LIDAR Frequency Averaging for Noise-Resistant Distance Sensing
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Solution Overview
Problem
LIDAR systems face challenges in achieving precise LIDAR data measurements due to noise, speckle, interference, and system limitations, leading to reduced precision.
Innovation Solution
A LIDAR system that combines light from a system output signal with a reference signal to generate beating signals, calculates averaged frequencies, and applies outlier identification criteria to enhance precision by averaging beat frequencies from the same surface, reducing distortions from edges and outliers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LIDAR systems use standard measurement methods, then the system is simple to operate, but the measurement precision is reduced due to noise, speckle, and interference
Solution Approach 1:
The patent segments the LIDAR measurement process into multiple independent data periods, where each period collects beat frequencies from the same surface. By dividing the measurement into segments and averaging results across segments, the system reduces the impact of noise, speckle, and interference while maintaining operational simplicity through automated processing.
Solution Approach 2:
The patent implements periodic action by repeating the measurement process across multiple data periods with identical frequency patterns. Each period captures beat frequencies from the same surface, and the periodic repetition allows statistical averaging to reduce random variations and improve precision without significantly increasing system complexity.
2Measurement precision
If LIDAR systems average multiple beat frequencies, then the measurement precision increases, but the processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-organizing beat frequencies into groups corresponding to the same surface before averaging. The system identifies and groups beat frequencies from identical surfaces in advance, then performs efficient averaging within each group. This preprocessing step reduces computational complexity and processing time compared to averaging all frequencies without prior organization.
3Measurement precision
If LIDAR systems collect data from multiple data periods, then the precision improves through averaging, but the quantity of data to process increases
Solution Approach 1:
The patent extracts only the relevant beat frequencies from the collected data by identifying those that originate from the same surface. Instead of processing all accumulated data, the system selectively extracts and averages beat frequencies corresponding to identical surfaces, reducing the effective data volume that requires detailed processing while maintaining precision improvements from multiple measurements.
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 system increases the precision of LIDAR data by reducing standard deviation and improving detection probability through the use of averaged beat frequencies and outlier correction.
Implementation Method 1
a light-combiner that combines light that returns to the LIDAR system from the system output signal with light from a reference signal so as to generate beating signals
Data Source
AI summary
The imaging system is configured to output a system output signal during multiple associated data periods. A pattern of a frequency of the system output signal as a function of time is repeated during each of the associated data periods. The LIDAR system includes a light-combiner that combines light that returns to the LIDAR system from the system output signal with light from a reference signal so as to generate beating signals that are each beating at a beat frequency. Each of the beat frequencies is associated with a different one of the data periods. The system also includes electronics that calculate averaged frequencies that are each an average of multiple different beat frequencies and each of the averaged frequencies is associated with a different one of the data periods. The electronics calculate LIDAR data from the average frequencies. The LIDAR data indicates a radial velocity and/or distance between the system and an object outside of the system.