Photon-Counting LiDAR Filtering for Continuous Bathymetry
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Solution Overview
Problem
Current photon counting Lidar technologies face challenges in effectively processing photon signals in water columns for bathymetry, failing to accurately extract water surface and water bottom signals and calculate water depth due to poor data processing algorithms.
Innovation Solution
An adaptive filtering method is introduced for photon counting Lidar, which involves adaptively acquiring elliptic filter parameters for water surface and underwater photon signals, determining their relationships, and filtering to obtain continuous bathymetry results by constructing and rotating elliptical search regions based on photon density and elevation data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional algorithms are used to process photon signals in water column, then the processing method is simple, but the extraction accuracy of water surface and water bottom signals is poor
Solution Approach 1:
The algorithm segments photon signals into water surface signals and water bottom signals by dividing the point cloud data into different elevation layers. This segmentation enables separate processing and analysis of signals from different depths, improving extraction accuracy while maintaining manageable computational complexity through structured data organization.
Solution Approach 2:
The algorithm introduces elevation dimension analysis by sorting photons according to their elevation values and creating elevation-based layers. This dimensional approach transforms the processing from simple 2D point cloud analysis to 3D spatial analysis, enabling accurate separation of water surface and bottom signals based on their vertical positions.
2Measurement precision
If photon counting Lidar uses high-energy emission to acquire waveforms with high signal-to-noise ratio, then the signal quality is improved, but the pulse energy and repetition frequency contradiction arises
Solution Approach 1:
The patent replaces traditional waveform-based signal processing with photon-counting-based processing. Instead of relying on high-energy pulses to create detectable waveforms, the system counts individual photons and uses statistical analysis to extract signals, enabling high repetition frequency operation while maintaining signal quality through advanced data processing algorithms.
Solution Approach 2:
The algorithm changes the processing parameter from waveform amplitude analysis to photon count statistics. By analyzing the distribution and timing of individual photon events rather than continuous waveforms, the system achieves high signal-to-noise ratio extraction even with low-energy, high-repetition-frequency pulses.
3Adaptability or versatility
If photon counting Lidar detects water column, then bathymetry capability is achieved, but the laser point cloud shows different characteristics from land requiring new processing methods
Solution Approach 1:
The algorithm applies different processing strategies to different spatial regions: water surface photons are processed using one set of criteria while water bottom photons use another. This local quality approach tailors the processing method to the specific characteristics of each region, improving bathymetry accuracy while adapting to the unique optical properties of water environments.
Solution Approach 2:
The algorithm dynamically adjusts processing parameters based on the detected photon distribution patterns. By analyzing the elevation distribution and density of photons in real-time, the system adapts its filtering and classification parameters to match the specific water conditions being measured, enabling versatile bathymetry across different environments.
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 method efficiently extracts water surface and underwater photon signals, enabling the automatic and continuous acquisition of water depth data even in varying water environments, effectively addressing the limitations of previous algorithms.
Implementation Method 1
photon counting Lidar uses extremely sensitive receiving devices, which convert traditional devices that accept hundreds or even thousands of photons' echo envelope amplitude detection into single photon detection
Data Source
AI summary
An adaptive filtering method of photon counting Lidar for bathymetry is provided in this invention, which includes steps: step S1: adaptively acquiring parameters of elliptic filtering for water surface photon signals; step S2: determining a relationship between filter parameters and elevation of underwater photon signals, and obtaining parameters of the elliptic filtering for photon signal in water column; and step S3: filtering and fitting the water surface photon signals and the underwater photon signals to acquire continuous bathymetry results.