Streak Image Sensor for LIDAR Depth Measurement Distortion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Airborne LIDAR systems used for detecting submerged objects face distortion in 2D images due to varying round-trip propagation times of return light, which depend on the azimuth angle and local conditions, leading to inaccurate depth and location measurements.
Innovation Solution
The method involves a streak image sensor system that periodically samples and stores electrical signals from sensor elements, synchronizing sampling with features representing boundaries between different optical materials, such as the water surface, to correct for distortion and align depth values across channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional LIDAR systems use stationary sensor elements with fixed instantaneous fields of view, then the system structure is simple, but image distortion occurs due to varying round-trip propagation times of return light at different azimuth angles
Solution Approach 1:
The patent transforms the stationary sensor system into a dynamic one by implementing sensor elements that can be individually triggered and controlled. Each sensor element's instantaneous field of view is dynamically activated based on detected features (such as water surface reflections), allowing the system to adapt to varying propagation times and azimuth angles, thereby resolving the image distortion problem while maintaining manageable complexity through selective activation rather than continuous operation of all sensors.
Solution Approach 2:
The system performs preliminary detection of feature points (such as water surface reflections) before initiating the actual depth measurement process. By first identifying the location and characteristics of the water surface through initial sensor readings, the system can then pre-calculate the appropriate propagation time and trigger the corresponding sensor elements at the correct moment, eliminating distortion caused by varying round-trip times without requiring complex real-time adjustments during measurement.
2Measurement precision
If the LIDAR system samples return light signals continuously across all sensor channels, then complete spatial coverage is achieved, but sampling synchronization becomes complex due to varying propagation times
Solution Approach 1:
The patent divides the sensor array into independently controllable channels, each associated with specific azimuth angles and propagation time ranges. Instead of synchronizing all sensors simultaneously, the system segments the sampling process into discrete channels that are triggered independently based on their specific propagation time requirements. This segmentation allows each channel to be optimized for its specific angular and temporal characteristics, achieving precise synchronization without requiring complex global coordination.
Solution Approach 2:
The system changes the sampling parameters (trigger time, integration duration, gain settings) for each sensor channel based on its specific azimuth angle and expected propagation time. By adjusting these parameters individually for each channel rather than using a uniform sampling scheme, the system achieves precise synchronization across all channels while simplifying the control logic, as each channel operates with pre-optimized parameters rather than requiring real-time synchronization coordination.
3Measurement precision
If sensor elements are triggered early to capture all possible return signals, then signal coverage is maximized, but depth measurement accuracy decreases due to inclusion of premature signals from other targets
Solution Approach 1:
The system performs preliminary detection and identification of the water surface reflection feature before initiating the depth measurement sampling process. By first detecting the characteristic signal pattern of the water surface (such as the strong reflection at a specific time and angle), the system can then precisely determine when to start sampling for subsurface objects. This preliminary action ensures that sampling begins at the correct temporal reference point, excluding premature signals from other targets while capturing all relevant return signals from submerged objects, thereby improving depth measurement accuracy without sacrificing signal coverage.
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 effectively reduces image distortion and improves the accuracy of depth and location measurements of submerged objects by synchronizing sampling with the arrival of return light signals, enhancing the precision of LIDAR systems in detecting objects beneath water surfaces.
Implementation Method 1
Some of the laser light may be reflected from the water surface, some light that enters the water is absorbed, some light that enters the water is backscattered by the water, and some light is reflected off objects
Implementation Method 2
some light that enters the water is backscattered by the water
Implementation Method 3
a sensor element 12, such as an avalanche photodiode (APD)... The current signals generated by the APDs 12
Data Source
AI summary
A LIDAR system that includes a streak image sensor having multiple sensor elements for receiving optical return signals from portions of a spatial region within their respective instantaneous fields of view is operated by periodically sampling and storing electrical signals generated by the sensor elements respectively, and initiating the periodic sampling of the electrical signals of each sensor individually and independently by reference to a feature of that sensor's electrical signal that represents a boundary between materials with different optical properties.