Low Fill-Factor LiDAR Sensor Calibration for Microlens-Free Detection
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Solution Overview
Problem
Conventional LIDAR systems with low fill-factor sensors struggle to efficiently and effectively sense surrounding objects in three dimensions due to issues with dark current, signal-to-noise ratio, and the need for complex and costly microlens arrays.
Innovation Solution
Optimized deployment of electrical and optical power in LIDAR systems with low f-number and low-fill-factor sensor arrays, utilizing a sensor array with low fill-factor pixels and a microlens array-free design, coupled with a scan timing calibration engine to align light collection with active areas, reducing dark current and improving signal detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If a low fill-factor sensor array is used to reduce dark current and power consumption, then power efficiency improves, but light collection efficiency deteriorates
Solution Approach 1:
The system performs preliminary calibration by scanning a calibration target to generate a lookup table that maps scanner positions to sensor pixel positions. This pre-established mapping enables the low fill-factor sensor to accurately identify which pixels receive light at each scanner position, compensating for the low light collection efficiency without requiring microlens arrays.
Solution Approach 2:
The system changes the operational parameters by using a low fill-factor sensor array instead of a conventional high fill-factor array, and compensates for the reduced light collection efficiency through software-based calibration and lookup table generation rather than optical enhancements.
2Object-generated harmful factors
If a low fill-factor sensor array is used to reduce dark current, then noise reduction improves, but signal detection capability deteriorates
Solution Approach 1:
The system uses feedback from the calibration process to generate a lookup table that provides real-time correction information. During operation, the system queries this lookup table based on current scanner position to determine which sensor pixels are actively receiving light, enabling accurate signal detection despite the low fill-factor and enhancing the ability to distinguish true signals from noise.
Solution Approach 2:
The calibration target scan and lookup table generation are performed in advance before actual object detection. This preliminary action establishes the relationship between scanner positions and active sensor pixels, allowing the system to compensate for low fill-factor effects during normal operation without sacrificing signal detection capability.
3Device complexity
If microlens arrays are removed to simplify device structure and reduce cost, then device complexity reduces, but light collection efficiency deteriorates
Solution Approach 1:
The system replaces the mechanical/optical microlens array structure with a software-based calibration and lookup table system. Instead of using physical microlens elements to focus light onto active pixel areas, the system uses computational methods to track and identify which pixels receive light at each scanner position, thereby eliminating complex optical components while maintaining detection capability.
Solution Approach 2:
The lookup table acts as an intermediary between the scanner position and sensor pixel identification. Rather than relying on optical elements to physically guide light, the system uses this computational intermediary to map scanner positions to the corresponding low fill-factor pixels that are currently receiving light, compensating for the absence of microlens arrays.
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
Enhances the collection efficiency of light reflected from targets, minimizes power consumption, and improves the signal-to-noise ratio, thereby enhancing the accuracy and efficiency of object detection in three dimensions.
Implementation Method 1
sensor array with low fill-factor pixels... enhances the collection efficiency of light reflected from targets... improves the signal-to-noise ratio
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.