Lidar Receiver Circuit Dynamic Resolution Histogram Memory
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Solution Overview
Problem
Current lidar technologies face challenges in efficiently determining distances and classifying objects at greater distances with high precision, leading to increased memory and computational demands, which are not effectively addressed by existing methods.
Innovation Solution
The implementation of a receiver assembly and lidar module using time-correlated photon counting with an evaluation circuit that reduces the temporal resolution of distance determination at predetermined distances, allowing for precise distance measurement while minimizing memory requirements through histogram reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high precision distance determination is maintained at all distances, then measurement precision is improved, but memory space requirements increase
Solution Approach 1:
The patent implements dynamic resolution adjustment where the distance determination resolution is adapted based on the measured distance. At shorter distances, high resolution is maintained for precise measurement. At longer distances (>100m), the resolution is reduced since the absolute precision requirement is lower. This dynamic adaptation allows the system to maintain measurement precision where needed while reducing memory space requirements where high precision is not critical.
Solution Approach 2:
The patent changes the resolution parameter of distance determination based on distance ranges. By adjusting the bin size in histograms and the time resolution in TDC measurements according to the distance being measured, the system optimizes the balance between precision and memory usage. This parameter change strategy allows high precision when measuring nearby objects while using coarser resolution for distant objects, significantly reducing overall memory requirements.
2Measurement precision
If full resolution distance determination is used for all distances, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the distance measurement range into different zones (e.g., near field and far field) and applies different resolution levels to each segment. This segmentation allows the system to process measurements with appropriate precision for each distance range, reducing the overall computational burden. By dividing the measurement space and applying differentiated processing strategies, the system avoids the unnecessary computational complexity of maintaining full resolution across all distances.
Solution Approach 2:
The patent applies partial action by using full resolution only when necessary (for nearby objects) and reduced resolution for distant objects. This selective application of measurement precision avoids the excessive computational action that would result from maintaining maximum resolution for all measurements, thereby reducing device complexity while maintaining sufficient precision for the application requirements.
3Measurement precision
If high temporal resolution is maintained for distance determination, then measurement precision is improved, but memory space for histograms increases
Solution Approach 1:
The patent implements dynamic temporal resolution adjustment where the time resolution of the TDC (Time-to-Digital Converter) is adapted based on the distance range being measured. For nearby objects, high temporal resolution is maintained to achieve precise distance determination. For distant objects, the temporal resolution is reduced, which directly decreases the number of histogram bins required and thus reduces the memory space needed for storing histograms.
Solution Approach 2:
The patent changes the temporal resolution parameter in the histogram based on distance. By adjusting the bin width and time resolution according to the measurement distance, the system optimizes memory usage. This parameter change allows the system to use fine temporal resolution for near-field measurements requiring high precision, while using coarser temporal resolution for far-field measurements where absolute precision requirements are lower, thereby significantly reducing histogram memory space.
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 precise distance determination with reduced memory usage, maintaining accuracy for distances over 100 meters and reducing computational complexity, thus enhancing the efficiency of lidar systems in vehicles by reducing spatial resolution accordingly.
Implementation Method 1
A photosensitive receiver converts the light pulses into an electric signal
Implementation Method 2
determines a distance between the receiver assembly and at least one object that reflects the light pulses from the electric signal originating in the receiver by means of time-correlated photon counting with at least one histogram, via the time of flight of the light pulse
Data Source
AI summary
A receiver assembly for receiving light pulses, a lidar module containing such a receiver assembly, and a method for receiving light pulses are proposed. There is at least one photosensitive receiver (SPAD) therein, which converts the light pulses into an electric signal. An evaluation circuit is connected to the receiver, which determines a distance between the receiver assembly and at least one object that reflects the light pulses from the electric signal, by means of a time-correlated photon counting with at least one histogram, via a time of flight of the light pulse. The evaluation circuit is configured to reduce the resolution of the distance determination starting at no further than a predetermined distance.