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Technology Stocks : Ouster (OUST)
OUST 28.42-10.4%2:48 PM EST

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From: Sam1/1/2021 4:39:19 PM
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This is from October but it's still interesting.

Lidar used to cost $75,000—here’s how Apple brought it to the iPhone How Apple made affordable lidar with no moving parts for the iPhone.
Timothy B. Lee - 10/15/2020, 12:40 PM

At Tuesday's unveiling of the iPhone 12, Apple touted the capabilities of its new lidar sensor. Apple says lidar will enhance the iPhone's camera by allowing more rapid focus, especially in low-light situations. And it may enable the creation of a new generation of sophisticated augmented reality apps.

Tuesday's presentation offered little detail about how the iPhone's lidar actually works, but this isn't Apple's first device with lidar. Apple first introduced the technology with the refreshed iPad in March. And while no one has done a teardown of the iPhone 12 yet, we can learn a lot from recent iPad teardowns.

Lidar works by sending out laser light and measuring how long it takes to bounce back. Because light travels at a constant speed, the round-trip time can be translated into a precise distance estimate. Repeat this process across a two-dimensional grid and the result is a three-dimensional "point cloud" showing the location of objects around a room, street, or other location.

A June analysis by System Plus Consulting found that the iPad's lidar sends out light using an array of vertical cavity surface-emitting lasers (VCSELs) made by Lumentum. It then detects the return flash using an array of sensors called single-photon avalanche diodes (SPADs) supplied by Sony. I'll explain what these are in the next section.

I found Apple's announcement particularly interesting because I've been working on a story about companies that are using the same combination of technologies—VCSEL lasers and SPAD detectors—to build much more powerful lidar for the automotive market. One of the big selling points of VCSELs and SPADs is that they can be created using conventional semiconductor fabrication techniques. As a result, they benefit from the huge economies of scale in the semiconductor industry. As VCSEL-based sensors become more common, they are likely to steadily get cheaper and better.

Two of the companies working on high-end VCSEL-based lidar—Ouster and Ibeo—have already gotten more traction than most companies in the crowded lidar business. Apple's decision to adopt the technology—and the possibility that other smartphone vendors could follow Apple's lead—will provide them with a nice tailwind in the coming years.

VCSELs helped Apple make radically simpler lidar

The first three-dimensional lidar sensor was introduced by Velodyne more than a decade ago. The spinning unit cost around $75,000 and was significantly larger than a smartphone. Apple needed to make lidar sensors radically cheaper and smaller in order to put one in each iPhone, and VCSELs helped the company do it.

What's a VCSEL? If you're building a laser using conventional semiconductor fabrication techniques, you have two basic options. You can make a laser that transmits light out the side of the wafer (known as an edge-emitting laser) or from the top (a vertical cavity surface emitting laser, or VCSEL).

Traditionally, edge-emitting lasers have been more powerful. VCSELs have been used for decades in everything from optical mice to optical networking gear. They were traditionally considered unsuitable for high-end applications where a lot of light was needed, but VCSELs have become more powerful as the technology has matured.

Making an edge-emitting laser typically requires cutting the wafer to expose the emitter. This adds to the cost and complexity of the manufacturing process and limits the number of lasers that can be made on one wafer. by contrast, VCSELs emit light perpendicular to the wafer, so they don't need to be individually cut or packaged. This means that a single silicon chip can hold dozens, hundreds, or even thousands of VCSELs. In principle, a chip with thousands of VCSELs shouldn't cost more than a few dollars when produced at large scale.

continues at arstechnica.com
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