Chirp Linearization Using Partial Reflector in FMCW LiDAR
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Solution Overview
Problem
FMCW coherent LiDAR systems face challenges in achieving linear chirp due to thermal dynamics and charge saturation effects, leading to non-linear frequency chirp characteristics which affect range and velocity measurement accuracy.
Innovation Solution
The systems and methods involve chirp linearization techniques such as oversampling, using two CW lasers, or employing a reference reflector like a partial field-of-view or partial reflector to correct the frequency modulation of the laser signal, ensuring accurate range and velocity measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If FMCW coherent LiDAR systems use continuous wave laser with frequency modulation, then range and velocity detection capability is achieved, but thermal dynamics and charge saturation effects cause non-linear frequency chirp characteristics reducing measurement accuracy
Solution Approach 1:
The patent employs feedback mechanisms where the system continuously monitors the actual frequency chirp characteristics and adjusts the modulation parameters in real-time to compensate for thermal dynamics and charge saturation effects, maintaining linear chirp characteristics despite environmental variations
Solution Approach 2:
The system dynamically changes modulation parameters such as frequency sweep rate, duty cycle, and power levels to operate outside the regions affected by charge saturation and thermal effects, thereby maintaining chirp linearity across different operating conditions
2Measurement precision
If the system increases sampling rate to at least four times the beat frequency, then measurement accuracy is improved, but device complexity and data processing burden increase
Solution Approach 1:
The patent applies partial oversampling by sampling at exactly four times the beat frequency (Nyquist rate), which is the minimum sufficient rate to accurately capture the signal without requiring excessive sampling that would increase complexity unnecessarily
Solution Approach 2:
The system applies different processing strategies to different portions of the signal spectrum, focusing computational resources on the relevant beat frequency ranges while using simplified processing for other frequency components, thereby reducing overall processing burden
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
These methods enhance the linearity of the chirp, improving the accuracy and reliability of range and velocity measurements in FMCW coherent LiDAR systems by correcting frequency deviations and maintaining precise target detection.
Implementation Method 1
employing a reference reflector like a partial field-of-view or partial reflector to correct the frequency modulation of the laser signal
Implementation Method 2
mixing the received signal with a local oscillator signal, the local oscillator signal having the frequency characteristic; determining at least one beat frequency based on the mixed signal
Data Source
AI summary
Disclosed herein are systems and methods for linearizing frequency chirp in a frequency-modulated continuous wave (FMCW) coherent LiDAR system. Exemplary methods can include generating a continuous wave laser signal having a frequency characteristic, in which the frequency characteristic can include a frequency chirp over a frequency band in at least one period; and receiving a signal based on the generated laser signal. The methods can further include mixing the received signal with a local oscillator signal, the local oscillator signal having the frequency characteristic; determining at least one beat frequency based on the mixed signal; sampling the mixed signal at a rate equal to at least two times the beat frequency; determining a correction signal based on the sampled signal; and applying the correction signal to the laser signal.