ToF Sensor Depth Resolution via Timestamp Averaging
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Solution Overview
Problem
Conventional LIDAR systems using histogram binning techniques suffer from quantization errors and reduced depth resolution due to finite binning, leading to inaccurate distance measurements and increased errors in distinguishing between closely spaced objects.
Innovation Solution
A method that determines the traveling time of light pulses by transmitting and receiving a series of pulses, associating timestamps with each pulse, and calculating the traveling time as an average or weighted average within a predetermined time window, eliminating the need for histogram binning and achieving infinite precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If histogram binning is used to determine traveling time, then the measurement process is simplified, but depth resolution and measurement precision are reduced due to quantization errors
Solution Approach 1:
The patent extracts the timestamp information directly from the photon detection events without performing histogram binning. By taking out the timestamp data and using it directly for traveling time calculation, the system eliminates the quantization errors introduced by histogram binning while maintaining measurement simplicity through direct timestamp averaging.
2Measurement precision
If the number of histogram bins is increased to improve depth resolution, then measurement precision improves, but device complexity and hardware resources increase dramatically
Solution Approach 1:
The patent replaces the mechanical histogram binning system with a computational approach using timestamp averaging. Instead of physically increasing the number of histogram bins, the system substitutes the mechanical binning process with an algorithmic method that calculates traveling time by averaging timestamps, thereby achieving high depth resolution without increasing sensor size or hardware complexity.
3Measurement precision
If the number of histogram bins is increased to improve depth resolution, then measurement precision improves, but peak detection becomes more difficult and depth error increases
Solution Approach 1:
The patent extracts the essential timestamp information from photon detection events and uses it directly for traveling time calculation through averaging. By taking out the timestamp data and performing statistical averaging, the system avoids the peak detection difficulties that arise in histogram-based methods when the number of bins is increased, as the timestamp averaging method naturally converges to the correct traveling time without requiring sharp peak identification.
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 increases depth resolution and reduces quantization errors, allowing for more accurate distance measurements, as demonstrated by improving depth resolution from 16 cm to 1 cm and reducing error from 4 cm in LIDAR systems.
Implementation Method 1
a time of flight (ToF) sensor array that determines a traveling time for light pulses
Data Source
AI summary
A method is disclosed to determine a traveling time for a plurality of received light pulses that reflected and returned from an object. Each returned light pulse is associated with a timestamp indicating a time between a transmission time of a corresponding light pulse and a time of arrival of the returned light pulse. For each timestamp, a number C is determined of time stamps that are subsequent to the timestamp and within a predetermined time window after the timestamp. A maximum number C is determined, and an index i is determined for the maximum number C. A traveling time is determined for the plurality of light pulses as an average of the timestamp having a same index as the maximum number C and timestamps that are within the predetermined time window after the timestamp having the same index as the maximum number C.