polarizing beamsplitter. (b) Signal processing and suppression of laser modulation nonlinearity. The left plot shows the measurement path signal (purple) and the auxiliary path signal (orange). The right plot presents the extracted peak points of auxiliary sampling signal and the measurement signal after resampling.

Fig. 4. Measurement signal spectrum before and after resampling. Blue represents the original spectrum and red represents the spectrum after nonlinearity suppression.

Fig. 5. Overall distance testing results. (a) Results of the 20 mm step experiment and standard deviation. (b) Linearity results and residuals. (c) Results of 10 s repeated distance measurements at a single position. (d) Allan deviation of the results plotted against the averaging time. (e) Comparison with traditional FMCW LiDAR measurement results.

Fig. 6. Distance testing results for each channel. (a) Spectral information of each channel’s measurement at a fixed distance. (b) Residuals for each channel in the 20 mm step experiment. (c) Distance measurement results for each channel in the 20 mm step experiment.

Fig. 7. Axial localization 3D imaging. (a) Experimental setup. The target consists of two vertically placed hardboards spaced approximately 30 cm apart, with the first hardboard having a “TIF” hollow pattern. (b) 3D image obtained by scanning the beam array in the horizontal direction. (c) and (d) Centimeter-level distance measurement precision for each LiDAR channel projected along the X-axis and Y-axis, respectively. (e) Histogram of the spectral distribution successfully detecting the front and rear planes of the target.

Fig. 8. 3D imaging in actual scenes. (a) Experimental setup and the actual scene of the corridor stairs. (b) Visualization of the measured point cloud, with the color of the points indicating depth information along the Z-axis. (c) Two-dimensional gradient information. (d) Time-frequency information of the LiDAR multichannel measurement process across the steps.