CN113030919A - Waveform detection method and system based on model fitting - Google Patents

Waveform detection method and system based on model fitting Download PDF

Info

Publication number
CN113030919A
CN113030919A CN202110279037.2A CN202110279037A CN113030919A CN 113030919 A CN113030919 A CN 113030919A CN 202110279037 A CN202110279037 A CN 202110279037A CN 113030919 A CN113030919 A CN 113030919A
Authority
CN
China
Prior art keywords
waveform
echo
water
laser
water body
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202110279037.2A
Other languages
Chinese (zh)
Inventor
丁凯
陶铭
谢仁平
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Dongguan University of Technology
Original Assignee
Dongguan University of Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Dongguan University of Technology filed Critical Dongguan University of Technology
Priority to CN202110279037.2A priority Critical patent/CN113030919A/en
Publication of CN113030919A publication Critical patent/CN113030919A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/483—Details of pulse systems
    • G01S7/486—Receivers
    • G01S7/487—Extracting wanted echo signals, e.g. pulse detection
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/483—Details of pulse systems
    • G01S7/486—Receivers
    • G01S7/487—Extracting wanted echo signals, e.g. pulse detection
    • G01S7/4876—Extracting wanted echo signals, e.g. pulse detection by removing unwanted signals
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/491—Details of non-pulse systems
    • G01S7/493—Extracting wanted echo signals

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Electromagnetism (AREA)
  • Optical Radar Systems And Details Thereof (AREA)

Abstract

The invention provides a novel waveform detection method and system based on model fitting. The method comprises the steps of firstly removing noise points and land laser points, and selecting laser points on the water surface; then, acquiring a water bottom echo waveform and a water surface echo waveform by using a Gaussian decomposition algorithm; then extracting the emission signal waveform and the echo signal waveform of each water laser spot; extracting water surface and water bottom echo waveforms from the sounding LiDAR echo waveforms by using a Gaussian decomposition algorithm; and finally, constructing a new function model, and fitting the water body backscattering waveform with the laser intensity being exponentially attenuated. Compared with the traditional model fitting method, the method has two remarkable advantages: firstly, the fitting obtained water body backscattering waveform is closer to the actual waveform. Secondly, the method can improve the detection precision of the laser echo position and the echo intensity.

Description

Waveform detection method and system based on model fitting
Technical Field
The invention relates to the technical field of laser communication, in particular to a waveform detection method and system based on model fitting.
Background
Depth measurement LiDAR can acquire the marine topography fast, and LiDAR also calls airborne laser depth measurement system, has characteristics such as high accuracy, high efficiency, high resolution. The data collected by the depth measurement LiDAR generally includes laser point cloud data, laser echo full waveform data, camera picture data, and the like. The method is characterized in that a processing algorithm for laser echo full waveform data is a key, a model fitting method takes a laser echo waveform as superposition of a plurality of different waveform functions, and the laser echo waveform is fitted into three parts, namely a water bottom echo waveform, a water surface echo waveform and a water body backscattering waveform, by constructing a model, so that information such as an echo position, echo intensity and the like is solved. The common model fitting method is to fit an echo waveform by using a Gaussian function and fit a water back scattering waveform by using a polygon function, however, each edge of the traditional polygon function is a linear function and cannot completely accord with the characteristic of exponential attenuation of laser intensity in a water body, so that the polygon function is used for fitting the water back scattering waveform in the prior art, and the accuracy of the solved laser echo position and echo intensity is low.
Disclosure of Invention
The invention provides a novel waveform detection method based on model fitting, which is mainly characterized in that a novel nonlinear function fitting water body backscattering waveform is constructed, and the characteristic that the laser intensity is exponentially attenuated in a water body is better met.
In order to achieve the above purpose, the invention provides the following technical scheme:
a waveform detection method based on model fitting comprises the following steps:
A. collecting effective waveform data of depth measurement LiDAR, reading full waveform data from airborne laser radar depth measurement data, removing invalid points caused by system errors and noise, removing land laser points according to the position and depth information of laser depth measurement points, and selecting effective water laser points;
B. extracting the transmitting signal waveform and the echo signal waveform of each water laser point, and solving the sounding LiDAR echo signal intensity through the following equations:
Figure BDA0002977743160000021
Figure BDA0002977743160000022
wherein, PbRepresenting the bottom echo intensity, P, acquired by a sounding LiDAR receiverwRepresenting the water backscatter echo intensity, PTRepresenting the laser emission intensity, ρ representing the substrate reflectivity, η representing the overall attenuation coefficient of the system, FpDenotes the field angle coefficient, nwDenotes the refractive index of the water body, ArDenotes the aperture area of the sounding LiDAR laser receiver, theta denotes the zenith angle, M (theta)i) Indicating a hot spot effect, N (θ)i) The pulse stretching effect H represents the flight height of the airplane, D represents the water depth, tau represents the optical thickness of the atmosphere, and beta represents the volume scattering coefficient; the sounding LiDAR return signal consists of three parts: water surface echo, water bottom echo, water body back scattering echo;
C. extracting water surface and water bottom echo waveforms from depth sounding LiDAR echo waveforms by using Gaussian decomposition algorithm, and Gaussian function fs(t) can be expressed as:
Figure BDA0002977743160000023
wherein WR(t) represents the received echo signal strength, αiSignal strength, mu, representing the ith Gaussian functioniIndicating the position of the echo, deltaiRepresenting the waveform width (standard deviation), N representing the number of Gaussian functions used for fitting, by solving for the function fs(t) taking N as 2 to obtain the water surface echo and the water bottom echo waveform;
D. constructing a new water body backscattering waveform function model, fitting a water body backscattering waveform with exponentially decayed laser intensity, wherein a fitting function fv (t) is as follows:
Figure BDA0002977743160000031
according to the characteristics of the water body, the water body backscattering waveform model is decomposed into five sections, wherein aB, c and d are respectively water back scattering waveform points X1，X2，X3And X4The abscissa (time, abbreviated as t, in ns); k. m and d are points X2，X3And X4The corresponding ordinate on the wave curve;
in the above formula, when t is less than or equal to a, fv(t) is 0; when t is more than 1 and less than or equal to b or c is more than t and less than or equal to d, fv(t) is a line segment, the function of which can be represented by X1，X2，X3And X4Obtaining coordinates; when b is more than t and less than or equal to c, fv(t) is an exponentially decaying curve according to X2，X3Coordinates, and a water body backscattering wave function model can be obtained by applying an undetermined coefficient method;
E. the water body backscattering waveform constructed by the method is combined with the water surface echo waveform and the water bottom echo waveform to calculate the laser echo position and the echo intensity.
A model fitting based waveform detection system includes a processor for executing instructions to implement a model fitting based waveform detection method.
The invention has the beneficial effects that:
the invention establishes a novel waveform detection method and system based on model fitting. Different from the traditional water body linear fitting method, the method constructs a new water body backscattering waveform model according to the characteristic of exponential attenuation of laser in the water body, the acquired water body backscattering waveform is closer to the actual water body echo waveform, and a solution is provided for high-precision detection of the laser echo.
The invention can improve the detection precision of the echo position and the echo intensity. The traditional waveform fitting method assumes that the echo waveform of the laser water body is linearly attenuated, although the detection efficiency is high, the error is relatively large, the method can improve the detection precision of the echo position and intensity, and has certain superiority.
Drawings
FIG. 1 is a schematic diagram of a linear function fitting echo waveform in the prior art;
FIG. 2 is a schematic diagram of a fitted echo waveform of the present invention;
FIG. 3 is a diagram of a prior art linear function fitting water backscatter waveform;
FIG. 4 is a schematic diagram of a fitted water backscatter waveform of the present invention;
FIG. 5 is a schematic diagram of a backscatter waveform model constructed in accordance with the invention;
fig. 6 is a block schematic diagram of the waveform detection method of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings:
a waveform detection method based on model fitting comprises the following steps:
A. collecting effective waveform data of depth measurement LiDAR, reading full waveform data from airborne laser radar depth measurement data, removing invalid points caused by system errors and noise, removing land laser points according to the position and depth information of laser depth measurement points, and selecting effective water laser points;
B. extracting the transmitting signal waveform and the echo signal waveform of each water laser point, and solving the sounding LiDAR echo signal intensity through the following equations:
Figure BDA0002977743160000051
Figure BDA0002977743160000052
wherein, PbRepresenting the bottom echo intensity, P, acquired by a sounding LiDAR receiverwRepresenting the water backscatter echo intensity, PTRepresenting the laser emission intensity, ρ representing the substrate reflectivity, η representing the overall attenuation coefficient of the system, FpDenotes the field angle coefficient, nwDenotes the refractive index of the water body, ArDenotes the aperture area of the sounding LiDAR laser receiver, theta denotes the zenith angle, M (theta)i) Indicating a hot spot effect, N (θ)i) The pulse stretching effect H represents the flight height of the airplane, D represents the water depth, and tau representsAtmospheric optical thickness, β represents the bulk scattering coefficient; the sounding LiDAR return signal consists of three parts: water surface echo, water bottom echo, water body back scattering echo;
C. extracting water surface and water bottom echo waveforms from depth sounding LiDAR echo waveforms by using Gaussian decomposition algorithm, and Gaussian function fs(t) can be expressed as:
Figure BDA0002977743160000053
wherein WR(t) represents the received echo signal strength, αiSignal strength, mu, representing the ith Gaussian functioniIndicating the position of the echo, deltaiRepresenting the waveform width (standard deviation), N representing the number of Gaussian functions used for fitting, by solving for the function fs(t) taking N as 2 to obtain the water surface echo and the water bottom echo waveform, as shown in FIG. 2;
D. constructing a new water body backscattering waveform function model, and fitting a water body backscattering waveform with exponentially decaying laser intensity, wherein a fitting function fv (t) is as shown in fig. 4:
Figure BDA0002977743160000061
according to the characteristics of the water body, the water body backscattering waveform model is decomposed into five segments as shown in fig. 5, wherein a, b, c and d are respectively water body backscattering waveform points X1，X2，X3And X4The abscissa (time, abbreviated as t, in ns); k. m and d are points X2，X3And X4The corresponding ordinate on the wave curve;
in the above formula, when t is less than or equal to a, fv(t) is 0; when t is more than 1 and less than or equal to b or c is more than t and less than or equal to d, fv(t) is a line segment, the function of which can be represented by X1，X2，X3And X4Obtaining coordinates; when b is more than t and less than or equal to c, fv(t) is an exponentially decaying curve according to X2，X3The coordinates of the position of the object to be imaged,a water body backscattering wave function model can be obtained by applying a undetermined coefficient method, as shown in FIG. 4;
E. the water body backscattering waveform constructed by the method is combined with the water surface echo waveform and the water bottom echo waveform to calculate the laser echo position and the echo intensity.
A model fitting based waveform detection system includes a processor for executing instructions to implement a model fitting based waveform detection method.
The invention establishes a novel waveform detection method and system based on model fitting. Different from the traditional water body linear fitting method, the method constructs a new water body backscattering waveform model according to the characteristic of exponential attenuation of laser in the water body, the acquired water body backscattering waveform is closer to the actual water body echo waveform, and a solution is provided for high-precision detection of the laser echo.
The invention can improve the detection precision of the echo position and the echo intensity. The traditional waveform fitting method assumes that the echo waveform of the laser water body is linearly attenuated, although the detection efficiency is high, the error is relatively large, the method can improve the detection precision of the echo position and intensity, and has certain superiority.
The above description is not intended to limit the technical scope of the present invention in any way, and any modifications to the above embodiments in accordance with the technical spirit of the present invention are possible; equivalent changes and modifications are also within the scope of the technical solution of the present invention.

Claims (2)

1. A waveform detection method based on model fitting is characterized in that: the method comprises the following steps:
A. collecting effective waveform data of depth measurement LiDAR, reading full waveform data from airborne laser radar depth measurement data, removing invalid points caused by system errors and noise, removing land laser points according to the position and depth information of laser depth measurement points, and selecting effective water laser points;
B. extracting the transmitting signal waveform and the echo signal waveform of each water laser point, and solving the sounding LiDAR echo signal intensity through the following equations:
Figure FDA0002977743150000011
Figure FDA0002977743150000012
wherein, PbRepresenting the bottom echo intensity, P, acquired by a sounding LiDAR receiverwRepresenting the water backscatter echo intensity, PTRepresenting the laser emission intensity, ρ representing the substrate reflectivity, η representing the overall attenuation coefficient of the system, FpDenotes the field angle coefficient, nwDenotes the refractive index of the water body, ArDenotes the aperture area of the sounding LiDAR laser receiver, theta denotes the zenith angle, M (theta)i) Indicating a hot spot effect, N (θ)i) The pulse stretching effect H represents the flight height of the airplane, D represents the water depth, tau represents the optical thickness of the atmosphere, and beta represents the volume scattering coefficient; the sounding LiDAR return signal consists of three parts: water surface echo, water bottom echo, water body back scattering echo;
C. extracting water surface and water bottom echo waveforms from depth sounding LiDAR echo waveforms by using Gaussian decomposition algorithm, and Gaussian function fs(t) can be expressed as:
Figure FDA0002977743150000021
wherein WR(t) represents the received echo signal strength, αiSignal strength, mu, representing the ith Gaussian functioniIndicating the position of the echo, deltaiRepresenting the waveform width (standard deviation), N representing the number of Gaussian functions used for fitting, by solving for the function fs(t) taking N as 2 to obtain the water surface echo and the water bottom echo waveform;
D. constructing a new water body backscattering waveform function model, fitting a water body backscattering waveform with exponentially decayed laser intensity, wherein a fitting function fv (t) is as follows:
Figure FDA0002977743150000022
according to the characteristics of the water body, the water body backscattering waveform model is decomposed into five sections, wherein a, b, c and d are respectively water body backscattering waveform points X1，X2，X3And X4The abscissa (time, abbreviated as t, in ns); k. m and d are points X2，X3And X4The corresponding ordinate on the wave curve;
in the above formula, when t is less than or equal to a, fv(t) is 0; when t is more than 1 and less than or equal to b or c is more than t and less than or equal to d, fv(t) is a line segment, the function of which can be represented by X1，X2，X3And X4Obtaining coordinates; when b is more than t and less than or equal to c, fv(t) is an exponentially decaying curve according to X2，X3Coordinates, and a water body backscattering wave function model can be obtained by applying an undetermined coefficient method;
E. the water body backscattering waveform constructed by the method is combined with the water surface echo waveform and the water bottom echo waveform to calculate the laser echo position and the echo intensity.
2. A waveform detection system based on model fitting is characterized in that: comprising a processor for executing instructions for implementing the waveform detection method of claim 1.
CN202110279037.2A 2021-03-16 2021-03-16 Waveform detection method and system based on model fitting Pending CN113030919A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110279037.2A CN113030919A (en) 2021-03-16 2021-03-16 Waveform detection method and system based on model fitting

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110279037.2A CN113030919A (en) 2021-03-16 2021-03-16 Waveform detection method and system based on model fitting

Publications (1)

Publication Number Publication Date
CN113030919A true CN113030919A (en) 2021-06-25

Family

ID=76470693

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110279037.2A Pending CN113030919A (en) 2021-03-16 2021-03-16 Waveform detection method and system based on model fitting

Country Status (1)

Country Link
CN (1) CN113030919A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113534096A (en) * 2021-07-19 2021-10-22 东莞理工学院 LiDAR signal geometric feature extraction method and system based on spline function
CN116609758A (en) * 2023-07-17 2023-08-18 山东科技大学 Extraction method for airborne laser sounding waveform during travel

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106125088A (en) * 2016-08-29 2016-11-16 天津大学 Sea water advanced method is determined based on laser radar sounding system
CN106556824A (en) * 2016-10-14 2017-04-05 深圳大学 A kind of noise echo elimination method and system of all-wave graphic data
CN106802289A (en) * 2017-01-20 2017-06-06 深圳大学 Unrestrained attenuation coefficient extracting method and system based on depth measurement laser all-wave graphic data
CN110031856A (en) * 2019-04-04 2019-07-19 山东科技大学 A kind of unrestrained attenuation coefficient extracting method of airborne LiDAR depth measurement data
CN110134976A (en) * 2018-02-09 2019-08-16 中国人民解放军战略支援部队信息工程大学 A kind of airborne laser sounding method for extracting signal and system

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106125088A (en) * 2016-08-29 2016-11-16 天津大学 Sea water advanced method is determined based on laser radar sounding system
CN106556824A (en) * 2016-10-14 2017-04-05 深圳大学 A kind of noise echo elimination method and system of all-wave graphic data
CN106802289A (en) * 2017-01-20 2017-06-06 深圳大学 Unrestrained attenuation coefficient extracting method and system based on depth measurement laser all-wave graphic data
CN110134976A (en) * 2018-02-09 2019-08-16 中国人民解放军战略支援部队信息工程大学 A kind of airborne laser sounding method for extracting signal and system
CN110031856A (en) * 2019-04-04 2019-07-19 山东科技大学 A kind of unrestrained attenuation coefficient extracting method of airborne LiDAR depth measurement data

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
KAI DING等: "A New Algorithm for Retrieving Diffuse Attenuation Coefficient Based on Big LiDAR Bathymetry Data", 《INTERNATIONAL SYMPOSIUM ON CYBERSPACE SAFETY AND SECURITY》 *
KAI DING等: "An Improved Quadrilateral Fitting Algorithm for the Water Column Contribution in Airborne Bathymetric Lidar Waveforms", 《SENSORS》 *
丁凯: "单波段机载测深激光雷达全波形数据处理算法及应用研究", 《中国优秀博硕士学位论文全文数据库(博士)信息科技辑(月刊)》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113534096A (en) * 2021-07-19 2021-10-22 东莞理工学院 LiDAR signal geometric feature extraction method and system based on spline function
CN113534096B (en) * 2021-07-19 2023-09-15 东莞理工学院 LiDAR signal geometric feature extraction method and system based on spline function
CN116609758A (en) * 2023-07-17 2023-08-18 山东科技大学 Extraction method for airborne laser sounding waveform during travel
CN116609758B (en) * 2023-07-17 2023-10-27 山东科技大学 Extraction method for airborne laser sounding waveform during travel

Similar Documents

Publication Publication Date Title
CN108845306B (en) Laser radar echo signal denoising method based on variational modal decomposition
CN111524084B (en) Photon counting laser radar point cloud denoising method based on multi-peak Gaussian fitting
CN106802289B (en) Unrestrained attenuation coefficient extracting method and system based on depth measurement laser all-wave graphic data
CN106500671B (en) Method for determining sea water depth by decomposing laser radar waveform based on LM algorithm
CN110673108B (en) Airborne marine laser radar signal processing method based on iteration Klett
CN110031856A (en) A kind of unrestrained attenuation coefficient extracting method of airborne LiDAR depth measurement data
CN113030919A (en) Waveform detection method and system based on model fitting
CN112285742B (en) Method for estimating carrier-to-noise ratio of coherent wind lidar in frequency domain
CN113311398A (en) Tracking method for high maneuvering dim small target with strong clutter complex background
JPH0980146A (en) Radar apparatus
CN110879391B (en) Radar image data set manufacturing method based on electromagnetic simulation and missile-borne echo simulation
CN117572384B (en) Method for improving detection performance of laser radar
CN116609758B (en) Extraction method for airborne laser sounding waveform during travel
CN108761384B (en) Target positioning method for robust sensor network
CN114184256A (en) Water level measuring method under multi-target background
CN106556824A (en) A kind of noise echo elimination method and system of all-wave graphic data
CN111951204B (en) Sea surface wind speed inversion method for Tiangong No. two detection data based on deep learning
WO2021179583A1 (en) Detection method and detection device
CN117368877A (en) Radar image clutter suppression and target detection method based on generation countermeasure learning
CN112130166A (en) AGV positioning method and device based on reflector network
CN113534096B (en) LiDAR signal geometric feature extraction method and system based on spline function
CN105699981B (en) A kind of hardware and software fitting method for measuring ceiling of clouds and thickness
CN116068503A (en) Combined calibration method and device for millimeter wave radar and laser radar and terminal equipment
CN113359145A (en) Target accurate positioning method in pulse laser ranging and application thereof
CN111948607A (en) Deep sea target passive positioning and particle filtering tracking method

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20210625

RJ01 Rejection of invention patent application after publication