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Table 2: System-level components of 3D Time of Flight cameras
modulation frequency is that the phase wraps around faster, meaning the range that can be unambiguously measured is shorter. The common way to get around this limitation is to use multiple modulation frequencies that wrap around at diff erent rates. The lowest modulation frequency provides a large range with no ambiguity but larger depth errors (noise, multipath interference, etc.), while higher modulation frequencies are used in tandem to reduce depth errors. An example of this scheme with three
diff erent modulation frequencies is shown in Figure 3. The fi nal depth estimate is calculated by weighting the unwrapped phase estimates for the diff erent modulation frequencies, with higher weights being assigned to the higher modulation frequencies. If the weights for each frequency are chosen optimally, the depth noise is inversely proportional to the root mean square (rms) of the modulation frequencies chosen in the system. For a constant depth noise budget, increasing the modulation frequencies enables reducing the integration time or the illumination power.
Other system aspects critical to performance There are many system features to consider when developing a high-performance ToF camera, some of which are covered briefl y here:
Image sensor
The image sensor is a key component in a ToF camera. The eff ects of most depth estimation nonidealities (for example, bias, depth noise, and multipath artifacts) are reduced when the average modulation frequency of the system increases. It is
14 October 2021 | Automation
therefore important that the sensor has a high demodulation contrast (ability to separate photoelectrons between Tap A and Tap B) at high modulation frequency (hundreds of MHz). The sensor also needs to have a high quantum effi ciency (QE) in the near-infrared wavelengths (for example, 850nm and 940nm), so that less optical power is needed to generate photoelectrons in the pixel. Finally, a low readout noise helps with the dynamic range of the camera by allowing to detect low return signals (far or low refl ectivity objects).
Illumination
The laser driver modulates the light source (for example, VCSEL) at high modulation frequency. In order to maximise the amount of useful signal at the pixel for a given optical power, the optical waveform needs to have fast rise and fall times with clean edges. The combination of laser, laser driver and PCB layout in the illumination subsystem are all critical to achieve this. There is also some characterisation required to fi nd the optimal optical power and duty cycle settings to maximise the amplitude of the fundamental in the Fourier transform of the modulation waveform. Finally, the optical power also needs to be delivered in a safe manner with some safety mechanisms built in at the laser driver and system level to ensure Class 1 eye-safety limits are respected at all times.
Optics
Optics play a key role in ToF cameras. ToF cameras have certain distinct characteristics that drive special optics requirements. Firstly, the fi eld of illumination of the light source should match the fi eld of view of the lens for optimum effi ciency. It is also important
that the lens itself should have high aperture for better light collection effi ciency. Large apertures can lead to other tradeoff s around vignetting, shallow depth of fi eld and lens design complexity. A low chief ray angle lens design can also help reduce the band-pass fi lter bandwidth, which improves ambient light rejection and therefore improves outdoor performance. The optical subsystem should also be optimised for the desired wavelength of operation (for example, anti-refl ective coatings, band-pass fi lter design, lens design) to maximise throughput effi ciency and minimise stray light. There are also many mechanical requirements to ensure optical alignment is within the desired tolerances for the end application.
Power management
Power management is also critically important in a high-performance 3D ToF camera module design. The laser modulation and pixel modulation generate short bursts of high peak currents, which places some constraints on the power management solution. There are some features at the sensor IC level that can help reduce the peak power consumption of the imager. There are also power management techniques that can be applied at the system level to help ease the requirements on the power source (for example, battery or USB). The main analogue supplies for a ToF imager typically require a regulator with good transient response and low noise.
Depth processing algorithm Finally, another large part of the system- level design is the depth processing algorithm. The ToF image sensor outputs raw pixel data from which the phase information needs to be extracted. This operation requires diff erent steps that include noise fi ltering and phase unwrapping. The output of the phase unwrapping block is a measurement of the distance travelled by the light from the laser to the scene and back to the pixel, often called range or radial distance.
The radial distance is generally converted into point cloud information, which represents the information for a particular pixel by its real-world coordinates (X,Y,Z). Often, end applications only use the Z image map (depth map) instead of the full point cloud. Converting radial distance into point cloud requires knowing the lens
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