In the “crowded” ToF application scenario, how to avoid the interference of multiple ToF measurement signals?

With the explosive application of ToF in terminal markets such as mobile phones, the 3D imaging and sensor market has become a hot spot in the market. Yole expects the global 3D imaging and sensing market to grow from $2.1 billion in 2017 to $18.5 billion in 2023, a compound annual growth rate of 44%.

With the explosive application of ToF in terminal markets such as mobile phones, the 3D imaging and sensor market has become a hot spot in the market. Yole expects the global 3D imaging and sensing market to grow from $2.1 billion in 2017 to $18.5 billion in 2023, a compound annual growth rate of 44%. Automotive electronics (35% CAGR), industrial and commercial applications (12% CAGR) and other high-end markets will also enter rapid growth, led by the consumer market (82% CAGR) aisle.

Compared with the other two solutions of 3D depth vision, the advantages of the current ToF solution in practical applications make the market optimistic about the greater opportunity of ToF in the rapid growth channel. For example: post-processing is not required when calculating the depth of field after the picture is taken, which can avoid delays and save the related costs caused by the use of powerful post-processing systems; The optical field of view as well as the transmitter pulse frequency can be done.

In addition, due to its multiple advantages of being less susceptible to external light interference, small size, fast response speed and high recognition accuracy, ToF has increasingly become the preferred technical solution for 3D vision in both mobile and vehicle applications.

In the “crowded” ToF application scenario, how to avoid the interference of multiple ToF measurement signals?
Using ToF technology can get the absolute value of the object, which has more performance advantages

The application is fully rolled out, and ToF ushered in explosive growth

As one of the main manufacturers of ToF innovative applications, the successful application of ADI’s ToF solutions in vivo NEX cameras has attracted the attention of the industry. At present, the company’s related solutions are more widely used in various application scenarios including automobiles, industries, and portable terminals. . Recently, Li Jia, ADI’s system application engineering manager, vividly pointed out that ToF is ushering in an opportunity for full bloom and explosive growth in a recent keynote speech on “ADI 3D Depth Detection”. She believes that there are mainly the following application opportunities:

The autonomous obstacle avoidance of various robots in automated factories will be an area where ToF can be quickly applied. With the increasing popularity of robotics applications in industrial environments, when robots are in a crowded work environment, they must be able to identify human and machine and machine movements, and respond quickly to avoid equipment and staff injury. If it is solved by lidar, the cost will need to increase by tens of thousands of yuan, and the dual-camera solution requires a lot of calculations and the adjustment of the precise position of the dual-camera. ToF has become the most cost-effective choice to solve the above problems.

ToF realizes face recognition to help building intelligent upgrade. Taking the ADI ToF 3D stereoscopic image automatic door solution with face recognition as an example, the traditional automatic door adopts the principle of infrared reflection, which can only detect whether there is an object in the sensing range, so that animals can also freely enter and exit the mall, causing management problems. troubled. ToF-based solutions can identify human features in space and the relative position distance between people and objects, preventing non-humans (such as animals) from entering commercial stores. In addition, there have been mature solutions for 3D automatic counting of people in commercial spaces in the past, but how to effectively use imaging technology to accurately distinguish the height and weight of people entering and leaving, and at the same time, the error of entry and exit time and height is less than 1%, which has a considerable technical threshold, and ADI’s ToF solution is different from traditional 3D crowd flow solutions, which mostly require the installation of at least two stereo cameras. ADI’s solution requires only one ToF camera lens mount, which is placed above the door frame and has no installation height restrictions.

In the “crowded” ToF application scenario, how to avoid the interference of multiple ToF measurement signals?
Situational virtual map of ToF applied to 3D people flow counting scheme

ToF car reversing images add car driver assistance functions. Combining the image sensor and VGA ToF sensor module with the built-in image processor, ADI’s automotive ToF solution can superimpose the actual image and accurately measure the distance between the object and the car. Compared with the traditional ultrasonic sensing solution, it has a better sensing angle , which can provide a wider range of collision detection and prevention for the reversing system.

ToF application scenarios are increasingly “crowded”, how to avoid interference?

So many application scenarios have opened up one outlet after another for ToF, but related troubles may arise as a result – how can multiple ToF application terminals in the same scenario avoid interference? At the Consumer Electronics Show at the beginning of the year, ADI made a presentation and technical analysis in this regard.

The demo setup is very simple, with two ToF cameras positioned perpendicular to each other, each showing the angle of the participating object in three dimensions, namely height, width and most importantly depth. Each color represents a different distance range, so if field workers get closer to the camera, the color on their hands will change. Likewise, the body of the worker turns a different color if it is farther away from the camera, which means the distance becomes further.

That’s no big deal in itself, as there were many other 3D cameras on Display at CES. But in this demo, ADI will show that multiple ToF cameras are placed face to face without interfering with each other.

ToF cameras capture distance information by emitting laser pulses, then measure the time it takes for the reflected pulses to return to the camera, and multiply the reflection time by the speed of light to obtain the desired distance or depth information. The problem is that if there are other light sources with the same wavelength as this laser, especially other ToF cameras, the measurement will be disturbed. Therefore, the measured time in the presence of any type of light interference is incorrect, which means that the calculated distance information is also incorrect.

In the “crowded” ToF application scenario, how to avoid the interference of multiple ToF measurement signals?
Comparison of the effects of the multi-TOF interference cancellation technology shown at CES2019 (used on the right, not used on the left)

You can see the effect of this interference from other cameras. Note that in this picture the color of the staff has changed, but this is meaningless, as different colors represent different distances, this is due to the reflection of the laser pulses from this ToF camera to the other ToF camera, showing distortion or Incorrect distance data.

On the other hand, this camera does not show this distortion, because we use a patent-pending algorithm that avoids or eliminates all irrelevant light information, using only the light information of its own laser source, so it gives the correct depth information. The other camera does not use this interference cancellation algorithm and will experience distortion, but this camera does not.

Summarize

With the application of ToF in industries, drones and other fields, the stability consideration caused by interference becomes more and more important. On the consumer side, with the increase of various applications, the interference between devices will also be a real and practical problem. Suppose there are multiple drones flying in the air, you certainly don’t want them to collide, you want the avoidance function built into the drone itself, and for that you really need the ToF function.

Likewise, a group of people wearing AR glasses playing a game in the same room, multiple autonomous robots sorting goods in the same large warehouse, or two self-driving cars approaching an intersection at the same time, if ToF cameras can’t eliminate other light sources interference, then the application range of accurate depth measurement using ToF technology will be severely limited. As a result, ADI expects the ability to prevent or cancel jamming in time-of-flight systems will become increasingly important.

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