Optical Distance Measurement Low-Pass Filter Memory Reduction
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Solution Overview
Problem
Current optical distance measurement methods using time-correlated single photon counting face challenges with high memory requirements and loss of integration cycles due to data transfer, leading to reduced measurement quality and increased costs, especially in ASIC integration, and require complex and costly data transfer solutions.
Innovation Solution
Implementing a method that uses a low pass filter to reduce or suppress frequency portions above a predetermined cut-off frequency in the distribution of times-of-flight of light, allowing for a second distribution with reduced memory requirements, which can be stored in a smaller memory area, thereby reducing the need for ping-pong memory and minimizing data transfer interruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a full-resolution histogram memory is used to store the complete distribution of times-of-flight data, then measurement precision is improved, but memory requirements and device complexity increase significantly
Solution Approach 1:
The patent extracts and removes high-frequency noise components from the times-of-flight distribution data using a low-pass filter. By separating the useful signal (low-frequency components representing actual distance information) from the noise (high-frequency components), the system can store only the filtered data, significantly reducing memory requirements while preserving measurement precision.
Solution Approach 2:
The patent changes the frequency domain parameters of the stored data by applying a low-pass filter with a specific cut-off frequency. This parameter transformation reduces the bandwidth of the stored signal, allowing for more efficient memory utilization while maintaining the essential distance measurement information within the filtered frequency range.
2Measurement precision
If data is transferred from histogram memory to data processing unit, then measurement quality is improved through evaluation, but integration cycles are lost during transfer time
Solution Approach 1:
The patent enables continuous integration cycles by reducing the data transfer time through prior filtering. The low-pass filter simplifies the data structure and reduces the amount of information that needs to be transferred, allowing the histogram memory to be quickly updated and ready for the next integration cycle without interruption, thus maintaining continuous operation.
3Measurement precision
If high sampling frequency and high resolution are used, then measurement precision is improved, but data transfer rates and system complexity increase
Solution Approach 1:
The patent extracts only the essential low-frequency components from the high-resolution times-of-flight data using a low-pass filter. This extraction process removes redundant high-frequency information that does not contribute to distance measurement precision, thereby reducing the data transfer rate requirements and simplifying the overall system architecture while maintaining the necessary measurement resolution.
4Productivity
If ping-pong memory is implemented to continue measurement during data transfer, then integration cycle loss is reduced, but memory requirements and chip surface area increase
Solution Approach 1:
The patent achieves measurement continuity through a different approach: by applying a low-pass filter to reduce data complexity and transfer time, the single memory structure can be quickly updated without requiring parallel ping-pong memory structures. This maintains integration cycle continuity while using fewer memory resources and reducing chip surface area requirements.
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 reduces memory requirements, minimizes data transfer time, and maintains measurement accuracy, allowing for more efficient and cost-effective optical distance measurement without the need for additional memory resources, thus overcoming the limitations of existing methods.
Implementation Method 1
Frequency portions of the first distribution of the times-of-flight of light above a predetermined cut-off frequency are reduced or suppressed by means of a low pass filter in a reduction step
Implementation Method 2
Optical distance measurements, in particular for use in the driverless navigation of vehicles, are based on the time-of-flight principle
Implementation Method 3
The measuring pulses are reflected by objects and photons of the reflected measuring pulses are detected
Implementation Method 4
photons of the reflected optical measuring pulses are detected by at least one receiver
Data Source
AI summary
A method for optical distance measurement is suggested, wherein a first distribution of times-of-flight of light of detected photons of transmitted measurement pulses is determined, which is stored in a first memory area of a memory unit. The first distribution of times-of-flight of light is assigned to time intervals of a first plurality of time intervals and frequency portions of the first distribution above a predetermined cut-off frequency are reduced or suppressed by means of a low pass filter in a reduction step, so that a second distribution of times-of-flight of light is generated. The second distribution is assigned to time intervals of a second plurality of time intervals and the blocking frequency of the low pass filter is selected to be smaller than or equal to half of the reciprocal value of a smallest interval width of the second plurality of time intervals.