A microcomb-empowered Fourier domain mode-locked LiDAR

Abstract

Light detection and ranging (LiDAR) has emerged as an indispensable tool in autonomous technology. Among its various techniques, frequency modulated continuous wave (FMCW) LiDAR stands out due to its capability to operate with ultralow return power, immunity to unwanted light, and simultaneous acquisition of distance and velocity. However, achieving a rapid update rate with sub-micron precision remains a challenge for FMCW LiDARs. Here, we present such a LiDAR with a sub-10 nm precision and a 24.6 kHz update rate by combining a broadband Fourier domain mode-locked (FDML) laser with a silicon nitride soliton microcomb. An ultrahigh frequency chirp rate up to 320 PHz/s is linearized by a 50 GHz microcomb to reach this performance. Our theoretical analysis also contributes to resolving the challenge of FMCW velocity measurements with nonlinear frequency sweeps and enables us to realize velocity measurement with an uncertainty below 0.4 mm/s. Our work shows how nanophotonic microcombs can unlock the potential of ultrafast frequency sweeping lasers for applications including LiDAR, optical coherence tomography and sensing.

Figures (9)

• Figure 1: Architecture of FDML LiDAR and its application in 3D imaging. a, Experimental setup of the FDML laser, which is calibrated by an integrated Si$_3$N$_4$ soliton microcomb for FMCW ranging. b, Optical spectra of the FDML laser and the 50 GHz soliton microcomb. c, 3D imaging of a diffusive target representing the Tsinghua Gate, which was slightly tilted in the measurement. d, Measured height change of the target and its linear fits along the dashed line in panel c. e, Distribution of the height after subtracting the solid linear fit.
• Figure 1: Linearity measurement for the FDML LiDAR.a, Experimental setup for the ranging linearity measurement. By mounting the mirrors on a linear translation stage, we characterized the linearity measurement accuracy of the FDML LiDAR. The movement of the target was calibrated by a laser interferometer. To cancel the fibre length fluctuations, we added a reference mirror in this setup too. Circ.: circulator, Col.: collimator, BS: beam filter, RM: reference mirror, MMs: measurement mirrors, BPD: balanced photodetector. b, Top: FDML LiDAR measured distance change versus the laser interferometer calibrated distance change. The measurement data were recorded by the 33 GHz Tektronix oscilloscope (bandwidth set at 24 GHz). Bottom: The residual error between the FDML LiDAR and the interferometer measured results. The standard deviation is 0.2 $\mu$m. c, The ranging linearity measurements recorded by the 8 GHz Keysight oscilloscope. The standard deviation of the residual error is 1.0 $\mu$m.
• Figure 2: Microcomb-based frequency calibration for FMCW ranging. a, Heterodyne beat signal between the microcomb and the FDML laser. The shaded region corresponds to the filtered pump and adjacent lines. b, Portion of the calibrated frequency sweep using three different lines under two drive frequencies $f_{m1}$ and $f_{m2}$. The light curves are calculated from the direct retrieved phase change, while the dark curves are calculated from phase change smoothed in a 2 ns window. c, Top: calibrated frequency change after phase smoothing within the whole frequency sweep span. The green curve is a 9th-order polyfit of the frequency sweep signal. Middle: calibrated chirp rate of the FDML laser. Bottom: ratio between the calibrated chirp rates and chirp rates derived from an assumed sinusoidal frequency sweep. d, Measured FMCW ranging signal in the time domain and its instantaneous spectra within a 0.15 $\mu$s window (dashed lines). e, Resampled FMCW signal and the instantaneous spectra. f, FMCW ranging output when using the direct measured signal and the resampled data. The inset shows the linear ranging outputs using the microcomb frequency calibration and an assumed sine-wave for resampling.
• Figure 2: Frequency calibration process.a, We first selected a segment of the recorded calibration signal by a 4.6 $\mu$s window. b, The segmented data was Fourier transformed and bandpass filtered (shaded boxes represent the passband). c, The bandpass filtered spectrum was inverse Fourier transformed back to the domain. The phase of the signal was retrieved by the Hilbert transform (blue curve). The retrieved phase was further smoothed in a 2 ns window (red curve). d, The instantaneous frequency was derived as the derivative of the phase versus time. The blue and red curves show the frequency without and with phase smoothing, respectively. The inset is a zoom in of the dashed box region. e, Retrieved frequency in the full sweep span. The frequencies were calibrated by 74 microcomb lines and were wrapped by $f_{r}$. The shaded box corresponds to the filtered pump and adjacent lines. f, The retrieved frequencies were further unwrapped by the 50.08 GHz comb line spacing (dots). The unwrapped frequencies were fitted by a 9th-order polyfit. This fit was used to resample the time domain signal for ranging.
• Figure 3: Precison of the FDML LiDAR.a, Distance in multiple measurements when the calibration signal was recorded by a 33 GHz oscilloscope and a 8 GHz oscilloscope. The 8 GHz oscilloscope has a larger memory depth and recorded data for a longer time. b, Allan deviation of the measured distance, which scale as $t^{-1/2}$ with the averaging time $t$. Sub-10 nm precision is achieved in less than 10 ms. The inset shows normalized precision scales as $1/{B_{\rm RF}}$ with $B_{\rm RF}$ being the digitizer bandwidth. c, Normalized precision scales linearly with the ranging resolution. d, Time domain FMCW ranging signal with a return power of 4 pW. e, FMCW ranging output using the direct time domain signal and the microcomb-calibrated signal with a 4 pW return power. f, Measured normalized ranging precision with different return powers (local oscillator power was 75 $\mu$W). The normalized precision scales as $P^{-1/2}$ for return powers $P<$10 nW. The inset shows SNR under different return powers.