FMCW Coherent LiDAR Chirp Linearization for Range Accuracy
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Solution Overview
Problem
Chirp non-linearity in frequency modulated continuous wave (FMCW) coherent LiDAR systems leads to inaccurate range and velocity measurements due to thermal dynamics and charge saturation effects, which are difficult to correct with external modulators, causing errors and potential target miss-detection.
Innovation Solution
Implement methods for chirp linearization in FMCW coherent LiDAR systems using oversampling, two continuous wave (CW) lasers, partial field-of-view (FOV) as a reference reflector, or external reflectors to correct chirp non-linearity by feedback mechanisms and error signal determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If external modulators are used to generate frequency chirp, then the LiDAR system can achieve range and velocity detection, but thermal dynamics and charge saturation effects cause chirp non-linearity that is difficult to correct
Solution Approach 1:
The patent employs feedback mechanisms where the actual chirp signal is monitored and compared against the ideal linear chirp profile. Correction signals are generated based on the detected non-linearity and fed back to the modulator to compensate for deviations, thereby maintaining measurement accuracy despite thermal and charge saturation effects.
Solution Approach 2:
The system dynamically adjusts modulation parameters such as chirp slope, frequency deviation, and modulation depth to compensate for non-linear effects. By changing these parameters in real-time based on operating conditions, the system maintains optimal linearity across varying temperature and charge states.
2Measurement precision
If oversampling is implemented to correct chirp non-linearity, then measurement accuracy improves, but system complexity and processing requirements increase
Solution Approach 1:
The patent implements oversampling at a rate higher than the minimum Nyquist rate to capture fine details of chirp non-linearity. By sampling excessively (more than necessary), the system obtains sufficient data points to accurately characterize and correct non-linear effects, then uses efficient algorithms to process only the essential correction information.
Solution Approach 2:
The system replaces complex hardware-based linearization mechanisms with software/digital signal processing approaches. Digital algorithms process the oversampled data to generate correction signals, substituting mechanical or analog complexity with flexible computational methods that can be implemented through programming.
3Reliability
If correction signals are applied to the laser signal, then chirp non-linearity is reduced, but system complexity increases due to additional signal processing components
Solution Approach 1:
The patent combines the correction signal generation and application functions within the existing signal processing chain. Rather than adding separate dedicated correction hardware, the system integrates non-linearity compensation into the existing modulation and detection pathways, merging multiple functions into unified processing stages.
Solution Approach 2:
The system uses its own received signal and internally generated reference signals to create correction signals, making the correction mechanism self-contained. The LiDAR system monitors its own performance and generates its own correction signals without requiring external calibration equipment or additional reference systems.
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
Achieves precise range and velocity measurements by correcting chirp non-linearity, ensuring accurate target detection and reducing errors in LiDAR systems.
Implementation Method 1
generating a continuous wave laser signal having a frequency characteristic, in which the frequency characteristic can include a frequency chirp over a frequency band
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.