FMCW LIDAR Distance Velocity Determination Alignment
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Solution Overview
Problem
Existing LIDAR systems for distance and velocity determination based on FMCW technology face inaccuracies due to assumptions of matching beam directions and object locations during up-chirp and down-chirp measurements, leading to incorrect interpretation of measurement results, especially in scenarios with fast movement or mechanical scanning.
Innovation Solution
The method involves determining and aligning difference frequency distributions for up-chirp and down-chirp signals to ensure that pixels in both distributions correspond to the same object point, using image processing techniques such as coregistration to match the distributions before calculating distance and velocity, allowing for accurate determination of distance and velocity from the same object location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If FMCW LIDAR systems use up-chirp and down-chirp sections for distance and velocity determination, then velocity information can be obtained through Doppler shift calculation, but measurement accuracy deteriorates when beam direction changes or objects move significantly between the two chirp sections
Solution Approach 1:
The patent performs preliminary actions by determining beam directions for both up-chirp and down-chirp sections, identifying matching beam direction pairs before conducting the actual measurement. This preparatory step ensures that only measurements from corresponding beam directions are combined, preventing errors from mismatched beam directions while maintaining the velocity measurement capability through Doppler shift calculation.
Solution Approach 2:
The system implements feedback by continuously monitoring beam direction changes between up-chirp and down-chirp sections. When beam direction mismatches are detected, the system adjusts the measurement process by selecting only matched beam direction pairs for combination, ensuring measurement reliability without sacrificing the Doppler-based velocity information extraction.
2Adaptability or versatility
If the scanning system mechanically moves the beam during up-chirp and down-chirp sections, then scene coverage is improved, but incorrect interpretation of measurement results occurs due to non-matching beam directions
Solution Approach 1:
Before combining measurement results from up-chirp and down-chirp sections, the patent performs preliminary beam direction matching by determining the beam direction at the start and end of each chirp section. This preliminary action identifies which beam directions correspond between the two sections, enabling correct interpretation of measurements even when mechanical scanning causes beam position changes.
Solution Approach 2:
The patent introduces beam direction identification as an intermediary step between the raw FMCW measurements and the final distance-velocity determination. By using beam direction as a mediator to match measurements from up-chirp and down-chirp sections, the system correctly interprets measurements from mechanically scanned scenes without sacrificing imaging capability.
3Loss of energy
If the duration of up-chirp and down-chirp sections is extended to improve signal evaluation, then signal-to-noise ratio improves, but object position changes significantly during measurement leading to incorrect results
Solution Approach 1:
The patent performs preliminary beam direction determination and object position estimation at the beginning of each chirp section. This preliminary action allows the system to evaluate signal quality and identify valid measurement windows before the full chirp duration elapses, ensuring that only measurements taken when objects remain within acceptable position ranges are used for final determination.
Solution Approach 2:
The system dynamically adjusts the effective measurement window within each chirp section based on real-time beam direction changes and object position estimates. By making the measurement process dynamic rather than static, the system maintains signal evaluation quality while preventing inclusion of measurements from significantly changed object positions.
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 ensures accurate and reliable distance and velocity measurements by ensuring that information from both chirp sections originates from the same object point, correcting for errors caused by beam direction changes and object movement, resulting in improved scene imaging.
Implementation Method 1
time-of-flight-based measuring systems (TOF-LIDAR measuring systems, TOF=time of flight), in which the time-of-flight of the laser light to the respective object and back is measured directly
Implementation Method 2
FMCW-LIDAR measuring systems with the use of a frequency-modulated FMCW laser (FMCW=frequency-modulated continuous wave)
Implementation Method 3
the time-dependent frequency characteristic of the signal 611 emitted by the light source 610 can also be such that two sections or partial signals are present in which the time derivative of the frequency generated by the light source 610 is opposite to each other, whereby the corresponding sections or partial signals can then be referred to as up-chirp and down-chirp. From the difference or beat frequencies determined for these two partial signals, both the Doppler shift fD as well as the beat frequency corrected with respect to the Doppler effect fb are calculated
Data Source
AI summary
In a method for scanning distance and velocity determination of at least one object, a light source emits an optical signal with a time-varying frequency. A first difference frequency distribution is determined that represents, for different pixels on the at least one object, a difference frequency between a measurement signal originating from the optical signal and reflected at the respective pixel and a reference signal not reflected at the object. At a later time, a second difference frequency distribution is determined. Then the first and the second difference frequency distributions are aligned by performing a transformation of the pixels of the first and of the second difference frequency distributions in such a way that after this alignment, pixels corresponding to each other both distributions correspond to the same object point. Finally, the distance and velocity for each pixel is determined using the two aligned difference frequency distributions.