LIDAR Interference Mitigation via Dithered Pulse Signatures
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Solution Overview
Problem
LIDAR systems face interference issues when multiple sensors are present, leading to ghost targets and reduced signal-to-noise ratios due to crosstalk, which affects the accuracy and reliability of surface feature detection.
Innovation Solution
Implementing dithered pulse signals with randomized timing and unique pulse signatures, combined with filtering processes to distinguish between coherent data points and noise, effectively reduces interference patterns and enhances data reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple LIDAR sensors are deployed to improve coverage and data reliability, then the quantity of substance increases, but interference between sensors increases causing ghost targets and reduced measurement precision
Solution Approach 1:
The patent segments the interference problem by assigning unique pulse signatures to different LIDAR sensors. Each sensor's pulses are divided into distinct groups with unique timing patterns, allowing the system to identify and separate interference from valid returns. This segmentation enables multiple sensors to operate simultaneously without complete signal collision.
Solution Approach 2:
The patent introduces pulse signatures as an intermediary identifier system. These signatures act as mediators that allow the receiving sensor to distinguish between its own transmitted pulses and pulses from other sensors. The signature information is embedded in the timing structure and used to tag and differentiate returns, preventing ghost target formation.
2Ease of operation
If pulse signals are transmitted at regular intervals to simplify timing synchronization, then ease of operation improves, but interference patterns become concentrated causing ghost targets
Solution Approach 1:
The patent uses periodic pulse transmission with unique timing patterns for each sensor. While pulses are transmitted periodically (maintaining simplicity), each sensor uses a distinct periodic pattern or duty cycle. This allows regular interval transmission to be maintained for ease of synchronization while the unique periodic patterns prevent constructive interference that creates ghost targets.
Solution Approach 2:
The patent changes the timing parameters of pulse transmission by assigning different pulse widths, duty cycles, or inter-pulse intervals to different sensors. These parameter variations ensure that even when sensors transmit at regular intervals, their timing patterns do not align to create constructive interference, thereby eliminating ghost targets while maintaining operational simplicity.
3Productivity
If all LIDAR sensors use the same pulse timing to maximize productivity, then productivity improves, but interference increases reducing reliability
Solution Approach 1:
The patent applies preliminary action by pre-assigning unique pulse signatures and timing patterns to each LIDAR sensor before operation begins. This preliminary configuration allows all sensors to transmit simultaneously at high rates (maximizing productivity) while the pre-established unique patterns enable the receiving sensor to reliably distinguish valid returns from interference (maintaining reliability).
Solution Approach 2:
The patent introduces dynamic timing variations where sensors can adjust their pulse transmission patterns based on detected interference conditions. When interference is detected, sensors can dynamically modify their timing patterns or duty cycles to avoid constructive interference, allowing the system to maintain high productivity while adapting to maintain reliability in real-time.
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 solution minimizes interference by distributing it as uniform noise, allowing for more accurate representation of environmental features and improved navigation in applications like autonomous driving.
Implementation Method 1
Light Detection and Ranging (LIDAR) is a remote sensing method that uses light in the form of a pulsed laser to measure variable distances to the environment
Implementation Method 2
The receiver is configured to receive one or more returned light signals reflected by the object and convert the one or more return light signals into electrical signals
Data Source
AI summary
Methods, apparatus, and systems related to light detection and ranging (LIDAR) are described. In one example aspect, a LIDAR apparatus includes a light emitter configured to generate, according to a first electrical pulse signal, a pulse light signal. The first electrical pulse signal comprises a first set of non-uniformly spaced pulses. The apparatus includes a receiver configured to convert returned light signals from the object into electrical signals and a filtering subsystem in communication with the receiver, configured to receive the electrical signals from the receiver and remove a point from a set of points representing at least a partial surface of the object as noise by determining whether there is a coherence between the point and corresponding neighboring points of the point along at least a first direction and a second direction of the set of points.