Time-of-Flight Camera Depth Measurement via Frequency Sweep
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Solution Overview
Problem
Conventional time-of-flight cameras face issues with phase-wrapping, multi-path interference, and low signal-to-noise ratio, which affect the accuracy of depth measurement.
Innovation Solution
A frequency-domain approach is employed, where a time-of-flight camera extracts optical path length from a dual frequency of a cross-correlation signal, avoiding phase-wrapping and multi-path interference, and accurately measuring path length even in low SNR environments by using a sweep of modulation frequencies and spectral analysis techniques like FFT.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If phase-sensing is used to determine object depth, then depth measurement capability is achieved, but phase-wrapping causes measurement ambiguity
Solution Approach 1:
The patent applies periodic action by using multiple modulation frequencies (sweeping through different frequencies) to illuminate the scene. By measuring phase at multiple periodic intervals (frequencies), the system can disambiguate the wrapped phase values and determine unambiguous depth, resolving the phase-wrapping problem while maintaining depth measurement capability
Solution Approach 2:
The patent changes the modulation frequency parameter over time (sweeping through a range of frequencies). This parameter change allows the system to capture phase information at multiple frequency points, which can then be used to resolve the ambiguity caused by phase-wrapping and achieve accurate depth measurement
2Measurement precision
If phase-sensing is used to determine object depth, then depth measurement is achieved, but multi-path interference corrupts the measurement
Solution Approach 1:
By using multiple modulation frequencies in a periodic sweep, the system can distinguish between direct-path and multi-path reflected light based on their different phase characteristics at various frequencies. This allows the system to identify and reject corrupted measurements from multi-path interference while maintaining accurate depth measurement for direct-path light
Solution Approach 2:
The system uses feedback by comparing phase measurements across multiple frequencies to identify consistent depth values. When multi-path interference is present, the phase measurements will be inconsistent across frequencies, allowing the system to detect and correct for the interference through iterative refinement of the depth estimate
3Measurement precision
If conventional phase-ToF sensing is used, then depth measurement is achieved, but accuracy deteriorates in low signal-to-noise ratio conditions
Solution Approach 1:
By performing measurements at multiple modulation frequencies in a periodic sweep, the system accumulates more information about the scene. This redundant information allows for better signal averaging and noise reduction, improving measurement reliability in low SNR conditions while maintaining depth measurement accuracy
Solution Approach 2:
The system performs preliminary measurements at multiple frequencies before final depth calculation. This preliminary action of gathering data across the frequency sweep allows the system to pre-process and filter noise effects before computing the final depth value, thereby improving accuracy in low SNR environments
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 method effectively resolves phase-wrapping and multi-path interference, providing accurate optical path length and depth measurements, even in challenging SNR conditions, enhancing the camera's precision and reliability.
Implementation Method 1
The optical signal returning to the camera sensor exhibits a shift in phase corresponding to the propagation distance of the signal, which allows object depth to be calculated
Implementation Method 2
conventional time-of-flight (ToF) cameras rely on phase-sensing to determine object depths
Data Source
AI summary
In some implementations, scene depth is extracted from dual frequency of a cross-correlation signal. A camera may illuminate a scene with amplitude-modulated light, sweeping the modulation frequency. For each modulation frequency in the sweep, each camera pixel may measure a cross-correlation of incident light and of a reference electrical signal. Each pixel may output a vector of cross-correlation measurements acquired by the pixel during a sweep. A computer may perform an FFT on this vector, identify a dual frequency at the second largest peak in the resulting power spectrum, and calculate scene depth as equal to a fraction, where the numerator is the speed of light times this dual frequency and the denominator is four times pi. In some cases, the two signals being cross-correlated have the same phase as each other during each cross-correlation measurement.