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Für LiDAR Polygonspiegel und Scannermotoren Vol.2

Für LiDAR Polygonspiegel und Scannermotoren Vol.2

 

Kapitel 6

Why do we recommend POLYGON for LiDAR?

Advantages of using “Polygon LiDAR”

Next, let's look at the optimal method of LiDAR. The LiDAR has several methods, and we compared the performance of the solid-state MEMS system with the polygon system using the polygon laser scanner we are involved in, and the millimeter-wave radar. Refer to the following summary table.

 Sensing distanceBeam lineResolutionRepeat-
ability
Scan angle SizeMain uses
Millimeter-
wave rader
~ 200 m 1 ~ few ~ 1 m ~ 20° ACC, LKAS
Polygon
LiDAR
~ 250 m Thousands to
tens of thousands
few cm 120° Distance / Position
detection
MEMS
LiDAR
~ 180 m Thousands to
tens of thousands
few cm 90° Distance / Position
detection

As shown in the table above, the millimeter-wave radar has a scanning angle of only 20 degrees ... (in comparison, Polygon LiDAR is 120 degrees!) Also, the millimeter-wave radar has only one to several lines of beams, which is significantly inferior to the thousands to tens of thousands of Polygon LiDAR lines. Next, it is the MEMS LiDAR that is compared well with the Polygon LiDAR. MEMS LiDAR has a major disadvantage in that it is not repeatable at all. A Study on the MEMS LiDAR is written in the previous article Chapter 2.

POLYGON is an ideal solution for LiDAR long-distance detection

From the charts above, Polygon LiDAR can be said to be a superior method to other methods in terms of sensing range, number of beam lines, resolution, repeatability and scan angle. Therefore, it sure be concluded that POLYGON is the best, particularly in LiDAR for long-distance detection.

On the other hand, Polygon LiDAR has a mechanical structure that requires a motor to rotate the polygon mirror, so it tends to be larger than other methods. Regardless of such a general image,
since we have been actively developing also downsizing while maintaining high specifications, our polygon mirrors and polygon laser scanners are widely considered from commercial vehicles (taxis, trucks, self-driving robots, etc.) to passenger cars.
 

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