CN109655811A - The extra large airborne LiDAR systematic error calibration model modelling approach of the dual-purpose double frequency in land - Google Patents
The extra large airborne LiDAR systematic error calibration model modelling approach of the dual-purpose double frequency in land Download PDFInfo
- Publication number
- CN109655811A CN109655811A CN201811329065.5A CN201811329065A CN109655811A CN 109655811 A CN109655811 A CN 109655811A CN 201811329065 A CN201811329065 A CN 201811329065A CN 109655811 A CN109655811 A CN 109655811A
- Authority
- CN
- China
- Prior art keywords
- model
- error
- parameter
- calibration
- airborne lidar
- 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
Links
- 230000009897 systematic effect Effects 0.000 title claims abstract description 20
- 238000013459 approach Methods 0.000 title claims abstract description 5
- 239000003643 water by type Substances 0.000 claims abstract description 7
- 239000013598 vector Substances 0.000 claims description 17
- 238000000034 method Methods 0.000 claims description 13
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 13
- 238000005259 measurement Methods 0.000 claims description 5
- 238000000611 regression analysis Methods 0.000 claims description 4
- -1 salinity Substances 0.000 claims description 3
- 238000012545 processing Methods 0.000 abstract description 2
- 239000011159 matrix material Substances 0.000 description 5
- 241000208340 Araliaceae Species 0.000 description 2
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 2
- 235000003140 Panax quinquefolius Nutrition 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 235000008434 ginseng Nutrition 0.000 description 2
- 238000007792 addition Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012805 post-processing Methods 0.000 description 1
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
- G01S7/497—Means for monitoring or calibrating
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Optical Radar Systems And Details Thereof (AREA)
Abstract
A kind of airborne LiDAR systematic error calibration model modelling approach of public extra large dual-purpose double frequency in land of the invention, including step 1, to airborne LiDAR, geometry location model simplification is land-based area three parameter model to control point data laid in land-based area calibration field according to acquisition etc. over the ground, step 2, laser waters propagation delay error model, step 3 are established, the parameter and model obtained according to step 1 and step 2, five parameter calibration models, i.e. the calibration model of the airborne LiDAR systematic error of sea area double frequency are constructed, parameter is resolved;Step 4, according to step 1, the parameter and model obtained in step 2 and step 3 finally constructs amphibious double frequency airborne LiDAR point cloud calibration model.The present invention establishes the calibration model for being suitable for the airborne LiDAR system point cloud of the dual-purpose double frequency in extra large land of land-based area and sea area, has filled up the blank problem of the airborne LiDAR systematic error calibration model of sea area double frequency, the processing capacity of related subsequent data has been driven to study very much.
Description
Technical field
The invention belongs to active microwave remote sensing technique fields, and it is airborne to especially relate to a kind of dual-purpose double frequency in extra large land
LiDAR systematic error calibration model modelling approach.
Background technique
By the fast development of more than ten years, airborne LiDAR system is quite mature in terms of hardware and the system integration, so
And the post-processing of its data and application study are then opposite develops slowly, wherein restrict the critical issue of its development first is that airborne
The elimination of LiDAR systematic error.System calibration is to eliminate the main method of systematic error, lacks a kind of calibration side of standard at present
Method, and the airborne LiDAR system calibration field built in the industry so far is land-based area calibration field, is not established suitable for sea area calibration
The systematic error calibration model of field.The present invention is passed through by carrying out correlation analysis to each systematic error using land-based area calibration field
Models computed disposes angle error, further establishes delay error model by analysis sea area calibration field hydrological environment information and is applied to
Sea area calibration field resolves placement vector error, range error and scanning angle error, and finally establishes and be suitable for land-based area and sea area
The calibration model of the extra large dual-purpose airborne LiDAR systematic error in land.
Summary of the invention
The present invention is directed to the blank problem of the airborne LiDAR systematic error calibration model of domestic sea area double frequency, provides one kind
The modeling method of the airborne LiDAR systematic error calibration model of the dual-purpose double frequency in extra large land suitable for land-based area and sea area.
The modeling process of the airborne LiDAR systematic error calibration model of the sea dual-purpose ranging in land provided by the invention includes following step
It is rapid: step 1, according to the control point data of acquisition laid in land-based area calibration field, the x measured by GPSGPS,yGPS,zGPS, attitude angle
H, P, R, placement vector Δ X, Δ Y, Δ Z, distance measurement value ρ and scan angle β, to airborne LiDAR, geometry location model simplification is over the ground
Land-based area three parameter model is used for inverse angle of setting, i.e., is navigated by the airborne LiDAR of double frequency in land-based area calibration field and fly data, in combination
Face metric data calculates angle of setting;Step 2, the hydrological data of the sea area calibration field of acquisition is analyzed, is examined in conjunction with sea area
The airborne LiDAR in drill ground, which navigates, flies data, establishes laser waters propagation delay mistake based on successive Regression and grey systems GM (1, n) combination
Delay error is introduced the airborne LiDAR systematic error calibration model in sea area of next step by differential mode type;Step 3, according to step 1 and
The parameter and model that step 2 obtains, to airborne LiDAR, geometry location model is optimized over the ground, is navigated by airborne LiDAR and is flown number
Five parameter calibration models of building, i.e. the calibration model of the airborne LiDAR systematic error of sea area double frequency are made the difference according to middle same place, resolve ginseng
Number;Step 4, according to step 1, it is airborne finally to construct amphibious double frequency for the parameter and model obtained in step 2 and step 3
LiDAR point cloud calibration model.
Preferably, in the step 1, xGPS,yGPS,zGPSIt is measured by GPS, attitude angle H, P, R are mentioned by inertial navigation system
For disposing vector Δ X, Δ Y, Δ Z can be measured in platform calibration by total station, and distance measurement value ρ and scan angle β are swept by laser ranging
Instrument offer is retouched, by unknown angle of settingAs system parameter, by airborne LiDAR geometry location model simplification over the ground
For three parameter model, error equation is established, resolves angle of setting using least square method,
Preferably, in the step 2, sea area calibration field hydrological data chooses water temperature, the depth of water, salinity, and water colour is transparent
Degree, hydraulic parameters introduce using successive Regression and examine hydrologic parameter conspicuousness, select strongest with delay error correlation
Parameter;Simultaneously using the correlation intensity analysis between grey systems GM (1, n) Lai Jinhang variable, finally by Gradual regression analysis model and
The weighted array of grey systems GM (1, n) two kinds of models, establishes laser waters propagation delay error model, then establishes ranging mistake
Differential mode type.
Preferably, being linear scan in the scanning mode of satisfaction (a) laser range scanners in the step 3;(b)
The angle of setting of airborne LiDAR system, which is smaller than under conditions of 0.5 °, then simplifies positioning equation, since angle of setting is given value, prolongs
Delay difference also as given value, then system, which is regarded as, contains only placement vector error, range error and angle error, then laser footpoint
Coordinate XBiWith true value XTBetween relationship become:
It is further made the difference by same place and establishes following error equation
Unknown calibration parameter is solved using the principle of least square
Three placement vector δ Δ X, δ Δ Y, δ Δ Z, range error δ Δ ρ and angle error δ Δ can be resolved by above formula
β。
The present invention disposes angle error by Models computed using land-based area calibration field, further passes through analysis sea area calibration field water
Literary environmental information establishes delay error model and resolves placement vector error, range error and scan angle mistake applied to sea area calibration field
Difference, and the calibration model for being suitable for the airborne LiDAR system point cloud of the dual-purpose double frequency in extra large land of land-based area and sea area is finally established, it fills up
The blank problem of the airborne LiDAR systematic error calibration model of sea area double frequency, has driven the processing capacity of related subsequent data to grind very much
Study carefully.
Detailed description of the invention
Fig. 1 is the flow chart that the present invention is implemented.
Specific embodiment
Below in conjunction with drawings and examples the present invention will be described in detail technical solution.
The dual-purpose airborne LiDAR systematic error calibration model modeling flow chart in sea land shown in Figure 1, below for embodiment
Each step in modeling procedure, is described in further detail the method for the present invention.
Step 1, geometry location model is three parameter model, error equation to airborne LiDAR over the ground under WGS-84 coordinate system
It is as follows:
In formula,
RH,P,RFor attitude angle spin matrix;For angle of setting spin matrix, as Boresight matrix;RβFor scanning
Angle spin matrix.x84,y84,z84For the control point coordinates that land-based area calibration field is laid, obtained by GPS, xGPS,yGPS,zGPSIt is surveyed by GPS
It takes, attitude angle H, P, R are provided by inertial navigation system (INS), dispose vector Δ X, Δ Y, Δ Z can be in platform calibrations by whole station
Instrument measures, and distance measurement value ρ and scan angle β are provided by laser range scanners, these are all observations;Only angle of settingIt is unknown-value, therefore, can be solved as system parameter.
If the coordinate by the WGS-84 at the control point obtained GPS is (xg,yg,zg)T, here it is considered that being true value.For letter
Change and calculate, the coordinate of laser footpoint will be calculated since laser scanning reference frame, then observation equation are as follows:
The value of other parameters is observation.Observation is moved on the right side of equal sign, (f is denoted asx,fy,fz)T, then
To (fx,fy,fz)TIt demands perfection after differential, error equation can be obtained by further arranging are as follows:
It is abbreviated asIn formula,
According to the principle of least square: VTV=min can form normal equation
Normal equation is solved, three placement angular dimensions can be obtained
Step 2, calibration field hydrological data in sea area chooses water temperature, the depth of water, salinity, water colour, transparency, these hydrology such as hydraulic pressure
Parameter and delay error construct laser waters propagation delay error model.It is introduced one by one using Gradual regression analysis model and examines the hydrology
Parameter conspicuousness rejects not significant parameter, selects " optimal " parameter, optimized parameter is exactly and the strongest ginseng of delay error correlation
Number, while the correlation intensity analysis between application grey systems GM (1, n) Lai Jinhang parameter.Finally by the set of weights of two kinds of models
It closes, establishes laser waters propagation delay error model;Gradual regression analysis model and grey systems GM (1, n) are not described herein, are added
Power combination establishment process model is as follows:
Equipped with m single function models, then there is built-up pattern: Yq=f (y1,y2,···,yk), k≤q, q are m
The number of combinations of model.If the weight vectors of function model in built-up pattern are as follows: P=[p1,p2,···,pk]。
The then form of built-up pattern are as follows: Yq=f (y1,y2,···,yn)=p1y1+p2y2+···+pkyk
The optimal weights vector solution of built-up pattern is to solve Mathematical Planning to error sum of squares according to the principle of least square.
Its objective function and constraint condition are as follows:Enable R=[1,1,1]T,
Then have:
Wherein v is single function model regression criterion, and V is the regression criterion matrix that each function is constituted.To the formula glug
Bright day multiplier solution can obtain optimal weights vector are as follows:
P=V-1R/RTV-1R
Above formula, which is substituted into built-up pattern, can obtain optimum weighted composition model, i.e. acquisition water route propagation delay error model.
Range error in the winged data of airborne laser LiDAR boat is mainly as caused by rangefinder error, Atmospheric Refraction Error, ground object target
Error and water route propagation delay error.Then range error model can be established are as follows:
Δ ρ=α+λ+γ+υ
In formula,
Δ ρ is range error;α is rangefinder error;λ is Atmospheric Refraction Error;γ is error caused by ground object target;υ
For water route propagation delay error.
It step 3, is linear scan in the scanning mode of satisfaction (a) laser range scanners;(b) airborne LiDAR system
Angle of setting be all under conditions of small angle (less than 0.5 °) then, positioning equation formula can be simplified as:
In formula,
X refers to abscissa of the laser footpoint in laser scanning reference frame, is equal to point cloud and throws to track line on ground
The lateral distance of shadow;
Z refers to ordinate of the laser footpoint in laser scanning reference frame, and size is equal to the elevation of t moment laser footpoint
ZtSubtract the elevation Z of the POS point of t moment interpolationot;The scale factor of S expression scanning mirror scanning angle.
Due to having resolved angle of setting in land-based area calibration field, as given value.Then can with five parameter calibration models come
Three winged placement vector δ Δ x of LiDAR boat airborne to sea areaA,δΔyA,δΔzA, range error δ Δ ρ and angle error δ Δ
β carries out calibration.The control point coordinates that wherein sea area calibration field is laid can be used as true value, obtain initial sit by multibeam sounding system
Then mark controls net with land-based area and carries out simultaneous adjustment acquisition high-precision coordinate value, and attitude angle H, P, R are provided by INS.
Placement vector error, range error and angle error are contained only in system, without under other error conditions.Then laser
Pin point coordinate XBiWith true value XTBetween relationship become:
After seeking local derviation to calibration parameter respectively, brings formula (1) into and arranges:
Have for the overlapping region points of common connection of adjacent (or vertical) air strips A and B:
Formula (2) can simplify are as follows:
Can then error equation be established:
Unknown calibration parameter is solved also with the principle of least square
Three placement vector δ Δ x can then be resolvedA,δΔyA,δΔzA, range error δ Δ ρ and angle error δ Δ β.
Step 4, in conjunction with three parameter model and five-parameter model, the airborne LiDAR system point cloud school of the extra large dual-purpose ranging in land is constructed
Positive model.
In formula, [X, Y, Z]T correctedFor the point coordinate after correction;[X,Y,Z]T biasedFor uncorrected coordinate;Yaw is
Course angle;X, y, z are laser footpoint coordinate;S is the scale factor for scanning scarnning mirror angle;β is instant scanning angle.
Specific example described herein only illustrates that spirit of the invention.The technical field of the invention
Technical staff various modifications or additions can be done to described specific example or be substituted in a similar manner, but
Without departing from the spirit of the invention or going beyond the scope defined by the appended claims.
Claims (4)
1. a kind of airborne LiDAR systematic error calibration model modelling approach of sea dual-purpose double frequency in land, it is characterised in that including following step
It is rapid:
Step 1, according to the control point data of acquisition laid in land-based area calibration field, the x measured by GPSGPS,yGPS,zGPS, posture
Angle H, P, R, placement vector Δ X, Δ Y, Δ Z, distance measurement value ρ and scan angle β, to airborne LiDAR geometry location model simplification over the ground
For land-based area three parameter model, it is used for inverse angle of setting, i.e., is navigated by the airborne LiDAR of double frequency in land-based area calibration field and flies data, in conjunction with
Ground metric data calculates angle of setting;
Step 2, the hydrological data of the sea area calibration field of acquisition is analyzed, flies number in conjunction with the airborne LiDAR boat of sea area calibration field
According to, based on successive Regression and grey systems GM (1, n) combination establish laser waters propagation delay error model, delay error is drawn
Enter the airborne LiDAR systematic error calibration model in sea area of next step;
Step 3, according to the parameter and model of step 1 and step 2 acquisition, to airborne LiDAR, the progress of geometry location model is excellent over the ground
Change, same place in data is flown by airborne LiDAR boat and makes the difference five parameter calibration models of building, the i.e. airborne LiDAR system of sea area double frequency
The calibration model for error of uniting resolves parameter;
Step 4, according to step 1, it is airborne finally to construct amphibious double frequency for the parameter and model obtained in step 2 and step 3
LiDAR point cloud calibration model.
2. modeling method according to claim 1, it is characterised in that: in the step 1, xGPS,yGPS,zGPSIt is surveyed by GPS
It takes, attitude angle H, P, R are provided by inertial navigation system, dispose vector Δ X, Δ Y, Δ Z can be surveyed in platform calibration by total station
, distance measurement value ρ and scan angle β are provided by laser range scanners, by unknown angle of setting Δ κ, Δ ω,Join as system
Number, by airborne LiDAR, geometry location model simplification is three parameter model over the ground, error equation is established, using least square solution
Angle of setting is calculated,
3. modeling method according to claim 1, it is characterised in that: in the step 2, the choosing of sea area calibration field hydrological data
Water intaking temperature, the depth of water, salinity, water colour, transparency, hydraulic parameters introduce using successive Regression and examine hydrologic parameter conspicuousness,
Selection and the strongest parameter of delay error correlation;Simultaneously using the correlation intensity between grey systems GM (1, n) Lai Jinhang variable
Analysis establishes the propagation of laser waters finally by the weighted array of Gradual regression analysis model and grey systems GM (1, n) two kinds of models
Then delay error model establishes range error model.
4. modeling method according to claim 1, it is characterised in that: in the step 3, swept in satisfaction (a) laser ranging
The scanning mode for retouching instrument is linear scan;(b) angle of setting of airborne LiDAR system is smaller than under conditions of 0.5 ° then to simplify and determine
Azimuth equation, since angle of setting is given value, delay error is also used as given value, then system regard as contain only placement vector error,
Range error and angle error, then laser footpoint coordinate XBiWith true value XTBetween relationship become:
It is further made the difference by same place and establishes following error equation
Unknown calibration parameter is solved using the principle of least square
Three placement vector δ Δ X, δ Δ Y, δ Δ Z, range error δ Δ ρ and angle error δ Δ β can be resolved by above formula.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811329065.5A CN109655811A (en) | 2018-11-09 | 2018-11-09 | The extra large airborne LiDAR systematic error calibration model modelling approach of the dual-purpose double frequency in land |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811329065.5A CN109655811A (en) | 2018-11-09 | 2018-11-09 | The extra large airborne LiDAR systematic error calibration model modelling approach of the dual-purpose double frequency in land |
Publications (1)
Publication Number | Publication Date |
---|---|
CN109655811A true CN109655811A (en) | 2019-04-19 |
Family
ID=66110756
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201811329065.5A Pending CN109655811A (en) | 2018-11-09 | 2018-11-09 | The extra large airborne LiDAR systematic error calibration model modelling approach of the dual-purpose double frequency in land |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109655811A (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110672031A (en) * | 2019-09-10 | 2020-01-10 | 中国科学院上海技术物理研究所 | Calibration method for three-dimensional laser scanning constrained by point and surface characteristics simultaneously |
CN112950702A (en) * | 2021-02-01 | 2021-06-11 | 华电淄博热电有限公司 | Coal pile volume calculation method based on three-dimensional point cloud |
CN116203547A (en) * | 2023-05-05 | 2023-06-02 | 山东科技大学 | Error correction method for laser scanning angle system |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104820217A (en) * | 2015-04-14 | 2015-08-05 | 同济大学 | Calibration method for multi-element linear array detection imaging laser radar with multiple normal planes |
KR101547940B1 (en) * | 2014-12-17 | 2015-08-28 | 가톨릭관동대학교산학협력단 | An error correction system for data of terrestrial LiDAR on the same plane and the method thereof |
CN105510901A (en) * | 2016-01-30 | 2016-04-20 | 武汉大学 | Optical satellite image time-varying error calibrating method and system based on multiple calibration fields |
CN106597417A (en) * | 2017-01-10 | 2017-04-26 | 北京航天计量测试技术研究所 | Remote scanning laser radar measurement error correction method |
CN107179533A (en) * | 2017-05-03 | 2017-09-19 | 长安大学 | A kind of airborne LiDAR systematic errors Self-checking method of multi-parameter |
CN108278968A (en) * | 2018-01-17 | 2018-07-13 | 北京建筑大学 | A kind of vehicle-mounted scanning system control point calibration method |
CN108572361A (en) * | 2018-04-03 | 2018-09-25 | 深圳飞马机器人科技有限公司 | Airborne laser radar system equipment integrates angle of setting calibration method and device |
-
2018
- 2018-11-09 CN CN201811329065.5A patent/CN109655811A/en active Pending
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR101547940B1 (en) * | 2014-12-17 | 2015-08-28 | 가톨릭관동대학교산학협력단 | An error correction system for data of terrestrial LiDAR on the same plane and the method thereof |
CN104820217A (en) * | 2015-04-14 | 2015-08-05 | 同济大学 | Calibration method for multi-element linear array detection imaging laser radar with multiple normal planes |
CN105510901A (en) * | 2016-01-30 | 2016-04-20 | 武汉大学 | Optical satellite image time-varying error calibrating method and system based on multiple calibration fields |
CN106597417A (en) * | 2017-01-10 | 2017-04-26 | 北京航天计量测试技术研究所 | Remote scanning laser radar measurement error correction method |
CN107179533A (en) * | 2017-05-03 | 2017-09-19 | 长安大学 | A kind of airborne LiDAR systematic errors Self-checking method of multi-parameter |
CN108278968A (en) * | 2018-01-17 | 2018-07-13 | 北京建筑大学 | A kind of vehicle-mounted scanning system control point calibration method |
CN108572361A (en) * | 2018-04-03 | 2018-09-25 | 深圳飞马机器人科技有限公司 | Airborne laser radar system equipment integrates angle of setting calibration method and device |
Non-Patent Citations (1)
Title |
---|
张靖等: "基于虚拟点模型的机载LiDAR***自动检校方法", 《测绘学报》 * |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110672031A (en) * | 2019-09-10 | 2020-01-10 | 中国科学院上海技术物理研究所 | Calibration method for three-dimensional laser scanning constrained by point and surface characteristics simultaneously |
CN112950702A (en) * | 2021-02-01 | 2021-06-11 | 华电淄博热电有限公司 | Coal pile volume calculation method based on three-dimensional point cloud |
CN116203547A (en) * | 2023-05-05 | 2023-06-02 | 山东科技大学 | Error correction method for laser scanning angle system |
CN116203547B (en) * | 2023-05-05 | 2023-07-11 | 山东科技大学 | Error correction method for laser scanning angle system |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN110779498B (en) | Shallow river water depth mapping method and system based on unmanned aerial vehicle multi-viewpoint photography | |
Kraus et al. | Advanced DTM generation from LIDAR data | |
Woodget et al. | Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry | |
Csanyi et al. | Improvement of lidar data accuracy using lidar-specific ground targets | |
CN102506824B (en) | Method for generating digital orthophoto map (DOM) by urban low altitude unmanned aerial vehicle | |
CN106199562B (en) | Sea error calibration method based on airborne laser radar measurement sea-floor relief | |
CN109655811A (en) | The extra large airborne LiDAR systematic error calibration model modelling approach of the dual-purpose double frequency in land | |
Tournadre et al. | UAV linear photogrammetry | |
CN106291512A (en) | A kind of method of array push-broom type laser radar range Nonuniformity Correction | |
CN108303044A (en) | A kind of leaf area index acquisition methods and system | |
CN105716581B (en) | Underwater object point coordinate determination method and device based on double medium camera works | |
CN107341778A (en) | SAR image ortho-rectification methods based on satellite control point storehouse and DEM | |
CN107219529A (en) | The acquisition methods and system of a kind of high-precision seafloor topography figure | |
CN108414998A (en) | A kind of laser satellite altitude meter echo waveform analog simulation method and equipment | |
CN109597040A (en) | A kind of field-free geometric calibration method of satellite-borne SAR image | |
CN106546262A (en) | Based on plane control and about binding close traverse measurement system external parameters calibration method | |
CN107015225A (en) | A kind of SAR platform elemental height error estimation based on self-focusing | |
CN108537770A (en) | It is a kind of without calibration satellite imagery infrared radiation characteristics inversion method and system | |
Thomas et al. | Unmanned aerial vehicles can accurately, reliably, and economically compete with terrestrial mapping methods | |
CN106875449B (en) | A kind of non-scalability camera calibration method of unmanned plane based on flying quality | |
KR20230040921A (en) | Atmospheric refraction positioning error correction method for optical remote sensing satellite image in qinghai-tibet plateau region | |
Seube et al. | Multibeam echo sounders-IMU automatic boresight calibration on natural surfaces | |
CN109613555B (en) | Method for arranging sea-land integrated calibration yard for verifying double-frequency LiDAR (light detection and ranging) detector | |
CN110030968A (en) | A kind of ground shelter measurement of elevation method based on spaceborne stereoptics image | |
CN117491978A (en) | Satellite-borne laser radar echo simulation method and device based on point cloud data |
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 | ||
WD01 | Invention patent application deemed withdrawn after publication | ||
WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20190419 |