LIDAR Time-Bin Convolution for Distance Sensing in Scattering
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Solution Overview
Problem
Lidar systems face challenges in obtaining precise distance measurements due to scattering effects from rain, fog, smoke, and other optical scatterers, which result in false distance readings and reduced accuracy.
Innovation Solution
The method involves pulsing a scene with laser pulse sequences, forming time-resolved light signals, summing adjoining time bins to create super time bins, and using adaptive filtering techniques such as Kalman filters to offset scattering effects, thereby enhancing signal-to-noise ratio and isolating the sharp return from objects, allowing for more accurate distance determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time-gating is used to remove returns from nearby scatterers, then false distance measurements are reduced, but the benefit is limited and measurement precision in scattering conditions remains insufficient
Solution Approach 1:
The patent applies periodic pulsed laser illumination to the scene, transmitting sequences of laser pulses at regular intervals. This periodic action allows the system to accumulate multiple time-resolved signals and perform temporal averaging, which enhances the signal-to-noise ratio and improves distance measurement precision in scattering conditions by systematically capturing and processing repeated measurements
Solution Approach 2:
The patent merges multiple adjoining time bins to form super time bins, combining signals from multiple temporal intervals. This merging process accumulates photons across adjacent time windows, increasing the total signal strength and improving measurement precision when photon counts in individual time bins are insufficient
2Measurement precision
If multiple laser pulse sequences are transmitted to accumulate signals, then signal-to-noise ratio is improved, but measurement time increases
Solution Approach 1:
The patent performs preliminary processing of time-resolved signals by identifying and removing early-time scattered light returns before accumulating signals from multiple laser pulses. This preliminary action prevents scattered light from contaminating the distance measurement accumulation process, allowing faster signal integration and reducing total measurement time while maintaining improved signal-to-noise ratio
Solution Approach 2:
The patent segments the time-resolved signal into multiple time bins and selectively processes different segments differently - early time bins are used to identify and remove scattered light, while later time bins are accumulated for distance measurement. This segmentation allows parallel processing of scatter removal and signal accumulation, reducing overall measurement time
3Measurement precision
If scattered light is reflected back to the lidar sensor, then false distance measurements occur, but the ability to distinguish true object returns from scatter remains insufficient
Solution Approach 1:
The patent uses feedback from early time bin signals to adjust the processing of later time bins. The system analyzes early-time scattered light returns and uses this information to determine appropriate signal accumulation parameters and scatter removal thresholds for subsequent distance measurement, creating a feedback loop that adapts to varying scattering conditions and improves signal discrimination
Solution Approach 2:
The patent introduces an intermediary processing step that separates scattered light identification from distance measurement by using early time bins as an intermediary layer. This intermediary analysis of scattered light patterns enables the system to distinguish true object returns from scatter without directly mixing the two signal types in the final distance calculation
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 the accuracy of distance measurements by increasing the signal-to-noise ratio and effectively mitigating the impact of scattering effects, enabling the creation of precise three-dimensional images and accurate object localization for applications like autonomous vehicle navigation.
Implementation Method 1
Lidar uses a pulsed laser beam to probe the distance to a reflector by measuring the time it takes for the light to be reflected back to the device
Implementation Method 2
rain drops, fog, smoke, sand, and other scatterers can obscure the signal. These scatterers act to reflect light back to the lidar sensor and result in false distance measurements
Data Source
AI summary
A method of lidar imaging pulses a scene with laser pulse sequences from a laser light source. Reflected light from the scene is measured for each laser pulse to form a sequence of time resolved light signals. Adjoining time bins in the time resolved light signals are combined to form super time bins. A three dimensional image of the scene is created from distances determined based on maximum intensity super time bins. One or more objects are located within the image. For each object, the time resolved light signals are combined to form a single object time resolved light signal from which to determine distance to the object.