Single Beam Lidar Azimuth Scanning for Moving Object Detection
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Solution Overview
Problem
Existing lidar sensors in autonomous vehicles face challenges in accurately determining the velocity of non-stationary obstacles, particularly at ranges between 80 meters and 300 meters, due to the complexity and cost associated with processing large amounts of three-dimensional point cloud data.
Innovation Solution
A low-cost lidar sensor using a single divergent beam scanned substantially only in azimuth, employing coherent detection methods like frequency-modulated continuous-wave (FMCW) or phase-coded modulation, and digital signal processing to distinguish moving objects from stationary backgrounds, reducing the need for complex computations and costly processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If three-dimensional point cloud data is processed to determine velocity of non-stationary obstacles, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential information needed for velocity determination from the returned light signals, rather than processing complete three-dimensional point cloud data. By using coherent detection to directly measure frequency shifts in returned signals, the system extracts velocity information without the computational overhead of full point cloud processing, thereby reducing device complexity while maintaining measurement precision.
Solution Approach 2:
The patent applies partial action by implementing coherent detection that processes only the necessary spectral components of returned light for velocity measurement. Instead of analyzing all spatial and temporal data in point clouds, the system focuses on frequency domain analysis of coherent signals, performing just enough processing to extract velocity information efficiently.
2Measurement precision
If three-dimensional point cloud data is processed to determine velocity of non-stationary obstacles, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent replaces the mechanical/computational process of three-dimensional point cloud processing with an optical-based coherent detection system. By using optical heterodyning and frequency domain analysis directly on returned light signals, the system achieves velocity measurement without the time-consuming computational steps required for point cloud processing, thereby reducing loss of time while maintaining measurement precision.
3Measurement precision
If complex computations are performed on point cloud data, then measurement precision is improved, but manufacturing precision requirements increase
Solution Approach 1:
The coherent detection system performs self-calibration through the natural properties of coherent light mixing. The local oscillator signal serves as a reference that automatically establishes the frequency relationship with returned signals, eliminating the need for complex external calibration procedures. This self-referencing approach reduces manufacturing precision requirements while maintaining measurement precision through the inherent stability of coherent detection.
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 effective detection and velocity determination of moving objects within the specified range with reduced computational complexity and cost, focusing on azimuthal scanning to prioritize object movement detection over elevation data, thus enhancing safety and efficiency in autonomous vehicle operations.
Implementation Method 1
The light source emits light towards a target that scatters the light
Implementation Method 2
the lidar system determines a distance to the target based on characteristics associated with the received scattered light
Implementation Method 3
employing coherent detection methods like frequency-modulated continuous-wave (FMCW) or phase-coded modulation
Implementation Method 4
applying coherent detection based on returned light from the target area
Data Source
AI summary
According to one aspect, a relatively low-cost sensor for use on an autonomous vehicle is capable of detecting moving objects in a range or a zone that is between approximately 80 meters and approximately 300 meters away from the autonomous vehicle. A substantially single fan-shaped light beam is scanned for a full 360 degrees in azimuth. Using frequency-modulated-continuous-wave (FMCW) or phase coded modulation on the beam, with back end digital signal processing (DSP), moving objects may effectively be distinguished from a substantially stationary background.