Distance Sensor Pulse Period Validation
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Solution Overview
Problem
Distance measurement devices using light pulses face challenges in accurately estimating distances beyond a certain maximum range due to the 'pulse wrap around' problem, where it is unclear whether a detected pulse is from a nearby or distant object, especially when pulse periods are short.
Innovation Solution
The method involves estimating distance values for pixels using light pulse trains with different periods, validating or invalidating these values by comparing them between adjacent pixels, and storing the results, allowing for unambiguous distance determination by considering the age of capture phases and using a checkboard pattern in the pixel array.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the pulse period is shortened to enable rapid distance calculation, then the measurement speed is improved, but the maximum unambiguous detection distance decreases
Solution Approach 1:
The patent applies periodic action by using multiple light pulse trains with different periods. The first pulse train has a first period and the second pulse train has a second period different from the first period. This allows the system to overcome the pulse wrap-around problem by comparing distance measurements from multiple periods, thereby extending the maximum unambiguous detection distance while maintaining rapid measurement speed.
Solution Approach 2:
The patent changes the period parameter of the light pulse trains. By using at least two different periods (first period and second period), the system can resolve the ambiguity of distance measurement. The validation unit compares distance values obtained from different periods to determine valid distance measurements, thus solving the contradiction between measurement speed and maximum detection distance.
2Measurement precision
If multiple pulse trains with different periods are used to extend detection range, then the maximum unambiguous detection distance is improved, but the measurement complexity increases
Solution Approach 1:
The patent segments the pixel array into different regions (first region and second region) and assigns different pulse trains to different regions. The first light pulse train is used for pixels in the first region, and the second light pulse train is used for pixels in the second region. This segmentation approach reduces the overall complexity by dividing the measurement task into manageable parts while still achieving extended detection range.
Solution Approach 2:
The patent dynamically selects which pulse train to use for measuring different pixels based on their spatial location and temporal characteristics. The validation unit dynamically validates or invalidates distance values based on comparisons between measurements from different pulse trains, allowing the system to adaptively handle the complexity of multi-period measurements.
3Measurement precision
If distance values are validated by comparing adjacent pixels, then the measurement accuracy is improved, but the processing time increases
Solution Approach 1:
The patent applies partial action by validating only certain distance values based on spatial and temporal criteria. The validation unit validates a first pixel's distance value based on comparison with adjacent pixels and temporal information, rather than validating all pixels uniformly. This selective validation approach improves accuracy for critical measurements while reducing overall processing time.
Solution Approach 2:
The patent performs preliminary action by capturing temporal information and spatial relationships during the measurement process itself. The system preliminarily identifies valid distance values through comparison with adjacent pixels and temporal data, so that subsequent processing can focus only on validated values, reducing the time loss associated with full validation.
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 enables rapid and accurate distance measurement beyond the traditional maximum range, minimizing errors and motion artifacts by validating or invalidating distance estimates based on comparisons and temporal considerations.
Implementation Method 1
the light reflected by objects located in the scene is detected by an element sensitive to the light of the measurement device
Implementation Method 2
the calculation of the travel time of light pulses
Data Source
AI summary
A method includes estimating first distance values associated with a plurality of first pixels, based on light pulses of a first light pulse train having a first period, estimating second distance values associated with a plurality of second pixels, the second distance values being estimated for each second pixel based on a second light pulse train having a second period different from the first period, for each of the first pixels being adjacent to one of the second pixels, validating or invalidating the first distance values, based on a comparison between the estimations of the first distance value and at least one of the second distance values of at least one second adjacent pixel, and storing an indication of the first pixels having been validated and/or invalidated.