CN116299236A - InSAR atmospheric error correction method based on thinning PS point - Google Patents

InSAR atmospheric error correction method based on thinning PS point Download PDF

Info

Publication number
CN116299236A
CN116299236A CN202310248334.XA CN202310248334A CN116299236A CN 116299236 A CN116299236 A CN 116299236A CN 202310248334 A CN202310248334 A CN 202310248334A CN 116299236 A CN116299236 A CN 116299236A
Authority
CN
China
Prior art keywords
point
data
distance
point data
delay phase
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
CN202310248334.XA
Other languages
Chinese (zh)
Inventor
董晓虎
程绳
金哲
李小来
杜勇
王身丽
李陶
刘杰
马思捷
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.)
Super High Voltage Co Of State Grid Hubei Electric Power Co ltd
State Grid Hubei Electric Power Co Ltd
Original Assignee
Super High Voltage Co Of State Grid Hubei Electric Power Co ltd
State Grid Hubei Electric Power Co Ltd
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 Super High Voltage Co Of State Grid Hubei Electric Power Co ltd, State Grid Hubei Electric Power Co Ltd filed Critical Super High Voltage Co Of State Grid Hubei Electric Power Co ltd
Priority to CN202310248334.XA priority Critical patent/CN116299236A/en
Publication of CN116299236A publication Critical patent/CN116299236A/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
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/40—Means for monitoring or calibrating
    • 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
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • 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
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Landscapes

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

Abstract

The invention provides an InSAR atmospheric error correction method based on an thinning PS point, which comprises the following steps: acquiring point location detection data of a radar signal in a target area; the point location detection data comprises PS point data and non-PS point data; performing thinning on PS point data according to the point density to obtain thinned PS point data; filtering the data of the PS point after the thinning to obtain a turbulent atmosphere delay phase; and correcting the PS point data of the target area according to the turbulence atmosphere delay phase to obtain corrected PS point data. According to the invention, the PS points are filtered to obtain the turbulence atmospheric delay phase, and finally the PS points in the target area are corrected by using a Kriging interpolation method, so that the correction accuracy of the atmospheric phase can be effectively improved.

Description

InSAR atmospheric error correction method based on thinning PS point
Technical Field
The invention relates to the technical field of synthetic aperture radars, in particular to an InSAR atmospheric error correction method based on an thinning PS point.
Background
When a radar signal propagates between a satellite and the ground, the radar signal passes through an atmosphere layer, refraction phenomenon occurs, phase propagation delay is caused, and then the measurement result of the ground deformation information is affected. And in the single-track InSAR mode, the propagation delay of the atmospheric phase is similar in the two observation processes of the master image and the slave image, so that the influence of the atmosphere on the InSAR measurement result can be mutually counteracted after interference treatment. However, in most cases, this is not the case, and the atmospheric effect phase is generated because the atmospheric condition changes during the image acquisition period in the repetitive orbit pattern, which causes the atmospheric effect phase to be greatly affected by the atmosphere. Atmospheric effects are one of the most important error sources limiting the measurement accuracy of the InSAR technique.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide an InSAR atmospheric error correction method based on a thinning PS point.
In order to achieve the above object, the present invention provides the following solutions:
an InSAR atmospheric error correction method based on a thinning PS point comprises the following steps:
acquiring point location detection data of a radar signal in a target area; the point location detection data comprises PS point data and non-PS point data;
thinning the PS point data according to the point density to obtain thinned PS point data;
filtering the PS point data after the thinning to obtain a turbulent atmosphere delay phase;
and correcting the PS point data of the target area according to the turbulence atmosphere delay phase to obtain corrected PS point data.
Preferably, the thinning the PS point data according to the dot density to obtain thinned PS point data includes:
dividing the point detection data into a plurality of circular point intervals by taking any point as a circle center and taking a preset distance as a radius;
calculating the number of PS points in each circular point position interval, and taking the number of the corresponding PS points as the point position density;
and performing thinning on the PS point data according to the point density and the point density threshold value to obtain thinned PS point data.
Preferably, the calculating the number of PS points in each circular point location interval and taking the number of corresponding PS points as the point location density includes:
the formula is adopted:
Figure BDA0004126803830000021
calculating the number of PS points in each circular point position interval; wherein m represents the point density, (i, j) represents the center of the circular point location interval, (ii, jj) represents the point coordinates except the center of the circle in the circular point location interval, and the PS point in the circular point location interval is marked as 1, the non-PS point is marked as 0.
Preferably, correcting PS point data of the target area according to the turbulent atmospheric delay phase to obtain corrected PS point data includes:
and correcting the PS point data by using a Kriging interpolation method according to the turbulence atmospheric delay phase to obtain corrected PS point data.
Preferably, the correcting the PS point data by using a Kriging interpolation method according to the turbulence atmospheric delay phase to obtain corrected PS point data includes:
calculating the distance between each PS point data and the corresponding turbulence atmosphere delay phase variance thereof to form a data queue;
dividing the data queue into a plurality of distance groups;
calculating the estimated value of the variation function corresponding to each distance group;
fitting the estimated value by using a preset variation function to obtain a fitted variation function;
and correcting the PS point data by using the variation function completed by fitting to obtain corrected PS point data.
Preferably, the calculating the distance between each PS point data and its corresponding turbulent atmospheric delay phase variance includes:
the formula is adopted:
Figure BDA0004126803830000031
Figure BDA0004126803830000032
calculating the distance between each PS point data and the corresponding turbulence atmosphere delay phase variance; wherein s is ij Represents the distance between the ith PS point and the jth PS point, (x) i ,y i ) Representing the coordinates of the ith PS point, (x) j ,y j ) Representing the coordinates of the jth PS point,
Figure BDA0004126803830000033
represents the turbulence atmospheric delay phase variance between the ith and jth PS points,/->
Figure BDA0004126803830000034
Turbulent atmosphere delay phase representing the ith PS point,/->
Figure BDA0004126803830000035
The turbulent atmosphere delay phase at the jth PS point is shown.
Preferably, the calculating the estimated value of the variation function corresponding to each distance group includes:
the formula is adopted:
Figure BDA0004126803830000036
calculating the estimated value of the variation function corresponding to each distance group; wherein N is H Represents the number of distance groups, maxh ij Represents the maximum distance value between PS points in the mth distance group, minh ij Represents the smallest distance value between PS points in the mth distance group, N (h' m ) The number of PS point pairs separated by a distance h is indicated,
Figure BDA0004126803830000037
represents the turbulent atmospheric delay phase between PS point pairs separated by a distance h.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides an InSAR atmospheric error correction method based on an thinning PS point, which comprises the following steps: acquiring point location detection data of a radar signal in a target area; the point location detection data comprises PS point data and non-PS point data; performing thinning on PS point data according to the point density to obtain thinned PS point data; filtering the data of the PS point after the thinning to obtain a turbulent atmosphere delay phase; and correcting the PS point data of the target area according to the turbulence atmosphere delay phase to obtain corrected PS point data. According to the invention, the PS points are filtered to obtain the turbulence atmospheric delay phase, and finally the PS points in the target area are corrected by using a Kriging interpolation method, so that the correction accuracy of the atmospheric phase can be effectively improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an InSAR atmospheric error correction method based on a thinning PS point;
FIG. 2 is a plot of PS point location provided by the present invention;
fig. 3 is a PS dot density map provided by the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The terms "first," "second," "third," and "fourth" and the like in the description and in the claims of this application and in the drawings, are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, inclusion of a list of steps, processes, methods, etc. is not limited to the listed steps but may alternatively include steps not listed or may alternatively include other steps inherent to such processes, methods, products, or apparatus.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
In order to achieve the above object, the present invention provides the following solutions:
referring to fig. 1, an InSAR atmospheric error correction method based on an thinning PS point includes:
step 1: acquiring point location detection data of a radar signal in a target area; the point location detection data comprises PS point data and non-PS point data;
the radar signal atmospheric delay additional phase is mainly caused by the vertical stratification and turbulent mixing process of the atmosphere. Since vertical stratification in an atmosphere model has a correlation with elevation. Therefore, in the region where the difference in topography is large, the atmospheric error concerning Gao Chengyou needs to be removed in combination with the elevation model.
Step 2: thinning the PS point data according to the point density to obtain thinned PS point data;
further, step 2 includes:
dividing the point detection data into a plurality of circular point intervals by taking any point as a circle center and taking a preset distance as a radius;
calculating the number of PS points in each circular point position interval, and taking the number of the corresponding PS points as the point position density;
referring to fig. 2-3, a calculated radius r is set with a point (i, i) as a center, other point coordinates in the radius are (ii, jj), wherein (-r is not less than ii is not less than r, -r is not less than jj is not less than r), black points in the radius are PS points, marked as 1, gray points are non-PS points, marked as 0, and the point density m of the points is calculated:
Figure BDA0004126803830000051
wherein m represents the point density, (i, j) represents the center of the circular point location interval, (ii, jj) represents the point coordinates except the center of the circle in the circular point location interval, and the PS point in the circular point location interval is marked as 1, the non-PS point is marked as 0.
And performing thinning on the PS point data according to the point density and the point density threshold value to obtain thinned PS point data.
Step 3: filtering the PS point data after the thinning to obtain a turbulent atmosphere delay phase;
the spatial domain filtering efficiency is affected by two aspects, namely, inversely proportional to a filtering window, the larger the window is, the lower the efficiency is, and the more PS points are, the lower the calculation efficiency is due to the number of PS points in the window. In the invention, a thinning criterion is set according to the point density. And providing that the dot density threshold value is set, the dot larger than the threshold value is thinned by adopting a small step length, and the dot smaller than the threshold value is thinned by adopting a large step length. The PS point thinning method based on the point density can realize the PS point thinning in a self-adaptive mode, so that the PS point thinning of high-density points can be realized, the PS point density of a low-density area is reserved, and the calculation efficiency of the atmospheric filtering treatment can be effectively improved.
Step 4: and correcting the PS point data of the target area according to the turbulence atmosphere delay phase to obtain corrected PS point data. According to the invention, the PS point data can be corrected by adopting a Kriging interpolation method according to the turbulence atmosphere delay phase to obtain corrected PS point data.
Specifically, step 4 includes:
calculating the distance between each PS point data and the corresponding turbulence atmosphere delay phase variance thereof to form a data queue;
in the present invention, the formula may be employed:
Figure BDA0004126803830000061
Figure BDA0004126803830000062
calculating the distance between each PS point data and the corresponding turbulence atmosphere delay phase variance; wherein s is ij Represents the distance between the ith PS point and the jth PS point, (x) i ,y i ) Representing the coordinates of the ith PS point, (x) j ,y j ) Representing the coordinates of the jth PS point,
Figure BDA0004126803830000063
represents the turbulence atmosphere delay phase variance, phi, between the ith PS point and the jth PS point i atm Turbulent atmosphere delay phase representing the ith PS point,/->
Figure BDA0004126803830000064
The turbulent atmosphere delay phase at the jth PS point is shown.
Dividing the data queue into a plurality of distance groups;
calculating the estimated value gamma of the variation function corresponding to each distance group * (h)；
Figure BDA0004126803830000065
Wherein N is H Represents the number of distance groups, maxh ij Represents the maximum distance value between PS points in the mth distance group, minh ij Represents the smallest distance value between PS points in the mth distance group, N (h' m ) The number of PS point pairs separated by a distance h is indicated,
Figure BDA0004126803830000066
representing turbulent atmospheric delay phase between PS point pairs separated by a distance h
Note that, when dividing the data set, two points should be noted: (1) ensuring meaningful parameters in the variation function, dividing at least 3-4 groups to calculate the variation function gamma * (h' m ) I.e. N H Not less than 4; (2) ensuring that each distance group includes enough data to enable gamma * (h' m ) The value is more reliable, i.e. N (h' m ) Is large enough.
Fitting the estimated value by using a preset variation function to obtain a fitted variation function;
after the fitting is completed, the invention also needs to check the variation function of the fitting completion. The invention has 2 methods to select: (1) a cross-checking method. Namely, the observed values at the observation points are compared with the estimated values calculated by the variation function after fitting, and when the mean value of errors tends to 0 and the variance is minimum, the structural model is most suitable. (2) And checking by using the variance of the dispersion.
And correcting the PS point data by using the variation function completed by fitting to obtain corrected PS point data. Furthermore, after the fitted variation function is obtained, the coefficient matrix K of the Kriging equation can be utilized to correct the PS point data to obtain corrected PS point data.
According to the invention, the PS points are filtered to obtain the turbulence atmospheric delay phase, and finally the PS points in the target area are corrected by using a Kriging interpolation method, so that the correction accuracy of the atmospheric phase can be effectively improved.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the method disclosed in the embodiment, since it corresponds to the device disclosed in the embodiment, the description is relatively simple, and the relevant points are referred to the device part description.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.

Claims (7)

1. An InSAR atmospheric error correction method based on a thinning PS point is characterized by comprising the following steps:
acquiring point location detection data of a radar signal in a target area; the point location detection data comprises PS point data and non-PS point data;
thinning the PS point data according to the point density to obtain thinned PS point data;
filtering the PS point data after the thinning to obtain a turbulent atmosphere delay phase;
and correcting the PS point data of the target area according to the turbulence atmosphere delay phase to obtain corrected PS point data.
2. The method for correcting the atmospheric error of the InSAR based on the thinned PS point according to claim 1, wherein the thinning the PS point data according to the point density to obtain thinned PS point data comprises the following steps:
dividing the point detection data into a plurality of circular point intervals by taking any point as a circle center and taking a preset distance as a radius;
calculating the number of PS points in each circular point position interval, and taking the number of the corresponding PS points as the point position density;
and performing thinning on the PS point data according to the point density and the point density threshold value to obtain thinned PS point data.
3. The method for correcting the atmospheric error of the InSAR based on the sparse PS points according to claim 2, wherein the calculating the number of the PS points in each circular point location interval and taking the number of the corresponding PS points as the point location density comprises the following steps:
the formula is adopted:
Figure FDA0004126803810000011
calculating the number of PS points in each circular point position interval; wherein m represents the point density, (i, j) represents the center of the circular point location interval, (ii, jj) represents the point coordinates except the center of the circle in the circular point location interval, and the PS point in the circular point location interval is marked as 1, the non-PS point is marked as 0.
4. The method for correcting the atmospheric error of the InSAR based on the PS point of the thin film according to claim 3, wherein the step of correcting the PS point data of the target area according to the turbulence atmospheric delay phase to obtain corrected PS point data comprises the following steps:
and correcting the PS point data by using a Kriging interpolation method according to the turbulence atmospheric delay phase to obtain corrected PS point data.
5. The InSAR atmospheric error correction method based on the dilute PS point according to claim 4, wherein the corrected PS point data is obtained by correcting the PS point data by using a Kriging interpolation method according to the turbulence atmospheric delay phase, comprising:
calculating the distance between each PS point data and the corresponding turbulence atmosphere delay phase variance thereof to form a data queue;
dividing the data queue into a plurality of distance groups;
calculating the estimated value of the variation function corresponding to each distance group;
fitting the estimated value by using a preset variation function to obtain a fitted variation function;
and correcting the PS point data by using the variation function completed by fitting to obtain corrected PS point data.
6. The method for correcting the atmospheric error of the InSAR based on the PS points according to claim 5, wherein the step of calculating the distance between each PS point data and the corresponding turbulence atmospheric delay phase variance comprises the steps of:
the formula is adopted:
Figure FDA0004126803810000021
Figure FDA0004126803810000022
calculating the distance between each PS point and its corresponding turbulenceFlow atmospheric delay phase variance; wherein s is ij Represents the distance between the ith PS point and the jth PS point, (x) i ,y i ) Representing the coordinates of the ith PS point, (x) j ,y j ) Representing the coordinates of the jth PS point,
Figure FDA0004126803810000023
represents the turbulence atmospheric delay phase variance between the ith and jth PS points,/->
Figure FDA0004126803810000025
Turbulent atmosphere delay phase representing the ith PS point,/->
Figure FDA0004126803810000024
The turbulent atmosphere delay phase at the jth PS point is shown.
7. The method for correcting the atmospheric error of the InSAR based on the thinned PS point according to claim 6, wherein the calculating the estimated value of the variation function corresponding to each distance group comprises:
the formula is adopted:
Figure FDA0004126803810000031
calculating the estimated value of the variation function corresponding to each distance group; wherein N is H Represents the number of distance groups, maxh ij Represents the maximum distance value between PS points in the mth distance group, minh ij Represents the smallest distance value between PS points in the mth distance group, N (h' m ) The number of PS point pairs separated by a distance h is indicated,
Figure FDA0004126803810000032
represents the turbulent atmospheric delay phase between PS point pairs separated by a distance h.
CN202310248334.XA 2023-03-15 2023-03-15 InSAR atmospheric error correction method based on thinning PS point Pending CN116299236A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310248334.XA CN116299236A (en) 2023-03-15 2023-03-15 InSAR atmospheric error correction method based on thinning PS point

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310248334.XA CN116299236A (en) 2023-03-15 2023-03-15 InSAR atmospheric error correction method based on thinning PS point

Publications (1)

Publication Number Publication Date
CN116299236A true CN116299236A (en) 2023-06-23

Family

ID=86825247

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310248334.XA Pending CN116299236A (en) 2023-03-15 2023-03-15 InSAR atmospheric error correction method based on thinning PS point

Country Status (1)

Country Link
CN (1) CN116299236A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112816983A (en) * 2021-01-06 2021-05-18 中南大学 Time sequence InSAR turbulence atmospheric delay correction method based on optimized interferogram set

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112816983A (en) * 2021-01-06 2021-05-18 中南大学 Time sequence InSAR turbulence atmospheric delay correction method based on optimized interferogram set
CN112816983B (en) * 2021-01-06 2023-09-19 中南大学 Time sequence InSAR turbulence atmosphere delay correction method based on optimized interference atlas

Similar Documents

Publication Publication Date Title
CN113534159B (en) Sea surface wind speed inversion method and system based on SAR satellite remote sensing data
CN103729846B (en) LiDAR point cloud data edge detection method based on triangular irregular network
CN112906547B (en) Railway train windshield breakage fault detection method based on E-YOLO
CN116299236A (en) InSAR atmospheric error correction method based on thinning PS point
CN112819958B (en) Engineering geological mapping method and system based on three-dimensional laser scanning
CN113313047B (en) Lane line detection method and system based on lane structure prior
CN114155501A (en) Target detection method of unmanned vehicle in smoke shielding environment
CN113720428B (en) Vehicle speed perception dynamic weighing compensation method based on artificial intelligence and computer vision
CN106646430A (en) Laser footprint center determining method based on ground detector
CN116310837B (en) SAR ship target rotation detection method and system
KR20230132686A (en) A method for damage identification and volume quantification of concrete pipes based on PointNet++ neural network
CN115272456A (en) Laser radar and camera online drift detection method, correction method, device and storage medium
CN115545100A (en) GB-InSAR atmospheric phase compensation method based on LSTM
CN113781478B (en) Oil tank image detection method, oil tank image detection device, electronic equipment and computer readable medium
CN110706177A (en) Method and system for equalizing gray level of side-scan sonar image
CN111308468B (en) Method for automatically identifying deformation risk area based on InSAR technology
CN111175709B (en) Error suppression-based large-range meteorological radar-oriented jigsaw method
CN112966656A (en) Data processing method and device
CN111523392A (en) Deep learning sample preparation method and recognition method based on satellite ortho-image full-attitude
CN115980697A (en) Method for inverting boundary layer height by using laser radar under different weather conditions
CN116862829A (en) Overhead line sag monitoring method and device in ice-covered environment
CN110780300B (en) Data processing method for wind profile radar
CN111833395B (en) Direction-finding system single target positioning method and device based on neural network model
CN114120236A (en) Method for identifying and positioning low-altitude target
CN109615874B (en) Road condition analysis method based on form tower psychological criterion

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