LiDAR Range Estimation via Spatial Intensity Analysis
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Solution Overview
Problem
Conventional LiDAR range estimation methods rely on high-speed ADCs to accurately determine the traveling time of laser pulses, which are expensive and prone to noise, limiting their effectiveness and increasing system costs.
Innovation Solution
The use of an optical detector array to measure the intensity of returned laser pulses, allowing a processor to calculate an intensity-related value and determine the traveling time of the laser pulse, thereby estimating the range between the object and the LiDAR system, using a low-cost ADC and reducing computational power requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a high-speed ADC is used to accurately determine the traveling time of the laser pulse, then the range estimation accuracy is improved, but the system cost increases and noise is substantially introduced
Solution Approach 1:
The patent divides the detector array into multiple segments or groups, where each segment measures intensity at different time points. This segmentation allows the system to extract traveling time information from spatial intensity distribution across multiple lower-speed ADCs, achieving accurate range estimation without requiring a single high-speed ADC, thereby reducing system cost while maintaining measurement precision.
Solution Approach 2:
The patent transitions from temporal sampling (single high-speed ADC measuring intensity over time) to spatial sampling (multiple low-speed ADCs measuring intensity across different detector elements). By mapping the time dimension to the spatial dimension through the detector array geometry, the system achieves the same measurement capability using cheaper, lower-speed components.
2Measurement precision
If a high-speed ADC is used to accurately determine the traveling time of the laser pulse, then the range estimation accuracy is improved, but substantial noises are introduced during operation
Solution Approach 1:
By segmenting the measurement across multiple detector elements and lower-speed ADCs, the patent reduces the sampling rate requirement for each individual ADC. Lower sampling rates inherently generate less quantization noise and thermal noise, thereby improving the signal-to-noise ratio while still achieving accurate traveling time determination through the combined spatial-intensity analysis.
Solution Approach 2:
The patent employs multiple low-cost, low-speed ADCs instead of a single high-speed ADC. These lower-speed ADCs are inherently noisier individually but when used in parallel across the detector array, their collective measurement provides accurate range estimation with reduced overall noise impact, as the noise from each channel is averaged or differentiated through the intensity distribution analysis.
3Ease of manufacture
If intensity information from an optical detector array is used to determine traveling time, then system cost is reduced and computational power requirements are reduced, but the measurement approach must be fundamentally changed
Solution Approach 1:
The patent replaces the conventional temporal-sampling mechanical approach (high-speed ADC sampling the returning pulse over time) with a spatial-intensity analysis approach. Instead of measuring how intensity changes over time at a single point, the system measures the spatial distribution of intensity across the detector array, which encodes the traveling time information. This substitution fundamentally changes the measurement paradigm from temporal to spatial, reducing hardware requirements while maintaining accuracy.
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 improves range estimation accuracy while reducing system manufacturing costs and computational power consumption, enabling efficient operation in applications like autonomous driving and high-definition map generation.
Implementation Method 1
The LiDAR receiver typically includes an optical detector to convert the returned laser pulse into an electrical signal
Implementation Method 2
The distance to the object (also referred to as the 'range') can be estimated based on a traveling time of the laser pulse and the speed of light
Data Source
AI summary
Embodiments of the disclosure provide a range estimation system for the optical sensing system. The exemplary range estimation system includes an optical detector array configured to receive a laser pulse returned from an object. The optical detector array includes a plurality of detector elements each configured to measure an intensity of the returned laser pulse. The range estimation system further includes a processor. The processor is configured to calculate an intensity-related value based on the intensities of the returned laser pulse measured using the optical detector array. The processor is further configured to determine a traveling time of the laser pulse based on the calculated intensity-related value. The processor is also configured to estimate a range between the object and the optical sensing system based on the traveling time of the laser pulse.