Lidar Pulse Energy Measurement via Signal Decay Modeling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current lidar systems face challenges in accurately measuring pulse energy without employing complex and expensive hardware, such as high-speed analog-to-digital converters (ADCs).
Innovation Solution
A system is developed that includes an electronic circuit and processors to determine pulse metrics like pulse energy, peak pulse power, or peak pulse intensity by calculating the difference between a measured waveform portion and a modeled reference level based on a signal decay model, allowing for accurate measurement without requiring sophisticated hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-speed analog-to-digital converters (ADCs) are used to measure pulse energy, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a computational model that copies the expected signal decay characteristics of the lidar system. Instead of using complex hardware to directly measure pulse energy, the system creates a reference model of how signals should decay over time, then compares actual measurements against this model to infer pulse energy. This software-based copying approach replaces the need for expensive high-speed ADC hardware while maintaining measurement accuracy.
Solution Approach 2:
The patent substitutes a software-based signal processing system for the hardware-based measurement approach. Instead of relying on high-speed ADCs and complex electronic measurement circuits, the system uses computational algorithms to analyze signal decay characteristics and derive pulse energy measurements. This replacement of mechanical/electronic measurement systems with software-based analysis reduces hardware complexity while preserving measurement precision.
2Measurement precision
If high-speed analog-to-digital converters (ADCs) are used to measure pulse energy, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent employs standard, low-cost ADC components rather than expensive high-speed ADCs. By using conventional ADCs with slower sampling rates and processing the data through signal decay analysis algorithms, the system achieves accurate pulse energy measurements without requiring costly high-speed conversion hardware. This approach treats the measurement function as achievable through software processing of lower-specification hardware.
Solution Approach 2:
The patent replaces expensive high-speed ADC hardware with a combination of standard ADCs and software-based signal decay analysis. This substitution eliminates the need for costly high-speed conversion components while maintaining measurement precision through computational methods that analyze the temporal decay characteristics of the received signal.
3Device complexity
If signal decay modeling is used to determine pulse metrics, then device complexity is reduced, but measurement precision may be compromised
Solution Approach 1:
The patent implements an iterative feedback process where the system compares measured signal decay characteristics against the modeled reference decay curve. By continuously adjusting and refining the pulse energy estimation based on the difference between actual measurements and model predictions, the system converges on accurate pulse metric values. This feedback mechanism ensures measurement precision is maintained even while using simplified hardware approaches.
Solution Approach 2:
The patent changes the measurement approach from direct hardware-based pulse energy detection to analyzing temporal signal decay parameters. By measuring how the signal amplitude decreases over time and comparing this decay profile against a reference model, the system extracts pulse energy and other metrics. This parameter transformation from spatial/amplitude-based measurement to temporal decay-based measurement enables accurate results with simpler hardware.
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 robust and accurate pulse energy measurement in lidar systems, reducing the need for complex hardware and lowering costs while maintaining measurement precision.
Implementation Method 1
determine a difference between a measured level on the second detected waveform portion and a modeled reference level determined based on a signal decay model and a measured pulse period
Data Source
AI summary
A system includes an electronic circuit configured to provide a detected waveform including a first detected waveform portion corresponding to a first output light pulse triggered at a first trigger time and a second detected waveform portion corresponding to a second output light pulse triggered at a second trigger time. The system further includes one or more processors configured to determine a pulse metric associated with the second output light pulse including by being configured to determine a difference between a measured level on the second detected waveform portion and a modeled reference level determined based on a signal decay model and a measured pulse period.