##Why Some Investors and Researchers Prefer Radar Over Radar, and Thereof Recent Developments in Radar
Direct Answer to Your Question / What This Answer is About
" ... Why does Google use radar? Doesn't LIDAR do everything radar can do? In particular, are there technical advantages with radar regarding object detection and tracking? ... " ~ Crashalot (Stack Exchange user, Opening Oposter)
To begin, some researchers and investors hold reservations about LiDAR.
Lidar is criticised for being expensive and unwieldy.
Advances, such as capturing images from a bird's eye view, and other such improvements, have made radar near-accurate compared to LiDar, while having a cheaper cost. (This will be explored in the technical section, not here.)
This is not conclusive as autonomous cars, radar, and/or LiDAR are being heavily researched.
Another path to take is a hybrid system between radar and LiDAR. (This will be explored in the technical section, not here.)
Start here: 10 Astonishing Technologies That Power Google’s Self-driving Cars (It has slides, so I can't extract the information as easily.)
Eon Musk has very strong opinions against LiDAR. Naturally, he has influence. A while back, radar was unable to detect certain phenomenon, such as in servere certain meteorological disturbances, such as a snow-storm.
This has changed with advances. More efficient systems and pierce the storms. New antenna and radar fabrication technologies are here. Technologies have enabled an such as: higher (millimeter wave) frequencies providing greater resolution with smaller phased-array antennas are now available.
"While not as anti-LiDAR as Musk, it appears researchers at Cornell University agree with his LiDAR-less approach. Using two inexpensive cameras on either side of a vehicle’s windshield, Cornell researchers have discovered they can detect objects with nearly LiDAR’s accuracy and at a fraction of the cost.
The researchers found that analyzing the captured images from a bird’s-eye view, rather than the more traditional frontal view, more than tripled their accuracy, making stereo camera a viable and low-cost alternative to LiDAR." – Crowe, Steve. "Researchers Back Tesla's Non-Lidar Approach To Self-Driving Cars - The Robot Report". The Robot Report, 2019, < https://www.therobotreport.com/researchers-back-teslas-non-lidar-approach-to-self-driving-cars/ >.
"So far in the self-driving realm, automakers and technology companies have been enamored with other sensors for this purpose. Automated cars are currently using cameras and laser sensors known as lidar.
By comparison, radar, which has been on production vehicles for two decades, has been a staple of driver-assist systems for obstacle detection, and until now, not viewed as a tool for localization. Perhaps it's even underappreciated. Venture capital has flowed into lidar and camera-based solutions for automated vehicles; radar has been viewed as a commodity.
'It's unfortunate that's the perception, but it's probably as it should be,' says John Xin, CEO of Lunewave, a startup developing radar-sensing systems. "Over the last 20 years, there's not been a whole lot of game-changing hardware technology coming out of radar sensors."
That's changing. Whether it's global suppliers such as Bosch, or startups such as Lunewave and WaveSense, a recent spinoff from MIT's Lincoln Laboratory, there's fresh innovation being wrung from radar, a technology that first found widespread use during World War II, and was first deployed on production automobiles by supplier Delphi in 1999.
These three companies are rethinking the role of radar in mobility. Here's a rundown of the technology advances underway." – Crowe, Steve. "Researchers Back Tesla's Non-Lidar Approach To Self-Driving Cars - The Robot Report". The Robot Report, 2019, < https://www.therobotreport.com/researchers-back-teslas-non-lidar-approach-to-self-driving-cars/ >.
Is LiDAR, radar, or camera Better for your business: Demystifying the ADAS / AD Technology Mix
Wikipedia is probably the best place to start:--
This paper is one example of advancement in radar:--
"A procedure for radar range calculation is described, reflecting current knowledge of the effects of external natural noise sources, atmospheric-absorption losses, and the refractive effect of the normal atmosphere. The range equation is presented in terms of explicitly defined and readily evaluated quantities. Curves and equations are given for evaluating the quantities that are not ordinarily known by direct measurement. Some conventions are proposed for use in general radar range calculation, including an antenna-noise-temperature curve, minimum-detectable signal-to-noise ratio (``visibility factor'') curves, and a formula for the reflection coefficient of a rough sea. A noise-temperature table and a work-sheet for range calculation are included in the Appendix." – Blake, Lamont V. "Recent advancements in basic radar range calculation technique." IRE Transactions on Military Electronics 2 (1961): 154-164.
There is a technical paper here that compares/constrats Radar and LiDAR:--
One path to take is synergy/a hybrid system between both radar and LiDAR:--
" .... Currently, aerial light detecting and ranging (LIDAR) systems are therefore preferred for the detection and ranging of objects submerged in the sea. LIDAR provides for large area coverage at high speed, but it lacks coherent detection capability, a shortcoming that severely limits system sensitivity and underwater target contrast. In response to this problem, this paper details the merging of RADAR and LIDAR technologies in the constitution of a hybrid LIDAR-RADAR detection scheme. ... " – Mullen, Linda J., et al. "Application of RADAR technology to aerial LIDAR systems for enhancement of shallow underwater target detection." IEEE Transactions on microwave theory and techniques 43.9 (1995): 2370-2377.
Where lives are at stake, back-ups/layers can be argued to be needed. Redundancies/back-ups ("redundancies" in a similar sense to a kidney, per the systems-sciences) can be extremely useful in the case where one system does not pick up shard of ice that makes a car fall off the path.
Sources, References, and Further Reading:--