LiDAR Chirp Signal Linearization via Fiber Optic Profile
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Solution Overview
Problem
FMCW LiDAR sensors face challenges in determining object ranges and velocities due to the use of non-linear chirp signals, which are costly to linearize and prone to interference from light sources.
Innovation Solution
A system that diverts a portion of the non-linear chirp signal into a fiber optic ending, where it is reflected back to determine its profile, allowing for linearization through regression analysis to compute frequency offsets and accurately determine object ranges and velocities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If non-linear laser sources are used to generate chirp signals, then cost is reduced, but measurement precision deteriorates due to non-linearity
Solution Approach 1:
The patent applies preliminary action by measuring the actual frequency-time profile of the non-linear chirp signal in advance using a spectrum analyzer, then storing this measured profile data for later use. This pre-characterization allows the system to compensate for non-linearity during normal operation without requiring expensive linear laser sources, thus resolving the contradiction between cost and measurement precision.
2Device complexity
If non-linear chirp signals are used, then device complexity is reduced, but measurement precision deteriorates due to non-linearity
Solution Approach 1:
The patent implements feedback by using the pre-measured non-linear profile data to continuously correct frequency offset calculations during LiDAR operation. The system retrieves the actual frequency-time relationship from stored measurements and applies this feedback to compensate for non-linearity in real-time, maintaining measurement precision while keeping the device simple and using non-linear laser sources.
3Ease of operation
If non-linear chirp signals are used, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent applies copying by creating a digital replica of the non-linear frequency-time profile through measurement and storage. This copied profile data is then used to substitute for the physical non-linearity in calculations, allowing the system to operate easily with non-linear sources while achieving precision equivalent to linear sources through mathematical correction.
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
Enables reliable determination of object ranges and velocities using cost-effective non-linear laser sources, while minimizing interference from light sources by linearizing the chirp signal, thereby improving the accuracy of LiDAR sensors.
Implementation Method 1
A profile of the non-linear chirp signal can be generated based on the data points. The non-linear chirp signal can be linearized based on the profile of the non-linear chirp signal.
Data Source
AI summary
Systems and methods of linearizing a signal of a light detection and ranging (LiDAR) sensor are described herein. A system receives a portion of a non-linear chirp signal. The portion of the non-linear chirp signal is sampled at a sampling frequency to generate data points corresponding to the portion of the non-linear chirp signal. A profile of the non-linear chirp signal is generated based on the data points. The non-linear chirp signal is linearized based on the profile of the non-linear chirp signal.