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

Laser cloud-detection radar signal self-adaptive identification method based on least mean square algorithm

A recognition method, laser technology, applied in the field of signal processing, can solve the problem of low signal-to-noise ratio of the returned signal, achieve high resolution, suppress system and background noise

Inactive Publication Date: 2009-11-18
ANHUI INST OF OPTICS & FINE MECHANICS - CHINESE ACAD OF SCI
View PDF0 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a method for adaptive identification of laser cloud radar signals based on the least mean square algorithm, to solve the problem that the signal-to-noise ratio of the return signal is low due to noise after the laser returns from the cloud

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
  • Laser cloud-detection radar signal self-adaptive identification method based on least mean square algorithm
  • Laser cloud-detection radar signal self-adaptive identification method based on least mean square algorithm
  • Laser cloud-detection radar signal self-adaptive identification method based on least mean square algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] 1. Principle introduction

[0032] Assuming that the signal modulated by the pseudo-noise sequence emitted by the laser is s(t), it is polluted by various signals and interference noise in the space during the propagation process, and then the signal plus noise scattered into the receiving detector by the clouds in the air is:

[0033] R(t)=s d (t-τ d )+n(t)+s c (t-τ c )

[0034] In the formula: s c (t-τ c ) represents the continuous signal scattered back (the continuous envelope part of the ideal signal in the following schematic diagram, which is usually used to describe fog or aerosol information), and also includes the multipath delay of the useful signal itself and artificial interference signals (enemy interference), n(t) is all additive white Gaussian noise in the channel (such as background light, circuit noise, etc.), s d (t-τ d ) is a sudden change signal (the two impacts of the ideal signal in the following schematic diagram, which are usually used to...

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 relates to a laser cloud-detection radar signal self-adaptive identification method based on a least mean square algorithm, which synchronously compound two m sequences with different cycles so as to generate a compound pseudo-noise sequence and synchronously transmit the sequence to a continuous modulation laser transmitting terminal and a signal receiving terminal respectively; the signal receiving terminal carries out sectional accumulation average calculating operation to a received signal, then adopts an LMS algorithm to substitute the result of the sectional accumulation average calculating operation and the compound pseudo-noise sequence, and finally establishes a laser atmospheric scattering system model by utilizing the convergence result obtained by the LMS algorithm. The method effectively solves the circuit design problem caused by requirement on extremely high pulse peak value power and extremely narrow pulse when a pulse modulating laser radar is applied to the cloud-detection, and also the problems that the receiving terminal needs to collect a large quantity of samples for accumulation and average and the computation workload is large, the resolution is low, the signal-to-noise ratio is low and the like, thus greatly improving the measuring efficiency and accuracy.

Description

technical field [0001] The invention relates to the field of signal processing, in particular to a method for self-adaptive identification of laser cloud radar signals based on the least mean square algorithm. Background technique [0002] Clouds are formed by the condensation and aggregation of water droplets or ice crystals. When the laser enters the cloud from the atmosphere, strong backscattering will occur at the boundary of the cloud. The characteristics are related to the performance parameters of the laser radar. In this way, by analyzing the changes of the laser echo, the position of the cloud base can be determined and the height of the cloud base can be calculated. Generally, the farther the detection distance is, the weaker the backscatter signal received by the receiver is. On the whole, the lidar signal presents an attenuation trend inversely proportional to the square of the distance; while locally, due to the influence of atmospheric instability and noise (v...

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): G01S17/95G01S7/48
CPCY02A90/10
Inventor 何俊峰刘文清张玉钧崔益本阚瑞峰阮俊陈臻懿耿辉
Owner ANHUI INST OF OPTICS & FINE MECHANICS - CHINESE ACAD OF SCI
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