Pulse Train Time-of-Flight Lidar for Thermal and Interference Management
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Solution Overview
Problem
Automotive lidar systems face challenges in detecting objects at long ranges or with high scanning speeds without increasing laser power or processing speed, leading to reduced pixel throughput and frame rates, and are prone to signal interference from other lidar systems.
Innovation Solution
A TOF lidar system configured to emit and process pulse trains instead of individual pulses, with each pulse in the train having a specific intensity and duration, allowing for faster scanning and improved range resolution by sampling reflections at expected intensities, reducing thermal build-up, and mitigating signal interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If lidar systems increase laser power to detect objects at long ranges, then detection capability is improved, but thermal build-up increases and ocular safety concerns arise
Solution Approach 1:
The system uses pulse trains with periodic modulation instead of continuous high-power emission. Multiple low-energy pulses are transmitted in sequence with specific timing patterns, allowing the target to reflect enough cumulative energy for detection while giving the laser system time to cool between pulses, thus reducing thermal build-up.
Solution Approach 2:
The system changes the temporal parameters of laser emission by using modulated pulse trains with varying intensities and time intervals rather than single high-power pulses. This allows accumulation of reflected signal energy over time while keeping peak power levels low enough to avoid excessive thermal build-up and maintain ocular safety.
2Productivity
If lidar systems increase processing speed to achieve faster scanning, then frame rate is improved, but system complexity and cost increase
Solution Approach 1:
The system performs preliminary actions by transmitting multiple predictive pulses in a train before receiving the return signal. The timing and intensity of each pulse in the train is pre-calculated based on expected target range and velocity, allowing the system to gather sufficient signal data without requiring ultra-fast processing hardware.
Solution Approach 2:
The system maintains continuous useful action by overlapping pulse transmission with signal processing. While earlier pulses are being processed, subsequent pulses in the train are already being transmitted and reflected, ensuring that the detection process continues without interruption and achieving high effective frame rates without proportionally increasing processing speed requirements.
3Illumination intensity
If lidar systems use single high-intensity pulses for detection, then signal strength is improved, but susceptibility to external interference increases
Solution Approach 1:
The system uses periodic modulated pulse trains with specific timing patterns instead of single pulses. The regular intervals and intensity variations create a distinctive temporal signature that allows the receiver to distinguish between intentional returns and random external interference, improving signal reliability without increasing peak intensity.
Solution Approach 2:
The system merges multiple low-intensity pulses into a cumulative signal by transmitting them in close succession as a train. The reflected signals from multiple pulses combine at the receiver to create a strong aggregate return signal, achieving the signal strength of a single high-intensity pulse while using only low-intensity individual pulses that are less susceptible to interference.
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 enables faster object detection with higher pixel throughput, reduced thermal footprint, and improved ocular safety using low-energy lasers, while maintaining reliability and accuracy despite external noise from other lidar systems.
Implementation Method 1
time-of-flight (TOF) lidar systems
Implementation Method 2
emitted lidar pulses are compared to their reflected lidar return signals
Implementation Method 3
a photodetector configured based on a combination of the first and second intensities to detect reflections of the pulse train
Data Source
AI summary
This document describes a time-of-flight lidar system configured to process pulse trains instead of individual pulses, for improved range resolution and pixel throughput. Each pulse in the pulse train is output at a respective duration and intensity, which may vary to provoke a return with a high-intensity and low signal ambiguity, prevent thermal build-up, or promote safe ocular operation. An expected intensity of the return as a function of time can be determined. By sampling reflections at the expected times and intensities, the lidar system quickly identifies a corresponding lidar return, even despite lidar noise. A return time of the return can indicate a distance or speed associated with an object pixel in a field-of-view. Processing pulse trains instead of individual pulses allows pixels to be scanned faster than using long durations or frame times, which also promotes ocular safety. Increased throughput is realized using low-energy lasers and inexpensive hardware, which minimize thermal footprint.