Lidar Signal-to-Noise Ratio via Polarization Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
LIDAR systems face noise issues in electrical signals due to misdirected light signals, which reduce the reliability of the data generated, as these systems struggle to effectively filter out noise from the LIDAR signals.
Innovation Solution
A LIDAR system design that includes a light source with a filter to separate and filter out misdirected signals from the LIDAR path, using a polarization splitter and rotator to differentiate between LIDAR and misdirected signals based on polarization states, thereby reducing noise in the electrical signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If the LIDAR system collects all reflected light signals, then the signal strength is improved, but noise from misdirected signals increases
Solution Approach 1:
The patent extracts and removes misdirected signals from the optical path using a filter component. The filter is configured to block misdirected light signals while allowing the desired LIDAR return signals to pass through, thereby separating the harmful noise from the useful signal before detection.
Solution Approach 2:
The patent introduces a filter as an intermediary component between the optical path and the detector. This filter acts as a mediator that selectively transmits or blocks specific light signals based on their directional properties, enabling the system to distinguish between misdirected noise and valid LIDAR returns.
2Reliability
If filtering components are added to remove misdirected signals, then noise is reduced, but device complexity increases
Solution Approach 1:
The patent integrates the filter functionality into the existing LIDAR system architecture in a way that allows a single component to serve multiple purposes: filtering misdirected signals while maintaining the optical path for valid signals. This multi-functional approach reduces the need for additional separate components.
Solution Approach 2:
The filter component is designed to automatically distinguish and block misdirected signals based on their inherent directional properties without requiring external control or additional processing. The filtering action is self-contained and does not add complex control logic to the system.
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
The filtering of misdirected signals improves the signal-to-noise ratio, enhancing the reliability and accuracy of the LIDAR data by isolating noise from the intended LIDAR signals, leading to more precise radial velocity and distance measurements.
Implementation Method 1
using a polarization splitter and rotator to differentiate between LIDAR and misdirected signals based on polarization states
Implementation Method 2
The processing unit is configured to convert optical signals that include the LIDAR signal to electrical signals
Data Source
AI summary
A LIDAR system includes a light source configured to output light. A portion of the light is included in a LIDAR signal that travels a LIDAR path from the light source to an object located outside of the LIDAR system and from the object to a filter and from the filter to a processing unit. The processing unit is configured to convert optical signals that include the LIDAR signal to electrical signals. A portion of the light is also included in one or more misdirected signals. Each of the misdirected signals travels a different misdirected path from the light source to the filter. Each of the misdirected paths is a different path from the LIDAR path. The system also includes a filter being configured to filter out the LIDAR signal from the misdirected signals. The system also includes electronics that generate LIDAR data from the electrical signals.