KEYWORDS: Calibration, Systems modeling, Modulation, Time of flight imaging, Sensors, Imaging systems, Inverse problems, Camera shutters, CMOS sensors, Cameras, Data modeling
Conversely to the continuous wave indirect time-of-flight (CW-iToF) imaging scheme, pulsed modulation ToF (PM-iToF) imaging is a promising depth measurement technique for operation at high ambient illumination. It is known that non-linearity and finite charge-transfer speed impact trueness and precision of ToF systems.1–3 As pulses are no Eigenfunctions to the shutter system, this issue is especially pronounced in pulsed modulation.2, 3 Despite these effects, it is possible to find analytical expressions founded on physical observations that map scenery parameters such as depth information, reflectance and ambient light level to sensor output.3, 4 In the application, the inverse of this map has to be evaluated. In PM-iToF, an inverse function cannot be yielded in a direct manner, as models proposed in the literature were transcendental.3, 4 For a limited range an approximating linearization can be performed to yield depth information.5 To extend the usable range, recently, an alternative approach that indirectly approximates the inverse function was presented.6 This method was founded on 1D doping concentration profiles, which, however, are typically not made available to end users. Also, limitations of the 1D approximation as well as stability are yet to be explored. This work presents a calibration methodology that copes with detector insufficiencies such as finite charge transfer speed. Contrarily to the state of the art, no prior knowledge on details of the underlying devices is required. The work covers measurement setup, a benchmark of various calibration schemes and deals with issues such as overfitting or defect pixels.
This contribution describes the modeling of CMOS image sensors employed in time-of-flight (ToF) sensor systems for 3D ranging applications. Our model relies on the theoretical description of photo-generation, charge transfer including diffusion, fringing field, and self-induced drift (SID). This method makes it possible to calculate the time-dependent charge carrier generation, transfer, and distribution. The employed approach allows elimination not only of irradiance-dependent charge transfer, but also of undesired reflectance effects, and the influence of ambient light through an in-pixel background measurement. Since the sensor is operated with very short integration times it is crucial to accomplish a fast transfer of the generated charge from the photodetector to the sense node, and speedy conversion into an electrical signal at its output. In our case, we employed a lateral drift field photodetector (LDPD), which is basically a pinned photodiode with a built-in drift field formed by a doping gradient. A novel pixel structure is presented which is optimized for a fast charge transfer by the appliance of the shown model. Numerical calculations predict a two times faster charge collection.
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