Low Fill-Factor LiDAR Calibration for Precise Object Detection
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Solution Overview
Problem
Conventional LIDAR systems with low fill-factor sensors face inefficiencies in three-dimensional object sensing due to dark current issues and complex optics, leading to reduced signal-to-noise ratio and increased manufacturing costs.
Innovation Solution
Optimized deployment of electrical and optical power in LIDAR systems with low f-number and low-fill-factor sensors by minimizing dark current through pixel design and eliminating the need for microlens arrays, utilizing scanning mirrors and MEMS mirrors to enhance collection efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional LIDAR systems use low fill-factor sensors, then manufacturing cost is reduced, but signal-to-noise ratio deteriorates due to dark current issues
Solution Approach 1:
The patent performs preliminary calibration by scanning a calibration target with known reflectivity values before actual object detection. This preliminary action establishes reference data that compensates for the low fill-factor sensor's dark current and optical imperfections, enabling reliable detection despite the sensor's inherent limitations
Solution Approach 2:
The system uses feedback from the calibration process to adjust detection algorithms. By comparing detected signals against calibrated reference data, the system compensates for noise and dark current effects, maintaining reliable object detection with low fill-factor sensors
2Reliability
If microlens arrays are added to improve collection efficiency, then signal detection is enhanced, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent extracts and removes the microlens array component from the optical system. Instead of adding complex optics, the invention achieves adequate collection efficiency through calibration-based compensation, eliminating the need for microlens arrays and reducing device complexity
Solution Approach 2:
The patent replaces the mechanical/optical solution (microlens arrays) with a computational approach (calibration-based signal processing). By substituting physical complexity with algorithmic compensation, the system achieves reliable detection without adding optical components
3Ease of operation
If scan timing is not calibrated, then system operation is simpler, but measurement precision deteriorates due to timing misalignment
Solution Approach 1:
The patent performs preliminary scan timing calibration by scanning a calibration target and measuring the actual timing of returned signals. This preliminary measurement establishes the correct timing relationship between scanner position and signal detection, ensuring precise object detection without requiring complex real-time timing adjustments
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
Improves power efficiency, reduces manufacturing complexity and cost, and enhances the signal-to-noise ratio by effectively detecting light reflected from targets, even with low fill-factor sensors.
Implementation Method 1
Light detection and ranging (LIDAR) devices have been implemented for automotive and industrial applications
Data Source
AI summary
The present disclosure relates to calibration of actively illuminated low fill-factor sensor devices and object detection, including capturing one or more returns in a first scan direction, assigning first timestamps corresponding to one or more of the returns in the first scan direction, identifying one or more peaks corresponding to intensity of one or more of the returns, correlating peak timestamps with one or more time intervals, the peak timestamps being associated with the peaks, generating a scan timing interval based on the peak timestamps, and calibrating one or more input devices or output devices based on the scan timing interval.