aeva lidar wavelength
One way of describing technology maturity is a scheme developed by NASA in the 1970sIn the case of TOF LiDAR, we believe the components and systems are at TRL 8, while the FMCW components and systems are at TRL 4. Even if it required two consecutive shots to get velocity on a target at 1km, it’s easy to see how that would be superior to a single shot at 100m given a common frame rate of 20Hz and typical vehicle speeds.Spurious reflections arise in both TOF and FMCW systems. Even a shorter 1us FMCW pulse can be corrupted by high intensity clutter 150m away. And LiDAR technology continues to evolve. The multitude of potential sidelobes in FMCW lead to artifacts that impact not just local range samples, but the entire returned waveform for a given pulse!A potentially stronger interference source is a reflection caused by either a windshield or other first surface that is applied to the LiDAR system. By reading the way this far more complex signal bounces off … Aeva's 4D Lidar design doesn't have this problem, which means when the market is finally ready manufacturers can scale up quickly, safely, and without worrying that one of their mission critical sensors could get jammed at an intersection.With purchase orders already in place, it seems many auto manufacturers have made up their minds that lidar will be part of their autonomous technology stack--at least for the first generation. This doubles the dwell time required per shot above and beyond that already described in the previous paragraph. The new developments are the MEMS, which have also been previously used in virtually all air bag and pressure sensors in automotive, as well as Gatlin guns, missile seekers, and laser resonator q-switches in the military. The total receiver cost will favor a TOF system.In a typical TOF system, incoherent detection (simple amplitude peak detection) takes place and optical elements only have to be within one-quarter of a wavelength (so called λ/4). To provide context, a 10us FMCW pulse spreads light radially across 1.5km range. LiDAR is more precise and better at detecting smaller objects compared to radar, works very well at night compared to camera systems, and has a longer range. It is well known that phased array beam steering degrades (creates spatial sidelobes) very quickly with frequency shifts of the laser beam. Traditional mechanical or other solid state lidars use an array of lasers to build a point cloud of objects in its path, and they measure an object's speed and direction by calculating movement between frames.
This randomizes the electric field of the signal return on the photodetector surface complicating (decohering) optical mixing.Lastly, due to the nature of the time domain processing vs frequency domain processing, the handling of multi-echoes—even with high dynamic range—is a straightforward process in TOF systems. Whereas, it requires significant disambiguation in FMCW systems.
Aeva is able to skip the calculation process using only a single beam and coded signals that detect frequency changes to calculate velocity--a sort of optical version of doppler radar. Furthermore, nonlinearities in the receiver front end (so-called spurious-free dynamic range) will limit the effective overall system sidelobe levels achievable due to: compression and ADC spurs (third order intercepts); phase noise;In contrast, a typical Gaussian TOF system, at 2ns pulse duration, has no time-based sidelobes whatsoever beyond the few cm of the pulse duration itself. Aeva’s LiDAR-on-chip will cost less than $500 at scale, in contrast to the several tens of thousands of dollars for today’s LiDAR sensors. The combination of a beam steering mechanism that depends on the laser being a constant intensity and constant wavelength, while the ranging mechanism depends on sweeping the frequency (wavelength) of the laser, doesn’t work well for traditional FMCW approaches. However, it has a number of disadvantages. We invite anyone evaluating LiDAR systems to carefully inspect the point cloud quality of TOF vs FMCW under various driving conditions for themselves. Even with the use of ASICs, the complexity of FMCW systems is several times the complexity (and cost) of the processing required for TOF.FMCW has a low technical readiness level, and Optical Phased Arrays have an even lower technical readiness level (roughly TRL 3 with experimental proof of principle and is not usable at scale to the extent needed for FMCW). AEye… ← AEye Unveils 4Sight™, a Breakthrough LiDAR Sensor That Delivers Automotive Solid-State Reliability and Record-Breaking Performance Even if a company decides to go with an end-to-end machine learning self-driving platform, there isn't any reason that lidar couldn't be one of the sensors the system uses. If a second laser shot is taken a short period later, say 50us after the first, the target will only have moved ~1.75mm during that interval.
True, FMCW allows low cost photodetectors, like PINs, whereas TOF often use APDs and other more costly detectors. The major scalability shortcomings of FMCW systems include the low shot rate due to the laser chirp pulse stretching, and the high-speed ADC and FPGA required to process returns. Textiles (cotton and polyester, wet or dry, 905 nm or 1550 nm) have a lidar reflectance in the range of 30% to 60%. We believe this path can take another 10 years to reach usable maturity.AEye believes that high shot-rate, agile-scanning TOF systems serve the needs of autonomous vehicle LiDAR more effectively than FMCW when cost, range, performance, and point cloud quality are important.
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