CN106707352B - A kind of minimizing technology of the aeromagnetic interference based on ε-SVR algorithms - Google Patents
A kind of minimizing technology of the aeromagnetic interference based on ε-SVR algorithms Download PDFInfo
- Publication number
- CN106707352B CN106707352B CN201611071153.0A CN201611071153A CN106707352B CN 106707352 B CN106707352 B CN 106707352B CN 201611071153 A CN201611071153 A CN 201611071153A CN 106707352 B CN106707352 B CN 106707352B
- Authority
- CN
- China
- Prior art keywords
- cosz
- cosx
- cosy
- data
- compensation model
- 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.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
- G01V3/15—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation specially adapted for use during transport, e.g. by a person, vehicle or boat
- G01V3/16—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation specially adapted for use during transport, e.g. by a person, vehicle or boat specially adapted for use from aircraft
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
- G01V3/38—Processing data, e.g. for analysis, for interpretation, for correction
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Aviation & Aerospace Engineering (AREA)
- Geophysics And Detection Of Objects (AREA)
- Measuring Magnetic Variables (AREA)
Abstract
A kind of minimizing technology of the aeromagnetic interference based on ε SVR algorithms, including：The compensation model interfered for aircraft itself is obtained based on ε SVR algorithms；Obtain aircraft survey data；And survey data is compensated using the compensation model, to remove the influence that aircraft interferes magnetic field.
Description
Technical field
The present invention relates to geophysics aeromagnetic survey fields, navigate more particularly, to a kind of unmanned plane based on ε-SVR algorithms
Magnetic gradient interferes minimizing technology.
Background technology
Aeromagnetic survey is widely applied as a kind of important airborne geophysical prospecting means in geophysics field.Traditional
Aeromagnetic survey platform with have it is man-machine based on, last decade, with the development of unmanned air vehicle technique, unmanned plane is widely used aviation
Magnetic prospecting field, unmanned plane is man-machine compared to having, and has the remarkable advantages such as cheap, efficient, safety.But unmanned plane is due to aircraft
The reasons such as size is smaller, and baseline is shorter between probe, cause in aeromagnetic data, the interference magnetic field highly significant of aircraft, seriously
Affect the quality of data of aeromagnetic survey and finally at figure effect.Therefore, effectively the influence in removal aircraft interference magnetic field is being navigated
Have great importance in magnetic gradient measurements.
It is domestic at present that external magnetic compensation equipment is mainly used in aeromagnetic survey field, such as the AADC systems of RMS companies
Row magnetic compensation instrument, the boat magnetic compensation equipment of PICO companies.The backoff algorithm of above-mentioned compensation equipment is calculated based on traditional boat magnetic compensation
Method designs.Its feature of the algorithm is that optical pumped magnetometer and the collected data of flux-gate magnetometer are first passed through a low pass filtered
Wave device filters out part and the incoherent noise of aircraft magnetic disturbance, thereafter by least-squares algorithm, reaches removal aircraft interference magnetic
The purpose of field.
There are following several point defects in existing unmanned plane aeromagnetic survey compensation：
(1) currently, the boat magnetic compensation method of unmanned plane boat magnetic mainly continues with man-machine magnetic compensation method, but common nothing
Man-machine flying height is limited, cannot achieve soaring for 3000 meters of flying heights.
Common unmanned plane mobility after carrying certain load is poor simultaneously, cannot achieve the cross of standard calibration in-flight
The maneuvering flights such as rolling, pitching, yaw, therefore to there is the calibration of man-machine design flight that can not apply on common unmanned plane.
(2) there are problems that multi-collinearity, least-squares algorithm cannot be solved preferably in traditional boat magnetic compensation model
The problem.
Invention content
In view of existing scheme there are the problem of, in order to overcome the shortcomings of that above-mentioned prior art, the present invention propose one
Unmanned plane aeromagnetic of the kind based on ε-SVR algorithms interferes minimizing technology.
According to an aspect of the invention, there is provided a kind of minimizing technology of the aeromagnetic interference based on ε-SVR algorithms,
Including：The compensation model interfered for aircraft itself is obtained based on ε-SVR algorithms；Obtain aircraft survey data；And make
Survey data is compensated with the compensation model, to remove the influence that aircraft interferes magnetic field.
It can be seen from the above technical proposal that the invention has the advantages that：
(1) unmanned plane aeromagnetic interference minimizing technology effectively realizes unmanned plane using completely new based on ε-SVR algorithms
Low latitude calibration flight effectively avoids deterioration of the multi-collinearity in boat magnetic compensation model to compensation result.
(2) dyadic wavelet processing, removal and the incoherent interference of air maneuver are carried out to signal data, and signal phase is not
There are distortion.
Description of the drawings
Fig. 1 is the flow chart that unmanned plane aeromagnetic of the embodiment of the present invention based on ε-SVR algorithms interferes minimizing technology；
Fig. 2 is the flow chart that compensation model is obtained in Fig. 1；
Fig. 3 is the flow chart of ε-SVR algorithm concrete operations in Fig. 2；
Fig. 4 is that in-flight gradient data compensation is front and back at figure comparison diagram for exploration.
Specific implementation mode
Certain embodiments of the invention will be done with reference to appended attached drawing in rear and more comprehensively describe to property, some of but not complete
The embodiment in portion will be shown.In fact, various embodiments of the present invention can be realized in many different forms, and should not be construed
To be limited to this several illustrated embodiment；Relatively, these embodiments are provided so that the present invention meets applicable legal requirement.
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with specific embodiment, and reference
Attached drawing, the present invention is described in more detail.
In this field, calibration flight refers to that it is quasi- to carry out modeling to the interference magnetic field of aircraft before carrying out aeromagnetic survey flight
The process of conjunction.Flying platform is flown to certain altitude, the flight in four orthogonal courses is completed, using magnetic by concrete operations first
Backoff algorithm models the data in-flight obtained, to be fitted the interference magnetic field of aircraft.
An embodiment of the present invention provides a kind of, and the unmanned plane aeromagnetic based on ε-SVR algorithms interferes minimizing technology, base
The compensation model interfered for aircraft itself is in-flight obtained in calibration in ε-SVR algorithms, which is applied to exploration
Flight obtains aeromagnetic survey data, the aeromagnetic data after being compensated.
A kind of specific unmanned plane aeromagnetic interference minimizing technology based on ε-SVR algorithms provided in an embodiment of the present invention
Include the following steps, as shown in Figure 1：
S101 in-flight obtains the compensation model interfered for unmanned plane itself in unmanned plane calibration based on ε-SVR algorithms.
The characteristics of obtaining compensation model using this method is the method using machine learning, and calibration flight is considered as study
Process seeks regression hyperplane using ε-SVR algorithms, using ε-SVR algorithms be based on structural risk minimization the characteristics of, Ke Yiyou
Effect solve the problems, such as boat magnetic compensation model in multi-collinearity, the present invention in unmanned plane calibration flight can be low-latitude flying,
And without high maneuvers flare maneuvers such as unmanned aerial vehicle roll, pitching, yaws.
S102 in-flight obtains survey data in unmanned plane exploration；
The survey data includes：Aeromagnetic survey gradient data, unmanned plane itself interfere data and with air maneuver not phase
Dry interference data.
S103 carries out dyadic wavelet processing for the survey data of acquisition；
Carrying out dyadic wavelet processing to survey data can remove and the incoherent interference of UAV Maneuver, as high-frequency electrical is made an uproar
Sound etc.；And the distortion of data signal phase will not be brought.After dyadic wavelet is handled, survey data only includes aeromagnetic number
Data are interfered according to unmanned plane itself.
S104 compensates survey data using compensation model is obtained in S101.
The survey data handled through dyadic wavelet is compensated using compensation model, removal unmanned plane itself interferes number
According to obtaining accurate aeromagnetic data.
In the present embodiment, step S101 is specifically included, as shown in Figure 2：
S201：Nominal data is in-flight obtained in unmanned plane calibration；
The survey data includes that gradient data is explored in calibration, unmanned plane itself interferes data and irrelevant with air maneuver
Interference data.
S202：Dyadic wavelet processing is carried out for the nominal data of acquisition；
Carrying out dyadic wavelet processing to nominal data can remove and the incoherent interference of UAV Maneuver, as high-frequency electrical is made an uproar
Sound etc., and the distortion of data signal phase will not be brought.After dyadic wavelet is handled, survey data only includes aeromagnetic number
Data are interfered according to unmanned plane itself.
S203：Down-sampled processing is carried out to the nominal data by dyadic wavelet processing；
Due to ε-SVR algorithms to small-scale sample have well study generalization ability, to it is down-sampled treated calibration number
The treatment effeciency of algorithm can be dramatically speeded up according to ε-SVR algorithm process is carried out.
S204：ε-SVR algorithm process is carried out to down-sampled treated nominal data and obtains compensation model.
As shown in figure 3, the concrete operations of this step are as follows：
S301：Treated that nominal data is brought into original optimization problem by down-sampled；
Shown in the expression formula of original optimization problem such as formula (1).
Wherein w is the fitting coefficient of hyperplane, and C is punishment parameter, ξiWithFor relaxation parameter, b is the intercept of hyperplane,
ε is the data fluctuations range that hyperplane can be tolerated, GdiFor i-th of sample point aircraft interference magnetic field to the total field gradient data of magnetic
Influence numerical value, can be measured by optical pumped magnetometer, s.t. indicate constraints.
It is worth noting that, punishment parameter using aeromagnetic anomaly signal as abnormity point elimination other than regression problem, effectively
Solve the problems, such as that unmanned plane can not soar and complete large angle maneuver.
Enable Ai=(cosXi, cosYi, cosZi,HeicosXicosYi,Heicos2Yi,HeicosXicosZi,
HeicosYicosZi,Heicos2Zi,HeicosXi(cosXi)',HeicosXi(cosYi)',HeicosXi(cosZi)',HeicosYi
(cosXi)',HeicosYi(cosYi)',HeicosYi(cosZi)',HeicosZi(cosXi)',HeicosZi(cosYi)',
HeicosZi(cosZi) ') be i-th of sample point fluxgate the eigenmatrix that is formed of measured value, for i-th of sample point,
cosXi, cosYi, cosZiFor direction cosines, (cosXi) ', (cosYi) ', (cosZiDerivative of) ' the be direction cosines to the time,
In：
cosXi=Ti/Hei
cosYi=Li/Hei
cosZi=Vi/Hei
Ti、LiAnd ViFor the measured value of the fluxgate of i-th of sample point,
Inner product operation can be mapped to higher dimensional space by kernel function, and realize seeking for hyperplane in higher dimensional space,
In aeromagnetic compensation problem, kernel function can select exponential form, shown in mapping mode such as following formula (2).
Mapping mode Φ (the A of kernel function are reasonably selected in this implementationi), outstanding compensation effect can be obtained.One
Determine to compensate in degree in compensation model there may be high-order interference and the nonlinear problem in part.Eigenmatrix AiIt is non-linear
Mapping is as shown in formula (3).
S302：By original optimization problem, primal-dual optimization problem is converted to；
Original optimization problem can be write as shown in formula (4) using method of Lagrange multipliers.
By solve above formula partial derivative, and enable its be zero can as shown in formula (5).
WhereinFor intermediate variable, formula (5) is substituted into formula (4), the antithesis optimization that can obtain original optimization problem is asked
Topic is as shown in formula (6).
Wherein αiWithFor the to be solved of primal-dual optimization problem.
S303：Dual problem is solved, compensation model is obtained.
By solving dual problem, the regression hyperplane of original optimization problem is obtained, compensation model such as formula (7) institute is obtained
Show.
Wherein A is the eigenmatrix of sample point to be compensated, and f (A) is the interference magnetic field of fitting.
Fig. 4 is to explore in-flight, and gradient data compensation is front and back at figure comparing result, and Fig. 4 (a) and Fig. 4 (b) are existing vertical
The direct mapping of vertical ladder degree and horizontal gradient data, it is seen that there are apparent ripple and band, Fig. 4 (c) and Fig. 4 (d) in figure is
Using the method in present example, treated into figure as a result, visible ripple and band are removed, and aeromagnetic anomaly is high-visible.
Although the embodiment of the present invention has carried out dyadic wavelet processing and down-sampled processing to nominal data, survey data has carried out two into small
Wave processing, but those steps it is not necessary to, those skilled in the art can omit those steps according to particular condition.
It should be noted that the minimizing technology of the aeromagnetic interference based on ε-SVR algorithms in the present invention, is not only used
The situation of unmanned plane in embodiment can be also used for the situation that other aircraft are explored.
It should also be noted that, the demonstration of the parameter comprising particular value can be provided herein, but these parameters are without definite etc.
In corresponding value, but analog value can be similar in acceptable error margin or design constraint.
It should be noted that in attached drawing or specification text, the realization method for not being painted or describing is affiliated technology
Form known to a person of ordinary skill in the art, is not described in detail in field.In addition, the above-mentioned definition to each element and method is simultaneously
It is not limited only to various concrete structures, shape or the mode mentioned in embodiment, those of ordinary skill in the art can carry out letter to it
It singly changes or replaces, such as：
(1) unless specifically described or the step of must sequentially occur, there is no restriction in listed above for the sequence of above-mentioned steps,
And it can change or rearrange according to required design.
(2) ε-SVR algorithm process can use different types of kernel function, as linear kernel function is retouched herein to substitute
The kernel function stated.
(3) ε insensitive loss function and punishment parameter can carry out generation according to real data using different function and numerical value
It replaces.
Particular embodiments described above has carried out further in detail the purpose of the present invention, technical solution and advantageous effect
Describe in detail bright, it should be understood that the above is only a specific embodiment of the present invention, is not intended to restrict the invention, it is all
Within the spirit and principles in the present invention, any modification, equivalent substitution, improvement and etc. done should be included in the protection of the present invention
Within the scope of.
Claims (7)
1. a kind of minimizing technology of the aeromagnetic interference based on ε-SVR algorithms, which is characterized in that including：
The compensation model interfered for aircraft itself is obtained based on ε-SVR algorithms；
Obtain aircraft survey data；And
Survey data is compensated using the compensation model, to remove the influence that aircraft interferes magnetic field, in aircraft mark
It is fixed to include for the compensation model that aircraft itself interferes based on the acquisition of ε-SVR algorithms in-flight：
Nominal data is obtained, which in-flight obtains in calibration；
Down-sampled processing is carried out to the nominal data；And
ε-SVR algorithm process is carried out to down-sampled treated nominal data and obtains compensation model,
Further include between obtaining survey data and being compensated to survey data using the compensation model：For surveying for acquisition
It visits data and carries out dyadic wavelet processing；And
Further include in acquisition nominal data and between the down-sampled processing of nominal data progress：The nominal data of acquisition carries out
Dyadic wavelet processing.
2. minimizing technology according to claim 1, which is characterized in that carry out ε-to down-sampled treated nominal data
SVR algorithm process obtains compensation model：
Treated that nominal data is brought into original optimization problem by down-sampled；
Original optimization problem is converted into primal-dual optimization problem；And
Primal-dual optimization problem is solved, compensation model is obtained.
3. minimizing technology according to claim 2, which is characterized in that the expression formula of the original optimization problem is as follows：
Gdi-wTΦ(Ai)-b≤ε+ξi,
Wherein：W is the fitting coefficient of hyperplane, wTIt is the transposition of the fitting coefficient of hyperplane, C is punishment parameter, ξiWithTo relax
Henan parameter, b are the intercept of hyperplane, and ε is the data fluctuations range that hyperplane can be tolerated, GdiFor i-th sample point aircraft
It interferes magnetic field to the influence numerical value of the total field gradient data of magnetic, is measured by optical pumped magnetometer, s.t. indicates constraints；
Wherein：AiFor the eigenmatrix that the measured value of i-th of sample point fluxgate is formed, Φ (Ai) it is kernel function mapping mode, institute
State that down-sampled treated that nominal data includes AiAnd Gdi。
4. minimizing technology according to claim 3, which is characterized in that the kernel function mapping mode
5. minimizing technology according to claim 3, which is characterized in that i-th of sample point eigenmatrix Ai=
(cosXi, cosYi, cosZi,HeicosXicosYi,Heicos2Yi,HeicosXicosZi,HeicosYicosZi,
Heicos2Zi,HeicosXi(cosXi)',HeicosXi(cosYi)',HeicosXi(cosZi)',HeicosYi(cosXi)',
HeicosYi(cosYi)',HeicosYi(cosZi)',HeicosZi(cosXi)',HeicosZi(cosYi)',HeicosZi
(cosZi) ') wherein, cosXi, cosYi, cosZiFor direction cosines, (cosXi) ', (cosYi) ', (cosZi) ' it is direction cosines
To the derivative of time,
cosXi=Ti/Hei
cosYi=Li/Hei
cosZi=Vi/Hei
Ti、LiAnd ViFor the measured value of the fluxgate of i-th of sample point,
6. minimizing technology according to claim 3, which is characterized in that the primal-dual optimization problem is：
Wherein, αiWithFor the to be solved of primal-dual optimization problem.
7. minimizing technology according to claim 6, which is characterized in that the compensation model is
Wherein A is the eigenmatrix of sample point to be compensated.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611071153.0A CN106707352B (en) | 2016-11-28 | 2016-11-28 | A kind of minimizing technology of the aeromagnetic interference based on ε-SVR algorithms |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611071153.0A CN106707352B (en) | 2016-11-28 | 2016-11-28 | A kind of minimizing technology of the aeromagnetic interference based on ε-SVR algorithms |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106707352A CN106707352A (en) | 2017-05-24 |
| CN106707352B true CN106707352B (en) | 2018-10-12 |
Family
ID=58934175
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611071153.0A Active CN106707352B (en) | 2016-11-28 | 2016-11-28 | A kind of minimizing technology of the aeromagnetic interference based on ε-SVR algorithms |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106707352B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107356978B (en) * | 2017-07-11 | 2019-03-01 | 中国科学院电子学研究所 | Boat magnetic compensation method based on principal component analysis |
| US11506811B2 (en) | 2017-09-30 | 2022-11-22 | Aerospace Information Research Institute, Chinese Academy Of Sciences | Magnetic compensation method based on aeromagnetic compensation error model |
| CN108520112A (en) * | 2018-03-21 | 2018-09-11 | 北京理工大学 | A kind of aircraft interference field compensation method based on Tikhonov regularization |
| CN109814163B (en) * | 2019-02-28 | 2020-09-01 | 中国科学院遥感与数字地球研究所 | Method and system for suppressing noise of aeromagnetic tensor data based on extended compensation model |
| CN114609555B (en) * | 2020-12-08 | 2024-05-03 | 北京自动化控制设备研究所 | Cluster unmanned magnetic total field full-axis gradient detection method and detection system using same |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2003069373A1 (en) * | 2002-02-12 | 2003-08-21 | Bhp Billiton Innovation Pty Ltd | Airborne vector magnetic surveys |
| WO2009062236A1 (en) * | 2007-11-12 | 2009-05-22 | Commonwealth Scientific And Industrial Research Organisation | Method and apparatus for detecting marine deposits |
| CN103577607A (en) * | 2013-11-20 | 2014-02-12 | 哈尔滨工程大学 | Method for boundary compensation based on morphological characteristics of geomagnetic anomaly data |
| CN104122597A (en) * | 2013-08-22 | 2014-10-29 | 中国科学院遥感与数字地球研究所 | Unmanned aerial vehicle aeromagnetic detecting system and method |
| CN105222809A (en) * | 2015-11-05 | 2016-01-06 | 哈尔滨工业大学 | The method of the boat magnetic interference penalty coefficient estimation of a kind of ground magnetic gradient robust |
| CN105301666A (en) * | 2015-11-05 | 2016-02-03 | 哈尔滨工业大学 | Self-adaptive adjustment method of aeromagnetic interference compensation coefficient |
| CN105425304A (en) * | 2015-11-03 | 2016-03-23 | 哈尔滨工业大学 | Compensation method for airplane aeromagnetic interference |
-
2016
- 2016-11-28 CN CN201611071153.0A patent/CN106707352B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2003069373A1 (en) * | 2002-02-12 | 2003-08-21 | Bhp Billiton Innovation Pty Ltd | Airborne vector magnetic surveys |
| WO2009062236A1 (en) * | 2007-11-12 | 2009-05-22 | Commonwealth Scientific And Industrial Research Organisation | Method and apparatus for detecting marine deposits |
| CN104122597A (en) * | 2013-08-22 | 2014-10-29 | 中国科学院遥感与数字地球研究所 | Unmanned aerial vehicle aeromagnetic detecting system and method |
| CN103577607A (en) * | 2013-11-20 | 2014-02-12 | 哈尔滨工程大学 | Method for boundary compensation based on morphological characteristics of geomagnetic anomaly data |
| CN105425304A (en) * | 2015-11-03 | 2016-03-23 | 哈尔滨工业大学 | Compensation method for airplane aeromagnetic interference |
| CN105222809A (en) * | 2015-11-05 | 2016-01-06 | 哈尔滨工业大学 | The method of the boat magnetic interference penalty coefficient estimation of a kind of ground magnetic gradient robust |
| CN105301666A (en) * | 2015-11-05 | 2016-02-03 | 哈尔滨工业大学 | Self-adaptive adjustment method of aeromagnetic interference compensation coefficient |
Non-Patent Citations (1)
| Title |
|---|
| 运五飞机上航磁梯度测量系统的安装与补偿;李晓禄 等;《物探与化探》;20060630;第30卷(第3期);第224-228、232页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106707352A (en) | 2017-05-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106707352B (en) | A kind of minimizing technology of the aeromagnetic interference based on ε-SVR algorithms | |
| CN106353824B (en) | System compensation and magnetic disturbance the compensation fusion method of airborne flux-gate magnetic gradient tensor instrument | |
| CN111433634B (en) | Magnetic compensation method based on aeromagnetic compensation error model | |
| CN106842344B (en) | The method of unmanned plane boat magnetic holoaxial gradient magnetic disturbance compensation based on feedforward network | |
| Thébault et al. | Revised spherical cap harmonic analysis (R‐SCHA): Validation and properties | |
| CN105509737B (en) | A kind of airborne mobile platform magnetic disturbance compensation method not influenceed by GEOMAGNETIC CHANGE | |
| Miyoshi et al. | A multi-scale localization approach to an ensemble Kalman filter | |
| CN105301666B (en) | A kind of self-adapting regulation method for the magnetic disturbance penalty coefficient that navigates | |
| CN109856689B (en) | Noise suppression processing method and system for superconducting aeromagnetic gradient tensor data | |
| CN109814163B (en) | Method and system for suppressing noise of aeromagnetic tensor data based on extended compensation model | |
| CN110018429B (en) | Method and system for eliminating magnetic field interference caused by vibration of magnetic detection platform | |
| Ahlefeldt | Microphone array measurement in european transonic wind tunnel at flight Reynolds numbers | |
| Tauscher et al. | Global 21 cm Signal Extraction from Foreground and Instrumental Effects. IV. Accounting for Realistic Instrument Uncertainties and Their Overlap with Foreground and Signal Models | |
| GB2481643A (en) | Gravity survey data processing | |
| Wang et al. | Design, experiments and simulation of voltage transformers on the basis of a differential input D-dot sensor | |
| CN108520112A (en) | A kind of aircraft interference field compensation method based on Tikhonov regularization | |
| Qiu et al. | Combining CHAMP and Swarm satellite data to invert the lithospheric magnetic field in the Tibetan Plateau | |
| Zhang et al. | Observation satellite attitude estimation using sensor measurement and image registration fusion | |
| CN112213678A (en) | Three-axis data correction and compensation method for vector magnetic detector | |
| Matsubara | The correlation function in redshift space: General formula with wide-angle effects and cosmological distortions | |
| Matzka et al. | A new aeromagnetic survey of the North Pole and the Arctic Ocean north of Greenland and Ellesmere Island | |
| CN108508479B (en) | Method for inverting three-dimensional gravity-magnetic data of open-ground well in cooperation with target position | |
| Li et al. | A magnetic interference compensation method for airborne electronic equipment without current sensors | |
| CN114325848A (en) | Aviation magnetic interference compensation method and device for adaptive correction of compensation coefficient | |
| Ma et al. | Outlier correction method of telemetry data based on wavelet transformation and Wright criterion |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |