Imaging Device Quasi-Gray Code Interference Rejection
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Solution Overview
Problem
Current imaging devices using time-of-flight principles for depth sensing face challenges in accurately calculating distances due to interference and noise, particularly in multi-camera systems and environments with varying ambient light conditions.
Innovation Solution
The implementation of a signal processor that randomly applies quasi-Gray code signals to generate correlation signals, measures pixel signals, and calculates distances based on these signals, while also using noise cancellation techniques and differential decoding to improve accuracy and reject ambient light and multi-camera interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple cameras are used for depth sensing, then the coverage and sensing capability are improved, but interference between cameras increases and measurement precision deteriorates
Solution Approach 1:
The patent divides the sensing process into distinct segments by assigning different quasi-Gray code patterns to different cameras and time periods. Each camera receives unique control signals during specific time windows, segmenting the interference problem into manageable parts that can be processed independently and combined without mutual contamination.
Solution Approach 2:
The patent implements periodic modulation of light sources with different frequencies and patterns for different cameras. By using periodic quasi-Gray code sequences with distinct characteristics, the system creates time-periodic signal structures that allow each camera's measurements to be distinguished from others, enabling interference rejection through frequency and pattern discrimination.
2Adaptability or versatility
If ambient light conditions vary, then the imaging device must adapt to different environments, but noise and interference increase reducing measurement precision
Solution Approach 1:
The patent converts ambient light interference into a beneficial signal by using correlation techniques. The system correlates received signals with known transmitted quasi-Gray code patterns, allowing the desired signal to be extracted while ambient light acts as uncorrelated noise that averages out. This transforms the harmful ambient light into a background that can be statistically rejected.
Solution Approach 2:
The patent changes the temporal and spectral parameters of the modulated light signals to distinguish them from ambient light. By using specific modulation frequencies, duty cycles, and quasi-Gray code patterns, the system creates signal characteristics that are fundamentally different from ambient light, enabling separation through parameter-based filtering and correlation detection.
3Measurement precision
If correlation signals are generated using multiple sets of control signals, then distance measurement accuracy is improved, but device complexity increases
Solution Approach 1:
The patent performs preliminary encoding of the control signals using quasi-Gray code patterns before the actual measurement process. This preliminary structuring of signals with known mathematical properties allows for simplified correlation-based decoding later. The pre-encoded signals contain built-in error correction and interference rejection capabilities that reduce the complexity of post-processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of distance calculations by reducing noise and interference, improving signal-to-noise ratio, and effectively handling varying ambient light conditions, thereby improving the precision of depth sensing in imaging devices.
Implementation Method 1
a ToF depth sensor includes a light source and an imaging device including a plurality of pixels for sensing reflected light. In operation, the light source emits light (e.g., infrared light) toward an object or objects in the scene, and the pixels detect the light reflected from the object or objects. The elapsed time between the initial emission of the light and receipt of the reflected light by each pixel may correspond to a distance from the object or objects.
Implementation Method 2
indirect ToF imaging devices may measure the phase delay between the emitted light and the reflected light and translate the phase delay into a distance
Implementation Method 3
the pixels detect the light reflected from the object or objects
Data Source
AI summary
An imaging device includes a pixel, and a signal processor configured to randomly apply a first set of signals including a first driving signal applied to a first light source, and a first set of control signals applied to the pixel that adhere to a quasi-Gray code scheme to generate first through eighth correlation signals based on light output from the first light source according to the first driving signal and reflected from an object. The signal processor is configured to randomly apply a second set of signals including a second driving signal applied to the first light source, and a second set of control signals applied to the pixel that adhere to the quasi-Gray code scheme to generate ninth through sixteenth correlation signals based on light output from the first light source according to the second driving signal and reflected from the object.