Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Surface classification method based on single-photon laser radar background noise rate

A background noise and lidar technology, applied in scene recognition, re-radiation of electromagnetic waves, instruments, etc., can solve the problems of low efficiency, low accuracy, and the assumption of unsuitable water surface, etc., to achieve fast calculation speed and small calculation amount. , the effect of large application potential

Active Publication Date: 2019-11-26
WUHAN UNIV
View PDF3 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Existing methods need to extract signal photons and compare them with high-resolution images for classification, NLCD auxiliary data is essential; and the noise rate threshold for water ice classification based on the background noise rate in the original point cloud data is based on experience At the same time, the current theoretical formula for the surface photon reflection noise rate is based on the assumption that the earth's surface is a Lambertian body, but this assumption is not applicable to the water surface, and there is no complete information on the theoretical formula for the water surface photon reflection noise rate.
[0006] It can be seen that there are technical problems of low accuracy and low efficiency in the prior art

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Surface classification method based on single-photon laser radar background noise rate
  • Surface classification method based on single-photon laser radar background noise rate
  • Surface classification method based on single-photon laser radar background noise rate

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] This embodiment provides a surface classification method based on the single-photon lidar background noise rate, please refer to figure 1 , the method includes:

[0054] Step S1: Obtain the system parameters of the single-photon lidar, the environmental parameters during measurement, and the target characteristic parameters.

[0055] Specifically, the single-photon lidar system parameters can include the laser wavelength λ, the effective area of ​​the receiving telescope A r , the telescope receives the half-field angle θ r , the bandwidth of the narrow-band filter Δλ, the comprehensive efficiency of the photoelectric system η; the environmental parameters during measurement include: solar radiance N λ 0 , one-way atmospheric transmittance T a , the solar zenith angle θ s , wind speed w; target characteristic parameters include ground slope σ L , ground reflectance β L , wind wave slope σ W , water surface reflectance β W .

[0056] Among them, the solar radia...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a surface classification method based on a single-photon laser radar background noise rate. On the basis of a mirror reflection theory, an expression of a water surface photonreflection noise rate is proposed is put forward; a background noise rate model is established by combining system parameters, environmental parameters and target characteristic parameters and mathematical expressions of a land background noise rate and a water body background noise rate are given respectively; a surface classification noise rate threshold value is obtained through calculation; and according to significant difference between land and water background noise rates, a statistical noise rate substituted into original point cloud data of the laser radar can be compared with a noiserate threshold to judge the surface type. According to the classification method, the dependence on a digital topographic map or a high-resolution remote sensing image required by the traditional method is eliminated; and used auxiliary data are available. The method having advantages of rapidness and high efficiency can be used for realizing high-precision surface type classification in coastalareas. The method is applied to the MABLE original point cloud data and the classification effect is excellent.

Description

technical field [0001] The invention relates to the technical field of surface classification, in particular to a surface classification method based on the single-photon laser radar background noise rate. Background technique [0002] Due to the higher detection sensitivity and higher repetition rate of photon counters and micropulse lasers, photon counting radars can obtain denser photon point cloud data than traditional full waveform radars. Therefore, in order to make more precise observations of the Earth's surface, NASA launched ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) at the end of 2018 and equipped it with a photon counting radar. However, since photon counting radar is very sensitive to both signal photons and noise photons mainly reflected from the background light of the sun, this makes the original single-photon point cloud data have a lot of noise. Therefore, how to distinguish signal photons from the original point cloud data is a problem. The key...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G01S17/88G01S7/48G06K9/00G06K9/62
CPCG01S17/88G01S7/48G06V20/13G06F18/24
Inventor 李松刘欣缘马跃张智宇张文豪周辉
Owner WUHAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com