Teardown Analysis of Panasonic's 3D Time-of-Flight Depth Sensing Camera Module with Lenovo Phab2Pro and Oppo RX17 Pro Comparisons

DUBLIN, Sept. 3, 2019 /PRNewswire/ -- The "Panasonic's 3D Time-of-Flight Depth Sensing Camera Module" report has been added to ResearchAndMarkets.com's offering.

This report is focused on the analysis of the 3D depth-sensing camera, comprising the near-infrared (NIR) ToF camera module, and the flood illuminator. Relying on Panasonic's knowledge of Charge Coupled Device (CCD) image sensors, the MN34906 has the smallest known pixel size for any ToF image sensor made with a CCD process on the market. Indeed, with a very low number of metal layers, Panasonic was able to produce a very cost-efficient image sensor with enough resolution and accuracy for a consumer application. Coupled with a standard flood illuminator based on vertical cavity surface emitting laser (VCSEL), the system has a very small form factor GS approach.

For 3D depth sensing, three approaches have been considered in consumer applications: active stereo vision (AS), structured light (SL) and Time-Of-Flight (ToF) sensing. SL was developed by Apple, which brought it to the market for the first time in 2017. It's based on a complex system requiring several components, including a Global Shutter (GS) image sensor and a dot projector. The latter has been considered difficult and expensive to make due to the precision required. The ToF approach could be less complex and less expensive. You just need a ToF Image sensor and a flood illuminator to bring depth sensing to a system. In this field, only three known companies have solutions.

In 2016, Infineon was the first to bring out its 3D ToF image sensr, developed with pmd, for the Google Tango Project. Today, Sony has the major share of the market with several designs wins starting from low-end smartphones, such as the Oppo RX17 Pro in 2018, to high-end ones, such as the Samsung S10 5G and Huawei P30 Pro in 2019. This year, Panasonic has surprised the market with a new ToF Image Sensor in the Vivo Nex Dual Display.

Key Topics Covered:

1. Overview/Introduction

2. Panasonic Company Profile

3. Vivo Nex Dual Display - Teardown and Market Analysis

4. Physical Analysis

• Physical Analysis Methodology
• 3D Sensing System Disassembly and Cross-Section
• NIR Camera ToF Sensor
• View, dimensions and cross-section
• NIR Camera ToF Sensor Die
• View, dimensions, pixels, delayering and main block IDs
• Process and cross-section
• Flood Illuminator Module Disassembly and Cross-Section
• NIR VCSEL Dies
• View, and dimensions
• Die processes and cross-sections
• Physical Data Summary

5. Physical Comparison: Lenovo Phab2Pro and Oppo RX17 Pro

• System Integration
• NIR Camera Module and ToF Sensor
• Flood Illuminator and VCSEL

6. Manufacturing Process Flow

• Die Fabrication Unit: NIR Image Sensor, NIR VCSEL
• NIR Image Sensor and VCSEL Process Flow

7. Cost Analysis

• Cost Analysis Overview
• Supply Chain Description and Yield Hypotheses
• NIR Image Camera Module Cost
• Front-end (FE), microlens and total FE cost
• Wafer and die cost
• Lens module and assembly cost
• NIR Flood Illuminator Cost
• Front-end (FE) cost
• Front-end cost per process step
• Wafer and die cost
• Assembly cost

Companies Mentioned

• Apple
• Google
• Huawei
• Infineon
• Lenovo
• Panasonic
• Samsung
• Sony

For more information about this report visit https://www.researchandmarkets.com/r/jvv564

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