LiDAR Distance Determination Using Reference Bitstream Matching
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Solution Overview
Problem
Existing Lidar technologies face challenges in efficiently processing large volumes of measurement data for determining distances to targets, requiring significant processing power and complex systems, particularly in applications requiring high resolution and large fields of view.
Innovation Solution
A method utilizing a bitstream of binary digits representing detected light signals, compared to a set of stored reference bitstreams, to determine distances without the need for complex processing such as Fourier transformations, enabling high-resolution distance determination with reduced processing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Digital Fourier Transform (DFT) is used to analyze the digital signal for determining distance to target, then the distance measurement accuracy is improved, but the processing power requirement and system complexity increase significantly
Solution Approach 1:
The patent segments the continuous signal processing task into discrete time bins, where each bin corresponds to a specific time interval and distance range. The signal is divided into multiple time bins based on the flight time of light, allowing parallel processing of different distance segments. This segmentation enables the system to process distance measurements in discrete intervals rather than requiring full-spectrum Fourier analysis, reducing computational complexity while maintaining measurement precision.
Solution Approach 2:
The patent performs preliminary binning of the detected signal into time bins before final distance determination. By pre-organizing the signal data into discrete time intervals corresponding to distance ranges, the system prepares the data in a format that requires minimal further processing. This preliminary action eliminates the need for computationally intensive Fourier transforms, as the distance information is already organized in ready-to-use time-bin structures.
2Measurement precision
If Digital Fourier Transform (DFT) is used for distance determination, then the distance measurement accuracy is improved, but the device complexity increases
Solution Approach 1:
The system segments the signal processing into simple time-bin assignments rather than complex Fourier analysis. Each detected photon event is assigned to a specific time bin based on its arrival time, and distance is determined by identifying which time bin contains the signal. This segmentation approach replaces complex mathematical transformations with simple temporal binning, significantly reducing device complexity while preserving distance measurement capability.
Solution Approach 2:
The patent replaces the mathematical/mechanical Fourier transform system with a temporal binning system. Instead of using complex signal processing hardware or software to perform Fourier analysis, the system uses simple time-stamping and binning logic to determine distance. This substitution of a complex mathematical processing system with a simpler temporal sorting system reduces device complexity while maintaining measurement precision.
3Measurement precision
If parallel illumination and detection of the field of view is implemented to improve resolution, then the imaging resolution is improved, but the data processing volume increases
Solution Approach 1:
The patent segments the field of view into multiple time bins, where each bin represents a specific distance range. By dividing the detection space into discrete temporal segments, the system processes data in manageable chunks rather than handling all data simultaneously. This segmentation allows parallel processing of different spatial regions while keeping the data volume for each segment manageable, thus improving resolution without overwhelming the processing system with excessive data volume.
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
Enables fast and efficient processing of Lidar data with high spatial resolution and frame rates, reducing memory and processing requirements while maintaining accurate distance measurements.
Implementation Method 1
Light detection and ranging (Lidar) is an active imaging technology wherein light is transmitted from a light source and light reflected by target(s) is detected
Implementation Method 2
Lidar involves a propagation time for the light, which may affect resolution of the imaging technology
Data Source
Figure 1
Figure 2~3
AI summary
A method for determining a distance to a target (10) comprises: receiving (202) a bitstream (112) of binary digits corresponding to a variation in time of a time-varying signal based on light transmitted by a light source (102) being reflected by the target (10), wherein each binary digit in the bitstream (112) is defined based on the time-varying signal at a time instance represented by the binary digit being above or below a threshold; comparing (204) the bitstream (112) of binary digits to a set of stored reference bitstreams (114) of binary digits, wherein each reference bitstream (114) represents a distance to the target (10); and determining (206) the distance to the target (10) based on selection of a reference bitstream (114) in the set of stored reference bitstreams (114) based on said comparing.