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Light detection and ranging (LiDAR) is a remote sensing technique with a wide range of industrial applications, including autonomous vehicles, robotics, space exploration, geological mapping, and agricultural observations.
The ongoing revolution in autonomous transport technology requires LiDAR sensors that combine long-range 3D capabilities, high spatial resolution, and fast real-time data acquisition. New research demonstrates how a solid-state microresonator can be used to generate complex frequency-modulated laser beams at multiple wavelengths that permit parallel distance and velocity measurements at an equivalent rate of three megapixels per second.
Earlier LiDAR systems developed for remote sensing applications, such as topographical mapping, meteorological applications, and air pollution monitoring, used pulsed laser beams that were mechanically scanned in two dimensions.
The operation of the pulse-based LiDAR systems relies on time-of-flight (TOF) measurements. The distance to the target object is calculated by recording the time difference between sending a short laser pulse and reception of the light reflected from the object.
Growing Demands Stimulate the Development of Advanced LiDAR Systems
Combining the distance measurement with information about the direction of the reflected laser pulse enables accurate determination of the object's spatial position in three dimensions.
A laser pulse with a duration of several nanoseconds can provide a centimeter-level resolution over distances of up to 300 m. Short pulses also permit the use of high instantaneous peak power (for long-range detection) while maintaining the average power within the eye-safety limit.
However, measuring the velocity of moving objects requires multiple pulses being sent towards the object at a repetition rate that is limited by the optomechanical beam scanner. Implementing amplitude-modulated laser pulses enables the use of the Doppler effect to calculate the speed of the target object based on the frequency shift between the transmitted and received signals.
Autonomous Technology is the Fastest Growing Market for LiDAR Sensors
Commercial availability of the pulse-based LiDAR systems at the onset of the autonomous vehicle development made them, together with onboard radars and video cameras, the engineers' primary choice for obstacle detection.
TOF LiDAR systems scanning up to 256 individual beams in parallel remain the industry-standard today, despite several significant drawbacks such as the high cost of mechanical scanning and interference from solar glare and other light sources.
The ever-increasing reliability and safety requirements for autonomous vehicles and robots, as well as the need for low-cost and large-scale manufacturing, have inspired the researchers to explore different working principles for the next-generation LiDAR systems.
Frequency-Modulated Lasers Allow Quick and Accurate Velocity Measurement
One of the most promising developments in the field is the frequency-modulated continuous-wave (FMCW) LiDAR, where the distance is measured by a repeated linear frequency chirping of a continuous laser beam.
The frequency of the modulated beam changes linearly with time (typically, the chirp duration is slightly longer than the time needed for the light to reach the target object). The reflected signal mixes with the signal used to modulate the measuring beam in a coherent detector that measures how much the frequency changed while the reflected light made its round trip to the object. Multiplying the frequency shift by the chirp rate yields the distance.
A moving object also causes an additional Doppler shift in the frequency of the reflected signal. This is used to extract the object's velocity relative to the LiDAR along the line of sight.
As with pulse-based LiDAR sensors, the incoming angle of the reflected signal indicates the direction to the object, providing accurate three-dimensional localization and velocity measurement with a single measurement.
Autonomous Vehicles Require High-Performance Sensors for Spatial Awareness
A significant advantage of coherent detection and signal processing is that only reflected light consistent with the probing beam is detected, eliminating interference from solar glare and other light sources, including other vehicles' LiDAR sensors.
Self-driving vehicles moving in a fast-changing environment at low visibility require LiDAR systems that can not only detect moving obstacles but also provide high enough spatial resolution to identify the obstacles in their path accurately. In most cases, this is achieved by scanning multiple beams in parallel.
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However, the enhanced performance of FMCW LiDAR comes with a higher cost and complexity associated with high-stability variable-frequency laser sources and sophisticated real-time signal processing. Performing these tasks on multiple laser beams in parallel poses a significant challenge.
Fundamental Research can Revolutionize LiDAR Technology
A research group at the Swiss Federal Institute of Technology in Lausanne (EPFL) led by Prof. Tobias Kippenberg recently made a breakthrough discovery that will pave the way towards cost-effective parallelization of FMCW LiDAR detection.
By coupling a continuous wave laser beam into a ring-shaped silicon nitride microresonator with precise geometry and non-linear refractive index (fabricated at EPFL's Centre of MicroNanoTechnology), the researchers created a solitary localized traveling lightwave called a soliton.
Non-Linear Photonics Circuit Efficiently Manipulates Laser Beams
The soliton's frequency spectrum is determined by the geometry of the microresonator and consists of multiple narrow-band spectral lines (with equidistant frequency spacings) called optical frequency comb. This effectively converts the continuous wave laser beam into a stream of numerous co-existing beams with equally spaced wavelengths.
Prof. Kippenberg and his coworkers were surprised to discover that a frequency chirping of the input beam did not perturb the soliton structure. Instead, the chirp was transferred with high fidelity to each of the generated comb teeth.
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Due to the small size of the microresonator, the comb teeth are spaced 99 GHz apart in the frequency domain, which is enough to spatially separate the resulting beams by using a standard diffraction grating. This allowed the researchers to create up to 30 independent FMCW LiDAR channels, each one inheriting the linear chirping of the input laser beam.
Fast and Accurate LiDAR Sensors for Future Applications
In a recent publication, the Swiss scientists demonstrated that each of the beams in their FMCW LiDAR setup could simultaneously measure the distance and velocity of a target object with a centimeter accuracy at an equivalent sampling rate of 3 Mpixel per second.
Splitting the power of the input laser beam into a manifold of individual beams in the 1550 nm wavelength band makes the new system eye- and camera-safe.
The spectral separation of the channels makes the device immune to channel crosstalk, as well as a very suitable platform for the future development of phased optical arrays based on next-generation integrated photonic circuits.
References and Further Reading
J. Riemensberger et al., (2020) Massively parallel coherent laser ranging using a soliton microcomb. Nature, 581, 164 – 170. Available at: https://doi.org/10.1038/s41586-020-2239-3
M.-G. Suh and K. J. Vahala, (2018) Soliton microcomb range measurement. Science, 359, 884 −887. Available at: https://dx.doi.org/10.1126/science.aao1968
S. Royo and M. Ballesta-Garcia, (2019) An Overview of Lidar Imaging Systems for Autonomous Vehicles. Appl. Sci., 9, 4093. Available at: https://doi.org/10.3390/app9194093
A. Malewar, (2020) Accelerating long-range coherent LiDAR by using photonic circuits. [Online] www.techexplorist.com Available at: https://www.techexplorist.com/accelerating-long-range-coherent-lidar-using-photonic-circuits/32248/ (Accessed on 12 June 2020).
Ecole Polytechnique Fédérale de Lausanne, (2020) Speeding up long-range coherent LiDAR. [Online] www.sciencedaily.com Available at: https://www.sciencedaily.com/releases/2020/05/200513111407.htm (Accessed on 12 June 2020).
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