CN110907967B - High-precision integrity convection layer pipe abnormity monitoring method and device - Google Patents
High-precision integrity convection layer pipe abnormity monitoring method and device Download PDFInfo
- Publication number
- CN110907967B CN110907967B CN201811085076.3A CN201811085076A CN110907967B CN 110907967 B CN110907967 B CN 110907967B CN 201811085076 A CN201811085076 A CN 201811085076A CN 110907967 B CN110907967 B CN 110907967B
- Authority
- CN
- China
- Prior art keywords
- abnormal
- standard deviation
- pipe
- troposphere
- convection layer
- 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
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
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/40—Correcting position, velocity or attitude
-
- 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
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
Abstract
The invention provides a method and a device for monitoring the abnormality of a convective stratum pipe with high precision and integrity, wherein the method comprises the following steps: determining an abnormal parameter model of the convection layer pipe by counting the meteorological data of the convection layer monitored by different monitoring stations; calculating the abnormal error of the convection layer pipe according to the abnormal parameter model of the convection layer pipe; enveloping the abnormal error of the convection layer pipe, and calculating the standard deviation of the abnormal error of the convection layer pipe; and calculating an expanded troposphere error standard deviation according to the troposphere pipe abnormal error standard deviation and the troposphere error standard deviation under the condition that the troposphere is not abnormal, calculating an expanded pseudo-range domain error standard deviation based on the expanded troposphere error standard deviation, and carrying out integrity monitoring based on the expanded pseudo-range domain error standard deviation. The method can reduce unknown positioning errors of the system, effectively count abnormal error characteristics of the tube, and improve error envelope precision.
Description
Technical Field
The invention relates to the technical field of anomaly monitoring of a convection layer pipe, in particular to a high-precision integrity anomaly monitoring method and device for the convection layer pipe.
Background
As the navigation signal passes through the troposphere, the propagation path may be curved due to the effects of troposphere refraction, thus introducing troposphere delays. In the existing integrity monitoring method, only the condition that the troposphere is abnormal is considered, and the existing troposphere model can relatively accurately calculate the troposphere delay without abnormality, but with the wide application of high-precision navigation, the abnormal troposphere can introduce larger unknown integrity risk and error, which seriously affects the integrity of the high-precision navigation and reduces the positioning precision. Therefore, as the high-precision navigation gradually enters the life safety field, and meanwhile, the dual-frequency differential technology is developed in a mature way, the error and integrity risk caused by abnormal troposphere errors are more negligible.
Tropospheric anomalies can be divided into horizontal non-nominal tropospheric anomalies caused by horizontally oriented meteorological parameter anomalies (e.g., weather front alternately generated by hot and cold air) and vertical tropospheric tube anomalies caused by vertically oriented anomalous meteorology (e.g., stratosphere) and the like, manifested as increasing meteorological temperature with increasing altitude or decreasing water vapor pressure with increasing altitude, resulting in anomalies in the rate of change of tropospheric refractive index with altitude.
Patent CN201610176414.9 discloses a troposphere delay integrity monitoring method and device. The method comprises the steps of receiving data information of a plurality of satellites, obtaining maximum pseudo-range errors in pseudo-range errors of all the satellites according to the data information of the plurality of satellites, determining a horizontal standard deviation of a troposphere of each visible satellite according to the maximum pseudo-range errors, calculating the horizontal error of the troposphere of each visible satellite according to the horizontal standard deviation of the troposphere of each visible satellite, and obtaining the troposphere error of each visible satellite according to the horizontal error of the troposphere of each visible satellite and the vertical error of the troposphere of each visible satellite. However, patent CN201610176414.9 has the following problems:
1. the convection layer pipe abnormity cannot be monitored and the pipe abnormity error can be calculated;
2. the standard deviation of the abnormal error of the convection layer pipe cannot be calculated;
3. the error envelope has low precision and can introduce large envelope redundant errors (redundancy between errors after the envelope and real errors).
Disclosure of Invention
In order to solve the defects of the prior art, the invention aims to provide a high-precision integrity anomaly monitoring method for a convective stratum pipe.
The technical scheme adopted by the invention is as follows:
a method for high accuracy integrity convective zone pipe anomaly monitoring, the method comprising the steps of:
determining an abnormal parameter model of the convection layer pipe by counting the meteorological data of the convection layer monitored by different monitoring stations;
calculating the abnormal error of the convection layer pipe according to the abnormal parameter model of the convection layer pipe;
enveloping the abnormal error of the convection layer pipe, and calculating the standard deviation of the abnormal error of the convection layer pipe;
and calculating an expanded troposphere error standard deviation according to the troposphere pipe abnormal error standard deviation and the troposphere error standard deviation under the condition that the troposphere is not abnormal, calculating an expanded pseudo-range domain error standard deviation based on the expanded troposphere error standard deviation, and carrying out integrity monitoring based on the expanded pseudo-range domain error standard deviation.
Furthermore, the convection layer tube abnormity parameter model comprises the height, the thickness and the gradient of the convection layer tube abnormity, wherein the gradient is the refractive index of the convection layer calculated according to the measured meteorological data of the convection layer.
Further, the determining the convection layer pipe abnormal parameter model specifically comprises the following steps:
acquiring troposphere meteorological data of different height layers monitored by different monitoring stations;
calculating the actually measured tropospheric refractive indexes of different monitoring stations according to the actually measured tropospheric meteorological data, namely the abnormal gradient of the tropospheric pipes;
according to troposphere meteorological data measured by different monitoring stations, the height and the continuous thickness of the troposphere pipe during the abnormal occurrence are counted, and the maximum value of the height and the maximum value of the thickness are taken;
and obtaining an abnormal parameter model of the convection layer pipe.
Further, the calculating of the anomaly error of the convection layer pipe specifically comprises the following steps:
calculating the change rate of the refractive index of the troposphere along with the height according to the meteorological data change when the troposphere is not abnormal;
according to troposphere meteorological data measured by different monitoring stations, counting the height and the continuous thickness of the troposphere pipe when the troposphere pipe is abnormal, and taking the maximum value of the height and the maximum value of the thickness to construct a troposphere pipe abnormal parameter model;
and calculating the abnormal error of the convection layer tube according to the difference value of the abnormal gradient of the convection layer tube and the refractive index of the convection layer after the height integration.
Further, enveloping the anomaly error of the flow layer pipe specifically comprises the following steps:
calculating abnormal errors of convection layer pipes of different monitoring stations;
counting the probability distribution of the abnormal errors of the convection layer pipe;
enveloping the probability distribution of the abnormal errors of the convection layer pipe by an expansion Gaussian function;
and the standard deviation of the expanded Gaussian function is the standard deviation of the abnormal error of the convection layer pipe.
And further, calculating the expanded troposphere error standard deviation by taking the root mean square according to the troposphere pipe abnormal error standard deviation and the troposphere error standard deviation under the condition that the troposphere is not abnormal.
In order to implement the method, the invention also provides a terminal which is applied to the method for monitoring the anomaly of the flow layer pipe, and the terminal carries out integrity monitoring based on the expanded pseudo-range domain error standard deviation.
In order to implement the method, the invention also provides a high-precision integrity convective stratum pipe abnormity monitoring device, which comprises:
the system platform is used for counting tropospheric meteorological data monitored by different monitoring stations, determining a tropospheric pipe abnormal parameter model, calculating tropospheric pipe abnormal errors, enveloping the tropospheric pipe abnormal errors, calculating tropospheric pipe abnormal error standard deviations and broadcasting the standard deviations to the terminal;
and the terminal is used for calculating the expanded troposphere error standard deviation according to the troposphere pipe abnormal error standard deviation and the troposphere error standard deviation under the condition that the troposphere is not abnormal, calculating the expanded pseudo-range domain error standard deviation based on the expanded troposphere error standard deviation and carrying out integrity monitoring based on the expanded pseudo-range domain error standard deviation.
Furthermore, the convection layer pipe abnormity parameter model comprises height, thickness and gradient of the convection layer pipe abnormity, wherein the gradient is the refractive index of the convection layer calculated according to the measured meteorological data of the convection layer.
The invention also provides a memory, the computer program executing the steps of:
determining an abnormal parameter model of the convection layer pipe by counting the meteorological data of the convection layer monitored by different monitoring stations;
calculating the abnormal error of the convection layer pipe according to the abnormal parameter model of the convection layer pipe;
enveloping the abnormal error of the convection layer pipe, and calculating the standard deviation of the abnormal error of the convection layer pipe;
and calculating an expanded troposphere error standard deviation according to the troposphere pipe abnormal error standard deviation and the troposphere error standard deviation under the condition that the troposphere is not abnormal, calculating an expanded pseudo-range domain error standard deviation based on the expanded troposphere error standard deviation, and carrying out integrity monitoring based on the expanded pseudo-range domain error standard deviation.
The invention solves the following technical problems:
1. calculating the abnormal error of the convection layer pipe, and improving the positioning precision of high-precision navigation;
2. calculating the standard deviation of the abnormal errors of the convection layer pipe, improving the error enveloping precision and reducing the integrity risk introduced by an enveloping method;
3. the risk of unknown integrity caused by the abnormal introduction of the convection layer pipe is eliminated, and the integrity of the system is improved;
4. the robustness of the high-precision navigation system under the abnormal troposphere is improved, and the integrity monitoring capability of the system is improved.
The invention has the following beneficial effects:
1) by the technology, the convection layer pipe abnormity model can be effectively obtained, and the convection layer pipe abnormity error is calculated.
2) By the method, the abnormal error characteristics of the pipe can be effectively counted, and the standard deviation of the abnormal error of the convection layer pipe can be calculated.
3) According to the method, the abnormal errors of the flow layer pipe are enveloped from an error source, the enveloping precision is improved, the unknown integrity risk of the system and the extra integrity risk introduced by the enveloping method are reduced, and the monitoring capability of the high-precision integrity is improved.
Drawings
FIG. 1 is a schematic view of an anomaly model for a convective zone pipe according to the present invention;
FIG. 2 is a diagram of an abnormal parameter model of a convection layer pipe according to the present invention;
FIG. 3 is a flow chart of the present invention for calculating anomaly errors of a convection layer pipe;
FIG. 4 is an envelope flow chart of the anomaly errors of the tropospheric pipe according to the present invention;
FIG. 5 is a flow chart of the method for monitoring the integrity of a convection layer pipe under an anomaly.
Detailed Description
On the basis of analyzing the convection layer pipe abnormity model, the invention provides a high-precision integrity convection layer pipe abnormity monitoring method, which calculates pipe abnormity error and error standard deviation, eliminates integrity risk caused by convection layer pipe abnormity, improves enveloping precision and reduces enveloping redundancy error. The invention is further illustrated below with reference to the figures and examples.
The first embodiment is as follows:
the invention provides a high-precision integrity anomaly monitoring method for a convection layer pipe, wherein the anomaly of the convection layer pipe is an abnormal convection layer phenomenon in the vertical direction, which is mainly caused by an inverse temperature layer and is represented as the meteorological temperature increasing along with the height increasing or the water vapor pressure decreasing along with the height increasing, and a schematic diagram of an anomaly model of the convection layer pipe is shown in figure 1 and comprises the following steps:
step 1, determining parameters of an abnormal model of a convection layer pipe:
by counting the troposphere meteorological data monitored by different monitoring stations, the height, thickness and gradient of the troposphere pipe abnormity can be counted, wherein the pipe abnormity gradient is the troposphere refractive index calculated according to the actually measured meteorological data. The specific implementation steps are as follows:
step 1.1, acquiring troposphere meteorological data (temperature, pressure and relative humidity) of different height layers monitored by N (N is at least 1) monitoring stations;
step 1.2, calculating the actually measured troposphere refractive indexes of N monitoring stations according to the actually measured troposphere meteorological data, namely the abnormal gradient of the troposphere pipe;
step 1.3, counting the height Hi and the continuous thickness di when the convection layer pipe is abnormal according to the measured meteorological data of the convection layer of the N monitoring stations, and taking the maximum values H and d;
finally, the obtained convection layer pipe abnormal parameter model is shown in fig. 2.
Step 2, calculating the abnormal error of the convection layer pipe:
the tropospheric delay is the integral value of the tropospheric refractive index dependence on the propagation path, so the tropospheric anomaly error in the zenith direction is the difference between the tropospheric anomaly gradient and the model tropospheric refractive index after integrating with respect to height, as shown by the hatched area in fig. 2. The specific implementation flow is shown in fig. 3, and the specific implementation steps are as follows:
step 2.1, calculating the change rate of the refractive index of the model troposphere along with the height according to the meteorological parameter change when the troposphere is abnormal;
2.2, constructing an abnormal parameter model of the convection layer pipe according to the three parameters of the abnormal height, the abnormal thickness and the abnormal gradient of the convection layer pipe obtained in the step 1.2 and the step 1.3;
and 2.3, the convection layer pipe abnormal error is the difference value of the convection layer pipe abnormal gradient and the model convection layer refractive index after height integration.
Step 3, enveloping the abnormal error of the convection layer pipe:
in order to improve the integrity of the system under the condition of the anomaly of the convection layer pipe and eliminate the integrity risk caused by the anomaly of the convection layer pipe, the anomaly error of the convection layer pipe needs to be enveloped. The specific implementation flow is shown in fig. 4, and the specific implementation steps are as follows:
step 3.1, calculating abnormal errors of convection layer pipes of the N monitoring stations according to the step 2.3;
step 3.2, counting the probability distribution of the abnormal errors of the convection layer pipe;
step 3.3, enveloping the error probability distribution in the step 3.2 by an expansion Gaussian function;
step 3.4, the standard deviation of the expanded Gaussian function is the standard deviation of the abnormal error of the convection layer pipe;
and 3.5, broadcasting the abnormal error standard deviation of the convection layer pipe to a terminal (receiver) by the system platform.
Step 4, monitoring the integrity of the convection layer pipe under the abnormality:
according to the calculated standard deviation of the convection layer pipe abnormal error, the standard deviation of the pseudo range domain error of the convection layer pipe abnormal expansion can be calculated by taking the root mean square method and expanding the convection layer pipe abnormal error standard deviation without the abnormal convection layer error standard deviation, the integrity risk caused by the convection layer pipe abnormal expansion is eliminated, and meanwhile, the error envelope precision is improved. The specific implementation flow is shown in fig. 5, and the specific implementation steps are as follows:
step 4.1: according to the convection layer pipe abnormal error standard deviation obtained in the step 3.4, expanding the troposphere error standard deviation without abnormality of the troposphere by taking the root mean square method;
step 4.2: calculating a pseudorange domain error standard deviation after expansion based on the troposphere error standard deviation after expansion;
step 4.3: and 4, based on the expanded pseudo range domain error standard deviation obtained in the step 4.2, carrying out integrity monitoring.
Example two:
the invention provides a terminal (receiver), which calculates an expanded troposphere error standard deviation by taking a root mean square method according to a received troposphere pipe abnormal error standard deviation and a troposphere error standard deviation under the condition that a troposphere is not abnormal, which is calculated according to a message. A pseudorange domain error standard deviation after dilation is computed based on tropospheric error standard deviation after dilation. Finally, the terminal (receiver) bases on the dilated pseudorange domain error standard deviation and performs integrity monitoring.
The invention also provides a high-precision integrity anomaly monitoring device for the convective stratum pipe, which comprises:
the system platform is used for counting tropospheric meteorological data monitored by different monitoring stations, determining a tropospheric pipe abnormal parameter model, calculating tropospheric pipe abnormal errors, enveloping the tropospheric pipe abnormal errors, calculating tropospheric pipe abnormal error standard deviations and broadcasting the standard deviations to the terminal;
and the terminal is used for calculating the expanded troposphere error standard deviation according to the troposphere pipe abnormal error standard deviation and the troposphere error standard deviation under the condition that the troposphere is not abnormal, calculating the expanded pseudo-range domain error standard deviation based on the expanded troposphere error standard deviation and carrying out integrity monitoring based on the expanded pseudo-range domain error standard deviation.
Preferably, the tropospheric pipe anomaly parameter model includes a height, a thickness and a gradient of occurrence of a tropospheric pipe anomaly, the gradient being a tropospheric refractive index calculated from measured tropospheric meteorological data.
Example three:
the invention also provides a memory storing a computer program executed by a processor to perform the steps of:
determining an abnormal parameter model of the convection layer pipe by counting the meteorological data of the convection layer monitored by different monitoring stations;
calculating the abnormal error of the convection layer pipe according to the abnormal parameter model of the convection layer pipe;
enveloping the abnormal error of the convection layer pipe, and calculating the standard deviation of the abnormal error of the convection layer pipe;
and calculating an expanded troposphere error standard deviation according to the troposphere pipe abnormal error standard deviation and the troposphere error standard deviation under the condition that the troposphere is not abnormal, calculating an expanded pseudo-range domain error standard deviation based on the expanded troposphere error standard deviation, and carrying out integrity monitoring based on the expanded pseudo-range domain error standard deviation.
Although the present invention has been described with reference to the preferred embodiments, it is not intended to limit the present invention, and those skilled in the art can make variations and modifications of the present invention without departing from the spirit and scope of the present invention by using the methods and technical contents disclosed above.
Claims (8)
1. A method for monitoring the abnormality of a convective stratum pipe with high-precision integrity is characterized by comprising the following steps:
determining an abnormal parameter model of the convection layer pipe by counting the meteorological data of the convection layer monitored by different monitoring stations, wherein the abnormal parameter model of the convection layer pipe comprises the height, the thickness and the gradient of the abnormal convection layer pipe, and the gradient is the refractive index of the convection layer calculated according to the measured meteorological data of the convection layer;
calculating the abnormal error of the convection layer pipe according to the abnormal parameter model of the convection layer pipe;
enveloping the abnormal error of the convection layer pipe, and calculating the standard deviation of the abnormal error of the convection layer pipe;
and calculating an expanded troposphere error standard deviation according to the troposphere pipe abnormal error standard deviation and the troposphere error standard deviation under the condition that the troposphere is not abnormal, calculating an expanded pseudo-range domain error standard deviation based on the expanded troposphere error standard deviation, and carrying out integrity monitoring based on the expanded pseudo-range domain error standard deviation.
2. The method for monitoring the anomaly of the tropospheric pipe with high accuracy and integrity as claimed in claim 1, wherein said determining the anomaly parametric model of the tropospheric pipe comprises the following steps:
acquiring troposphere meteorological data of different height layers monitored by different monitoring stations;
calculating the actually measured tropospheric refractive indexes of different monitoring stations according to the actually measured tropospheric meteorological data, namely the abnormal gradient of the tropospheric pipes;
according to troposphere meteorological data measured by different monitoring stations, the height and the continuous thickness of the troposphere pipe during the abnormal occurrence are counted, and the maximum value of the height and the maximum value of the thickness are taken;
and obtaining an abnormal parameter model of the convection layer pipe.
3. The method for monitoring the anomaly of the tropospheric pipe with high accuracy and integrity as claimed in claim 1, wherein said calculating the anomaly error of the tropospheric pipe comprises the following steps:
calculating the change rate of the refractive index of the troposphere along with the height according to the meteorological data change when the troposphere is not abnormal;
according to troposphere meteorological data measured by different monitoring stations, counting the height and the continuous thickness of the troposphere pipe when the troposphere pipe is abnormal, and taking the maximum value of the height and the maximum value of the thickness to construct a troposphere pipe abnormal parameter model;
and calculating the abnormal error of the convection layer tube according to the difference value of the abnormal gradient of the convection layer tube and the refractive index of the convection layer after the height integration.
4. The method for monitoring the anomaly of the tropospheric pipe with high accuracy and integrity as claimed in claim 3, wherein said enveloping the anomaly errors of the tropospheric pipe comprises the following steps:
calculating abnormal errors of convection layer pipes of different monitoring stations;
counting the probability distribution of the abnormal errors of the convection layer pipe;
enveloping the probability distribution of the abnormal errors of the convection layer pipe by an expansion Gaussian function;
and the standard deviation of the expanded Gaussian function is the standard deviation of the abnormal error of the convection layer pipe.
5. The method of claim 1, wherein the expanded tropospheric error standard deviation is calculated by taking the root mean square (rms) based on the tropospheric anomaly error standard deviation and the tropospheric error standard deviation without tropospheric anomaly.
6. A terminal, for use in the method of claim 1, wherein the terminal performs integrity monitoring based on an expanded pseudorange domain error standard deviation.
7. A high accuracy integrity convective laminar tube anomaly monitoring apparatus, comprising:
the system platform is used for counting tropospheric meteorological data monitored by different monitoring stations, determining a tropospheric pipe abnormal parameter model, calculating a tropospheric pipe abnormal error, enveloping the tropospheric pipe abnormal error, calculating a tropospheric pipe abnormal error standard deviation and broadcasting the tropospheric pipe abnormal error standard deviation to the terminal, wherein the tropospheric pipe abnormal parameter model comprises height, thickness and gradient of occurrence of tropospheric pipe abnormality, and the gradient is a tropospheric refractive index calculated according to actually measured tropospheric meteorological data;
and the terminal is used for calculating the expanded troposphere error standard deviation according to the troposphere pipe abnormal error standard deviation and the troposphere error standard deviation under the condition that the troposphere is not abnormal, calculating the expanded pseudo-range domain error standard deviation based on the expanded troposphere error standard deviation and carrying out integrity monitoring based on the expanded pseudo-range domain error standard deviation.
8. A memory storing a computer program, the computer program performing the steps of:
determining an abnormal parameter model of the convection layer pipe by counting the meteorological data of the convection layer monitored by different monitoring stations, wherein the abnormal parameter model of the convection layer pipe comprises the height, the thickness and the gradient of the abnormal convection layer pipe, and the gradient is the refractive index of the convection layer calculated according to the measured meteorological data of the convection layer;
calculating the abnormal error of the convection layer pipe according to the abnormal parameter model of the convection layer pipe;
enveloping the abnormal error of the convection layer pipe, and calculating the standard deviation of the abnormal error of the convection layer pipe;
and calculating an expanded troposphere error standard deviation according to the troposphere pipe abnormal error standard deviation and the troposphere error standard deviation under the condition that the troposphere is not abnormal, calculating an expanded pseudo-range domain error standard deviation based on the expanded troposphere error standard deviation, and carrying out integrity monitoring based on the expanded pseudo-range domain error standard deviation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811085076.3A CN110907967B (en) | 2018-09-17 | 2018-09-17 | High-precision integrity convection layer pipe abnormity monitoring method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811085076.3A CN110907967B (en) | 2018-09-17 | 2018-09-17 | High-precision integrity convection layer pipe abnormity monitoring method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110907967A CN110907967A (en) | 2020-03-24 |
| CN110907967B true CN110907967B (en) | 2022-02-08 |
Family
ID=69812647
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811085076.3A Active CN110907967B (en) | 2018-09-17 | 2018-09-17 | High-precision integrity convection layer pipe abnormity monitoring method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110907967B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115184968B (en) * | 2022-06-22 | 2023-06-02 | 同济大学 | Troposphere delay limit residual error estimation method based on two-step Gaussian envelope method |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20090059323A (en) * | 2007-12-06 | 2009-06-11 | 부산대학교 산학협력단 | Method for verifying of indirect methods which evaluating total amounts of tropospheric ozone from total ozone measured by satellite |
| CN106134460B (en) * | 2011-12-22 | 2014-04-09 | 北京遥测技术研究所 | A kind of pseudo satellite, pseudolite tropospheric delay correcting method |
| CN105785407A (en) * | 2016-02-23 | 2016-07-20 | 东南大学 | Meteorological-parameter-free troposphere delay correction method suitable for China |
| CN105866802A (en) * | 2016-03-24 | 2016-08-17 | 北京航空航天大学 | Method and device for monitoring delay integrity of troposphere |
| CN106324622A (en) * | 2016-08-05 | 2017-01-11 | 西安希德电子信息技术股份有限公司 | Local enhanced system integrity monitoring and real-time location enhancing method |
| CN107064961A (en) * | 2017-03-24 | 2017-08-18 | 北京航空航天大学 | The method and device tested satellite navigation system integrity monitoring performance |
| CN108508461A (en) * | 2018-03-27 | 2018-09-07 | 千寻位置网络（浙江）有限公司 | Based on GNSS carrier phase high accuracy positioning completeness monitoring methods |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8718673B2 (en) * | 2010-05-21 | 2014-05-06 | Maple Acquisition Llc | System and method for location assurance of a mobile device |
-
2018
- 2018-09-17 CN CN201811085076.3A patent/CN110907967B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20090059323A (en) * | 2007-12-06 | 2009-06-11 | 부산대학교 산학협력단 | Method for verifying of indirect methods which evaluating total amounts of tropospheric ozone from total ozone measured by satellite |
| CN106134460B (en) * | 2011-12-22 | 2014-04-09 | 北京遥测技术研究所 | A kind of pseudo satellite, pseudolite tropospheric delay correcting method |
| CN105785407A (en) * | 2016-02-23 | 2016-07-20 | 东南大学 | Meteorological-parameter-free troposphere delay correction method suitable for China |
| CN105866802A (en) * | 2016-03-24 | 2016-08-17 | 北京航空航天大学 | Method and device for monitoring delay integrity of troposphere |
| CN106324622A (en) * | 2016-08-05 | 2017-01-11 | 西安希德电子信息技术股份有限公司 | Local enhanced system integrity monitoring and real-time location enhancing method |
| CN107064961A (en) * | 2017-03-24 | 2017-08-18 | 北京航空航天大学 | The method and device tested satellite navigation system integrity monitoring performance |
| CN108508461A (en) * | 2018-03-27 | 2018-09-07 | 千寻位置网络（浙江）有限公司 | Based on GNSS carrier phase high accuracy positioning completeness monitoring methods |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110907967A (en) | 2020-03-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103323888B (en) | Method for eliminating delay errors of troposphere of GNSS atmospheric probing data | |
| CN107064961B (en) | The method and device tested satellite navigation system integrity monitoring performance | |
| CN104965207B (en) | A kind of acquisition methods of zone convection layer zenith delay | |
| CN110031877B (en) | GRNN model-based regional NWP troposphere delay correction method | |
| CN108898252A (en) | A kind of prediction technique of whole nation troposphere Atmosphere Refractivity Profile | |
| CN109917424B (en) | Residual error correction method for troposphere delay in NWP (N-WP) inversion under multi-factor constraint | |
| CN101971047A (en) | Device and method for the real-time monitoring of the integrity of a satellite navigation system | |
| CN110275183B (en) | GNSS occultation ionosphere residual error correction method and system based on ionosphere electron density | |
| Mercier et al. | Estimation of finescale rainfall fields using broadcast TV satellite links and a 4DVAR assimilation method | |
| CN106093967A (en) | The ionosphere delay method for solving that a kind of pseudorange phase place is comprehensive | |
| CN113189620B (en) | GNSS occultation near space climate data inversion method and system | |
| CN110907967B (en) | High-precision integrity convection layer pipe abnormity monitoring method and device | |
| CN113325448A (en) | Large-altitude-difference CORS network resolving method considering troposphere delay reconstruction | |
| CN111982245A (en) | Method and device for calibrating main steam flow, computer equipment and storage medium | |
| CN105204047B (en) | A kind of detecting and repairing method of the single rough error of observed quantity in satellite navigation system | |
| CN117073933B (en) | Pipeline pressure monitoring method and system for gas pipe network | |
| CN102749634B (en) | Pseudo-range acceleration failure detecting method in satellite navigation region reinforcement system | |
| CN113777636B (en) | Double-smooth pseudo range domain detection method for GBAS ionosphere delay gradient | |
| Schulz et al. | Evaluation of a lightning location algorithm using an elevation model | |
| CN112733315B (en) | Integrity risk verification method and system | |
| CN109813339B (en) | Total station distance measurement method and system for sectional type atmosphere correction | |
| CN114037023A (en) | Method for correcting abnormal water vapor data of polar region of microwave radiometer by using marine satellite | |
| Liu et al. | Analysis on the performances of the GNSS tropospheric delay correction models | |
| CN113960635B (en) | Troposphere delay correction method considering daily variation | |
| CN109633699A (en) | A kind of satellite navigation system positioning performance calculation method based on bin count |
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 | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 200438 9 / F, 10 / F, 11 / F, 12 / F, 38 Lane 1688, Guoquan North Road, Yangpu District, Shanghai Applicant after: QIANXUN SPATIAL INTELLIGENCE Inc. Address before: Room j165, 1st floor, building 64, 1436 Jungong Road, Yangpu District, Shanghai, 200433 Applicant before: QIANXUN SPATIAL INTELLIGENCE Inc. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |