CN113838313A - Obstacle identification method for course beacon channel clearance jitter - Google Patents
Obstacle identification method for course beacon channel clearance jitter Download PDFInfo
- Publication number
- CN113838313A CN113838313A CN202111428322.2A CN202111428322A CN113838313A CN 113838313 A CN113838313 A CN 113838313A CN 202111428322 A CN202111428322 A CN 202111428322A CN 113838313 A CN113838313 A CN 113838313A
- Authority
- CN
- China
- Prior art keywords
- jitter
- obstacle
- clearance
- azimuth
- airport
- 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.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/04—Anti-collision systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
Abstract
The invention discloses an obstacle identification method for course beacon channel clearance jitter, which solves the problems that in the prior art, when the channel clearance jitter exceeds the limit, relevant personnel in a field cannot analyze data by themselves and entrust a third party mechanism to analyze the data, so that the cost is high, the time is long, and the reason cannot be found in time. The method comprises the steps of establishing a basic geographic data model of the obstacle in front of a course beacon according to an airport topographic map, geographic information data, an obstacle vector and an airport CAD (computer-aided design) plane/elevation map, obtaining a jitter azimuth ϴ according to a current channel clearance flight correction curve, deducing a reflection point calculation method by establishing a reflection point function model, calculating and fitting a jitter area, converting the jitter area into a vector model, comparing the vector model with the basic geographic data model, analyzing the obstacle causing influence, and displaying and releasing the obstacle. The invention only needs to input simple self data, fits the whole reflection area causing the jitter by a single and a plurality of physical reflection point calculation methods, and identifies the barrier by comparative analysis.
Description
Technical Field
The invention belongs to the technical field of obstacle identification of course beacon channel clearance jitter, and particularly relates to an obstacle identification method of course beacon channel clearance jitter.
Background
The equipment for calibrating the clearance in civil aviation flight comprises a course beacon (course for short) and a gliding beacon (gliding for short), which are two pieces of equipment independent of each other, wherein the clearance of the course is called the channel clearance, and the gliding clearance is called the gliding clearance. A synthesis method of a gliding clearance curve is provided in an article of research and discussion about gliding clearance flight check standard in volume 2 and phase 6 of 2018 in the civil aviation bulletin, a solution is provided for the jitter of the gliding clearance, and an analysis method of the channel clearance is not mentioned. In addition, the fairway clearance and the glide clearance have the following differences: (1) the curve synthesis principle is different, the course is the synthesis of space direct projection and barrier reflection, and the gliding is caused by the space direct projection and the ground reflection; (2) the judgments of the shaking thresholds are different, the course is that the two sides of the center line of the channel are linearly increased to 175 muA and are kept from being not less than 175 muA to 10 degrees, the degree from 10 degrees to 35 degrees is more than or equal to 150 muA, and the downward sliding is mainly to judge that 190 muA does not repeatedly appear; (3) the reasons for the shaking are different, the course is heavier than the building, and the gliding is heavier than the mountain. In conclusion, the research on the heading clearance cannot refer to the analysis of the gliding clearance, and no relevant literature provides a method for solving the clearance jitter of the heading beacon, so that the independent analysis is needed.
The purpose of the course clearance check is to ensure that the course beacon is able to provide a correct course indication and that there are no false courses within the course beacon coverage area. If the channel clearance is out of limit due to jitter in a certain direction, the course beacon has the possibility of a false channel, equipment limitation or failure of flight verification is directly caused, the operation efficiency of an airport is greatly influenced, and even the civil aviation safety is threatened. Through a large amount of researches, the applicant finds that the clearance jitter overrun of the course beacon channel is closely related to the building for the first time. However, because the number of airport flight areas and surrounding buildings is large, it is difficult for airport equipment operation managers to directly determine which building is caused at the very first time of a problem, so that targeted debugging cannot be performed in flight correction, and the problem cannot be effectively solved. Meanwhile, if the problem is not solved, along with more and more construction around the airport, the accumulated problem is increased, the reason for the deterioration of the channel clearance signal can not be traced effectively, and the operation management and the operation safety of the airport are not facilitated.
In the prior art, a convenient method for calculating and identifying the obstacle in real time according to the flight correction result does not exist. When the clearance of the course beacon channel shakes, if a determined reason is required to be searched, a third party mechanism can only be entrusted, and analysis is carried out through signal simulation, so that the method has the following problems: (1) the modeling and simulation are carried out by combining antenna equipment, terrain and barrier models, the consumed time is long, the cost is high, and the operation and maintenance personnel of the common airport navigation equipment cannot carry out the operation and the simulation. (2) Only single simulation can be carried out and the real-time performance is not achieved, if other jitters exist in the next verification process, the simulation carried out in the previous process is already invalidated, and a third-party mechanism needs to be entrusted again to carry out analysis through signal simulation.
Therefore, designing a method for identifying obstacles with a course beacon channel clearance jitter to solve at least some of the above technical problems is a technical problem to be solved by those skilled in the art.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method for identifying the obstacle caused by the clearance jitter of the course beacon channel is provided to at least solve the partial technical problems.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
an obstacle identification method for course beacon channel clearance jitter comprises the following steps:
step 2, obtaining a jitter azimuth ϴ by taking values according to a current channel clearance flight correction data curve;
step 3, calculating and fitting a jitter vector model through the jitter azimuth ϴ in the step 2;
and 4, comparing the jitter vector model in the step 3 with the basic geographic data model in the step 1, analyzing the obstacles causing the influence, and displaying and releasing the obstacles.
Further, in step 3, in combination with the jitter azimuth ϴ, a single physical reflection point is first calculated, and then a plurality of physical reflection points are calculated according to the single physical reflection point, so as to fit a reflection region formed jointly, and finally obtain a vector model of the jitter region.
Further, the calculation method of the single physical reflection point comprises the following steps:
wherein D is the transverse distance between the reflection point and the central line of the runway, X is the longitudinal distance between the reflection point and the course beacon, L is the distance between the verification airplane and the course beacon, and ϴ is the azimuth angle of the jitter position relative to the extended line of the runway.
Further, in equation (1), when the positions of ϴ and D are fixed, the value of X can be found, so if there are two dither azimuth angles ϴ 1 and ϴ 2:
at the dither azimuth ϴ 1 in the first embodiment,
when D is respectively located at { D1,D2,…DnWhen is equal to (X), X is { X1, X 2, X 3… Xn} （2）
At the dither azimuth ϴ 2 in the azimuth,
when D is respectively located at { D1,D2,…DnWhen is equal to (X), X is { X1, X 2, X 3… Xn} （3）
Further, a specific method for obtaining the dither vector model is as follows: and fitting the linear reflection areas of the points according to the formulas (2) and (3), sequentially generating CAD files for the linear reflection areas forming influences, and finally converting the CAD files into vector models.
Further, the location of the reflection point is determined from the distance L of the verification aircraft from the heading beacon and the dithered azimuth ϴ.
Further, in the step 2, when taking values according to the current channel clearance correction data curve, a clearance value within +/-35 degrees is extracted.
Further, in the step 4, when the jitter vector model and the basic geographic data model are subjected to comparative analysis, the obstacle which may cause the influence is accurately determined according to the relative position relationship between the linear reflection area and the airport station and the surrounding geographic environment.
Further, the relative position relationship between the linear reflection area and the airport heading beacon at least comprises the distance and the angle between the linear reflection area and the airport heading beacon.
Further, in the step 4, after the analyzed obstacle causing the influence is displayed and issued, the obstacle is stored.
Compared with the prior art, the invention has the following beneficial effects:
the obstacle identification method for the course beacon channel clearance jitter is scientific and reasonable in design and convenient to use, the operation management personnel of the airport equipment can identify the obstacle causing the course clearance jitter only by inputting simple data, and the obstacle can be identified by comparing and analyzing through calculating by single and multiple physical reflection points and fitting the whole reflection area causing the jitter.
Compared with the prior art, the obstacle identification method for the course beacon channel clearance jitter has the following advantages: (1) the method is simple and convenient to use, and airport equipment operation management personnel can calculate by themselves only by inputting airport information, flight correction curves and modes, geography and airport planning CAD without trusting a third-party mechanism to perform modeling simulation. (2) The method is accurate in real time, only after analysis can be carried out in the prior art, and a single obstacle causing influence cannot be accurately identified from thousands of obstacles in the first time of occurrence of a problem; the obstacle identification method for the course beacon channel clearance jitter can accurately identify the single obstacle which causes influence from thousands of obstacles at the first time when the course beacon channel clearance jitter occurs. (3) The method for identifying the obstacle with the flutter course of the course beacon can accurately identify a single obstacle which influences the flight course from thousands of obstacles at the first time when the flutter occurs in the course beacon, so that the optimization measures can be provided in cooperation with the flight-checking team at the first time, and the invalid debugging can be avoided in cooperation with the flight-checking team at the first time, thereby reducing the investment cost of the airport. (4) The area affected by the jitter is found for the first time to be independent of the length and width of the airport runway and the distance of the course beacon from the end of the runway, and is only related to the position of the verification aircraft from the course beacon and the azimuth of the jitter.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is an evolution diagram of the method of the present invention.
FIG. 3 is a diagram showing the detailed working process of the method of the present invention.
FIG. 4 is a graph of a time flight check in an airport example of the present invention.
FIG. 5 is a topographical view of the periphery of an airport in an example of an airport of the present invention.
FIG. 6 is a plot of a fit of linear reflection regions for an airport example of the present invention.
FIG. 7 is a representation of a CAD file generated from linear reflection regions in an example airport of the present invention.
FIG. 8 is a diagram of obstacles analyzed by comparing a vector model with a geographic information model library in an airport example according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1-8, the obstacle identification method for course beacon channel clearance jitter provided by the invention has scientific and reasonable design and convenient use, the operation manager of the airport equipment can identify the obstacle causing the course clearance jitter only by inputting simple data, and the obstacle can be identified by comparing and analyzing through calculating by single and multiple physical reflection points and fitting the whole reflection area causing the jitter. The invention relates to an obstacle identification method for course beacon channel clearance jitter, which comprises the following steps:
Step 2, extracting a clearance value within +/-35 degrees according to a current channel clearance flight correction data curve to obtain a jitter azimuth ϴ;
step 3, establishing a function model according to the runway length L1, the runway width B, the distance LLZ between the course beacon and the end of the runway, the flight correction distance L and the jitter azimuth ϴ, and calculating and fitting a jitter vector model through the jitter azimuth ϴ in the step 2;
firstly, a single physical reflection point is calculated by combining the jitter azimuth ϴ, and the calculation method of the single physical reflection point comprises the following steps:
wherein D is the transverse distance between the reflection point and the central line of the runway, X is the longitudinal distance between the reflection point and the course beacon, L is the distance between the verification airplane and the course beacon, and ϴ is the azimuth angle of the jitter position relative to the extended line of the runway.
At the reflection point, D is the transverse distance from the reflection point to the center line of the runway, X is the longitudinal distance from the reflection point to the course beacon, for each reflection point, the incident angle from the transmitting end to the reflection point is assumed to be alpha, and for the incident part, tan alpha = D/X; for the reflection part, the transverse distance between the jitter position and the reflection point is calculated to be D + sin (ϴ) × L, the longitudinal distance between the jitter position and the reflection point is calculated to be cos (ϴ) × L-X, tan alpha = (D + sin (ϴ) × L)/(cos (ϴ) × L-X) is obtained, and the formula (1) can be obtained through simplification.
In equation (1), when the locations of ϴ and D are fixed, the value of X can be found, so if there are two dither azimuth angles ϴ 1 and ϴ 2:
at a jitter azimuth of ϴ 1,
when D is respectively located at { D1,D2,…DnWhen is equal to (X), X is { X1, X 2, X 3… Xn} （2）
At a jitter azimuth of ϴ 2,
when D is respectively located at { D1,D2,…DnWhen is equal to (X), X is { X1, X 2, X 3… Xn} （3）
And (3) fitting the linear reflection areas of the points based on the data in the steps (2) and (3), sequentially generating CAD files for the linear reflection areas forming influences, and finally converting the CAD files into vector models.
Step 4, comparing the jitter vector model in the step 3 with the basic geographic data model in the step 1, analyzing the obstacles causing the influence, and displaying, publishing and storing the obstacles; when the jitter vector model and the basic geographic data model are compared and analyzed, obstacles which may cause influence are accurately judged according to the relative position relation between the linear reflection area and the airport course beacon and by combining the surrounding geographic environment, and then the analyzed obstacles which cause the influence are displayed, released and stored; wherein the relative position relationship between the linear reflection area and the airport heading beacon at least comprises the distance and the angle between the linear reflection area and the airport heading beacon.
Compared with the prior art, the obstacle identification method for the course beacon channel clearance jitter has the following advantages: (1) the method is simple and convenient to use, and airport equipment operation management personnel can use the method only by inputting airport information, flight correction curves and modes, geography and airport planning CAD without trusting a third-party mechanism to perform modeling simulation. (2) The method is accurate in real time, only after analysis can be carried out in the prior art, and a single obstacle causing influence cannot be accurately identified from thousands of obstacles in the first time of occurrence of a problem; the obstacle identification method for the course beacon channel clearance jitter can accurately identify the single obstacle which causes influence from thousands of obstacles at the first time when the course beacon channel clearance jitter occurs. (3) The method for identifying the obstacle with the flutter course of the course beacon can accurately identify a single obstacle which influences the flight course from thousands of obstacles at the first time when the clearance of the course beacon flutters, so that the optimization measures can be provided with the flight checking team at the first time, and the invalid debugging can be avoided by matching the flight checking team at the first time, thereby reducing the airport investment cost. (4) The area affected by the jitter is found for the first time to be independent of the length and width of the airport runway and the distance of the course beacon from the end of the runway, and is only related to the position of the verification aircraft from the course beacon and the azimuth of the jitter.
The obstacle identification method for course beacon channel clearance jitter realizes the following working principle:
firstly, a current channel clearance flight check curve is called, and a jitter azimuth angle ϴ is obtained through value calculation. According to a judgment criterion AC-86-TM-2016-01 flight verification specification of civil aviation land-based navigation equipment: the two sides of the center line of the channel are linearly increased to 175 muA and are kept from being not less than 175 muA to 10 degrees, and the angle from 10 degrees to 35 degrees is greater than or equal to 150 muA and is taken as a reference line, and the flight calibration curve and the reference line are compared. And secondly, configuring a geographic data model library around the airport, wherein the geographic data model library comprises terrain, airport building vector data and airport planning CAD files. Thirdly, setting the length and width of the airport runway, the distance between the course beacon and the tail end of the runway, the flight correcting distance and the jitter limiting azimuth angle ϴ, establishing a function model by an optical-based calculation method after the setting is finished, obtaining physical reflection points at different positions from the centerline of the runway, forming a reflection area with multiple reflection points, converting the file into a vector model, and configuring the vector model to a geographic data model base through coordinate positioning. Thirdly, obstacles causing the influence are analyzed through comparison and displayed and issued. And finally, storing the result, thereby facilitating management.
The specific working process is as follows:
1. and establishing a site environment of the obstacle in front of the course beacon as a basic geographic data model according to the airport topographic map, the geographic information data, the obstacle vector and the airport CAD plane/elevation map.
2. And extracting a clearance value within +/-35 degrees according to the flight correction data curve to obtain the jittering direction ϴ.
3. Single physical reflection point and reflection area calculations.
And establishing a function model according to the runway length L1, the runway width B, the distance LLZ between the course beacon and the end of the runway, the flight correction distance L and the jitter azimuth ϴ.
D is the transverse distance between the reflection point and the central line of the runway, and X is the longitudinal distance between the reflection point and the central line of the runway.
Calculating a single physical reflection point by the following calculation method (1):
single point calculations, when ϴ and D are each fixed in position, can determine the value of X.
At the dither angle ϴ 1, the dither angle,
when D is respectively located at { D1,D2,…DnWhen is equal to (X), X is { X1, X 2, X 3… Xn} （2）
At the dither angle ϴ 2, the dither angle,
when D is respectively located at { D1,D2,…DnWhen is equal to (X), X is { X1, X 2, X 3… Xn}（3）
And (3) fitting the data in the steps (2) and (3) to the linear region of each point, finally forming an affected linear region to generate a CAD file, converting the CAD file into a vector model, and comparing the vector model with the geographic information data in the step (1).
4. And analyzing the obstacles causing the influence by comparison, displaying and publishing. And determining the obstacles which may cause influence according to the relative position relationship between the reflection area and the heading beacon, including the distance and the angle, and the surrounding geographic environment.
In order to enable a person skilled in the art to better understand the method for identifying the obstacle caused by the clearance jitter of the course beacon channel, the following airport example is provided.
1. As shown in FIG. 4, the curves of flight calibration at an airport show that the flutter orientation is about 28.5 ° -32 °, and the rounding results are ϴ 1=28 ° and ϴ 2=32 ° -degree
2. Configuring a peripheral airport topography map, geographic information data, obstacle vectors, airport CAD plane/elevation map, as shown in fig. 5. Peripheral obstacles are more, and the difficulty of accurately locking the obstacles is greater.
3. Setting parameters: runway length L1=4000 meters, runway width B =45 meters, course distance from runway end LLZ =220 meters, verification aircraft distance from course beacon L6 NM (about 11112 meters), flutter azimuth ϴ 1=28 °, ϴ 2=32 °, respectively.
6-8, the linear region is fit back by single point calculation using part of the correlation data for the airport, as shown in FIG. 6; generating a CAD file, as shown in FIG. 7; and converting the data into a vector model, comparing the vector model with a geographic information model base, and analyzing the obstacle, as shown in fig. 8.
4. In conclusion, comparative analysis, as shown in fig. 8, building a and building B are the main causes of the jitter.
5. Storing the flight correcting data, storing the current data, and storing and recording the data in the same way after the next flight correcting is finished.
The invention provides a method for identifying an obstacle with over-limit clearance jitter of a course beacon channel, which is used for inverting an area where the obstacle appears by utilizing an algorithm according to a flight correction result and airport information, comparing the area with a topographic map and an airport CAD (computer aided design) plane map and identifying the obstacle for the first time. The problem of current airport equipment operation managers can't utilize the data of oneself, real-time and accurate discernment cause the barrier that influences is solved to and when the shake appears in the navigation beacon channel clearance, from the barrier that causes the influence in a large number of barriers is accurately discerned, it is time-saving and progressive.
Finally, it should be noted that: the above embodiments are only preferred embodiments of the present invention to illustrate the technical solutions of the present invention, but not to limit the technical solutions, and certainly not to limit the patent scope of the present invention; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention; that is, the technical problems to be solved by the present invention, which are not substantially changed or supplemented by the spirit and the concept of the main body of the present invention, are still consistent with the present invention and shall be included in the scope of the present invention; in addition, the technical scheme of the invention is directly or indirectly applied to other related technical fields, and the technical scheme is included in the patent protection scope of the invention.
Claims (10)
1. An obstacle identification method for course beacon channel clearance jitter is characterized by comprising the following steps:
step 1, establishing a field environment of an obstacle in front of a course beacon as a basic geographic data model according to an airport topographic map, geographic information data, an obstacle vector and an airport CAD plane/elevation map;
step 2, obtaining a jitter azimuth ϴ by taking values according to a current channel clearance flight correction data curve;
step 3, calculating and fitting a jitter vector model through the jitter azimuth ϴ in the step 2;
and 4, comparing the jitter vector model in the step 3 with the basic geographic data model in the step 1, analyzing the obstacles causing the influence, and displaying and releasing the obstacles.
2. The method as claimed in claim 1, wherein in step 3, a single physical reflection point is calculated in combination with the jitter azimuth ϴ, and then a plurality of physical reflection points are calculated according to the single physical reflection point, so as to fit a reflection region formed together, and finally obtain a vector model of the jitter region.
3. The method for identifying the obstacle caused by the clearance jitter of the course beacon channel as claimed in claim 2, wherein the calculation method of the single physical reflection point comprises the following steps:
wherein D is the transverse distance between the reflection point and the central line of the runway, X is the longitudinal distance between the reflection point and the course beacon, L is the distance between the verification airplane and the course beacon, and ϴ is the azimuth angle of the jitter position relative to the extended line of the runway.
4. The method as claimed in claim 3, wherein in the formula (1), when the positions of ϴ and D are fixed, the value of X is determined, so that if there are two jitter azimuth angles ϴ 1 and ϴ 2:
at the dither azimuth ϴ 1 in the first embodiment,
when D is respectively located at { D1,D2,…DnWhen is equal to (X), X is { X1, X 2, X 3… Xn} （2）
At the dither azimuth ϴ 2 in the azimuth,
when D is respectively located at { D1,D2,…DnWhen is equal to (X), X is { X 1, X 2, X 3… Xn} （3）。
5. The method for identifying the obstacle with the clearance jitter of the course beacon channel as claimed in claim 4, wherein the specific method for obtaining the jitter vector model is as follows: and fitting the linear reflection areas of the points according to the formulas (2) and (3), sequentially generating CAD files for the linear reflection areas forming influences, and finally converting the CAD files into vector models.
6. The method as claimed in claim 3, wherein the location of the reflection point is determined based on the distance L of the verification aircraft from the heading beacon and the jitter azimuth ϴ.
7. The method for identifying the obstacle with the clearance jitter of the course beacon channel as claimed in claim 1, wherein in the step 2, when the value of the current channel clearance correction data curve is taken, the clearance value within ± 35 ° is extracted.
8. The method as claimed in claim 2, wherein in the step 4, when the jitter vector model and the basic geographic data model are compared and analyzed, the obstacle that may be affected is accurately determined according to the relative position relationship between the linear reflection area and the airport station and the surrounding geographic environment.
9. The method as claimed in claim 8, wherein the relative position relationship between the linear reflection region and the airport heading beacon includes at least a distance and an angle therebetween.
10. The method as claimed in claim 1, wherein in step 4, the analyzed obstacle causing the influence is displayed and released and then stored.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111428322.2A CN113838313B (en) | 2021-11-29 | 2021-11-29 | Obstacle identification method for course beacon channel clearance jitter |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111428322.2A CN113838313B (en) | 2021-11-29 | 2021-11-29 | Obstacle identification method for course beacon channel clearance jitter |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113838313A true CN113838313A (en) | 2021-12-24 |
| CN113838313B CN113838313B (en) | 2022-02-18 |
Family
ID=78971855
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111428322.2A Active CN113838313B (en) | 2021-11-29 | 2021-11-29 | Obstacle identification method for course beacon channel clearance jitter |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113838313B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116774207A (en) * | 2023-08-22 | 2023-09-19 | 中国民用航空总局第二研究所 | Obstacle recognition method and device for course beacon channel structure shake |
| CN117711208A (en) * | 2024-02-05 | 2024-03-15 | 中国民用航空总局第二研究所 | Method for analyzing influence of building position and distribution on course beacon channel jitter |
| CN117711208B (en) * | 2024-02-05 | 2024-04-23 | 中国民用航空总局第二研究所 | Method for analyzing influence of building position and distribution on course beacon channel jitter |
Citations (35)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103886587A (en) * | 2014-02-24 | 2014-06-25 | 深圳市飞天网景通讯有限公司 | Method and system for realizing positioning anti-shaking on terminal |
| WO2014115139A1 (en) * | 2013-01-23 | 2014-07-31 | Iatas (Automatic Air Traffic Control) Ltd | System and methods for automated airport air traffic control services |
| CN104008674A (en) * | 2014-06-16 | 2014-08-27 | 中国民航大学 | Terminal area approach flight time forecasting method based on pattern matching |
| CN104344882A (en) * | 2013-07-24 | 2015-02-11 | 中国国际航空股份有限公司 | Airplane jittering detection system and method |
| CN105450950A (en) * | 2015-12-07 | 2016-03-30 | 北京航空航天大学 | Method for removing jitter from aerial video of unmanned aerial vehicle |
| CN105716471A (en) * | 2014-12-02 | 2016-06-29 | 哈尔滨新光光电科技有限公司 | Method for simulating objective shaking through electromagnetic adsorption reflector |
| CN106324639A (en) * | 2016-09-13 | 2017-01-11 | 上海顺砾智能科技有限公司 | Unmanned plane automatic return flight method |
| US20170140654A1 (en) * | 2013-10-21 | 2017-05-18 | Rhett R. Dennerline | Database System to Organize Selectable Items for Users Related to Route Planning |
| CN106843282A (en) * | 2017-03-17 | 2017-06-13 | 东南大学 | Region based on M100 development platforms is searched for and obstacle avoidance system and method completely |
| CN107272028A (en) * | 2017-07-18 | 2017-10-20 | 中国民用航空总局第二研究所 | Navigation equipment on-line monitoring and flight check system and method based on unmanned plane |
| CN108172028A (en) * | 2018-02-24 | 2018-06-15 | 中国民用航空总局第二研究所 | The appraisal procedure that ground aviation device dynamic operation influences downslide structure |
| US20180218620A1 (en) * | 2017-02-01 | 2018-08-02 | Honeywell International Inc. | Air traffic control flight management |
| CN108614485A (en) * | 2018-05-24 | 2018-10-02 | 杨翼 | A kind of system of Global Airports barrier screening assessment |
| CN110008389A (en) * | 2019-02-13 | 2019-07-12 | 浩亚信息科技有限公司 | A kind of real-time measuring method of visual flight barrier, electronic equipment, storage medium |
| CN110097645A (en) * | 2019-05-16 | 2019-08-06 | 中国人民解放军95927部队 | A kind of flight simulation emulated interface removal dither method and flight simulator |
| CN110580381A (en) * | 2019-08-16 | 2019-12-17 | 中国民用航空总局第二研究所 | method for quickly simulating civil aviation course beacon antenna array |
| US20190392718A1 (en) * | 2018-06-20 | 2019-12-26 | Honeywell International Inc. | Apparatus and method for assisting flight crew during an approach to an airport with restrictions for non-standard conditions |
| CN110991153A (en) * | 2019-12-05 | 2020-04-10 | 北京天华航宇科技有限公司 | Flight verification report automatic generation method of instrument landing system |
| CN111103566A (en) * | 2019-11-28 | 2020-05-05 | 中国科学院上海微系统与信息技术研究所 | Course angle determining method, course angle determining system, electronic equipment and storage medium |
| CN111340389A (en) * | 2020-03-16 | 2020-06-26 | 民航数据通信有限责任公司 | Method and device for standardized control and evaluation of airport clearance obstacle |
| CN111526284A (en) * | 2020-04-03 | 2020-08-11 | 中国民用航空总局第二研究所 | Intelligent identification system and identification method for civil aviation gliding beacon interference source |
| CN111627108A (en) * | 2020-05-22 | 2020-09-04 | 邹仲恒 | Navigation airport low-altitude chart based on AR display technology and implementation system thereof |
| CN111824453A (en) * | 2020-06-08 | 2020-10-27 | 中国民用航空中南地区空中交通管理局 | Method and system for contrastively analyzing flight verification results of instrument landing system equipment |
| CN112173141A (en) * | 2020-09-25 | 2021-01-05 | 中国直升机设计研究所 | Helicopter synthetic view display method |
| CN112201082A (en) * | 2020-10-27 | 2021-01-08 | 上海行沙科技有限公司 | N-point replacement method for flight release time slot |
| CN112255612A (en) * | 2020-11-03 | 2021-01-22 | 中国电子科技集团公司第二十八研究所 | Radar track random jitter assessment method |
| CN112329101A (en) * | 2020-10-30 | 2021-02-05 | 中国航空国际建设投资有限公司 | Method for evaluating clearance of airport runway |
| CN112528793A (en) * | 2020-12-03 | 2021-03-19 | 上海汽车集团股份有限公司 | Method and device for eliminating shaking of obstacle detection frame of vehicle |
| CN112632795A (en) * | 2020-12-30 | 2021-04-09 | 中国民用航空总局第二研究所 | Implementation method for reducing beam width of course beacon array antenna |
| CN112669652A (en) * | 2021-01-08 | 2021-04-16 | 武汉凌云长空机场保障技术有限公司 | Airport sign light guide system |
| CN112748421A (en) * | 2019-10-30 | 2021-05-04 | 陕西汽车集团有限责任公司 | Laser radar calibration method based on automatic driving of straight road section |
| CN113205706A (en) * | 2021-04-22 | 2021-08-03 | 九州云(北京)科技发展有限公司 | ILS signal quality monitoring method based on flight QAR data |
| CN113421030A (en) * | 2021-07-21 | 2021-09-21 | 西安科优诚机场设计咨询有限公司 | Airport clearance obstacle standardized assessment method based on GIS system |
| CN113460328A (en) * | 2021-06-09 | 2021-10-01 | 中国商用飞机有限责任公司 | System and method for civil aircraft ground comprehensive dynamic detection |
| US20210358309A1 (en) * | 2019-02-15 | 2021-11-18 | Fujitsu Limited | Collision risk calculation method, storage medium, and collision risk calculation device |
-
2021
- 2021-11-29 CN CN202111428322.2A patent/CN113838313B/en active Active
Patent Citations (36)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014115139A1 (en) * | 2013-01-23 | 2014-07-31 | Iatas (Automatic Air Traffic Control) Ltd | System and methods for automated airport air traffic control services |
| US20180061243A1 (en) * | 2013-01-23 | 2018-03-01 | Iatas (Automatic Air Traffic Control) Ltd | System and methods for automated airport air traffic control services |
| CN104344882A (en) * | 2013-07-24 | 2015-02-11 | 中国国际航空股份有限公司 | Airplane jittering detection system and method |
| US20170140654A1 (en) * | 2013-10-21 | 2017-05-18 | Rhett R. Dennerline | Database System to Organize Selectable Items for Users Related to Route Planning |
| CN103886587A (en) * | 2014-02-24 | 2014-06-25 | 深圳市飞天网景通讯有限公司 | Method and system for realizing positioning anti-shaking on terminal |
| CN104008674A (en) * | 2014-06-16 | 2014-08-27 | 中国民航大学 | Terminal area approach flight time forecasting method based on pattern matching |
| CN105716471A (en) * | 2014-12-02 | 2016-06-29 | 哈尔滨新光光电科技有限公司 | Method for simulating objective shaking through electromagnetic adsorption reflector |
| CN105450950A (en) * | 2015-12-07 | 2016-03-30 | 北京航空航天大学 | Method for removing jitter from aerial video of unmanned aerial vehicle |
| CN106324639A (en) * | 2016-09-13 | 2017-01-11 | 上海顺砾智能科技有限公司 | Unmanned plane automatic return flight method |
| US20180218620A1 (en) * | 2017-02-01 | 2018-08-02 | Honeywell International Inc. | Air traffic control flight management |
| CN106843282A (en) * | 2017-03-17 | 2017-06-13 | 东南大学 | Region based on M100 development platforms is searched for and obstacle avoidance system and method completely |
| CN107272028A (en) * | 2017-07-18 | 2017-10-20 | 中国民用航空总局第二研究所 | Navigation equipment on-line monitoring and flight check system and method based on unmanned plane |
| CN108172028A (en) * | 2018-02-24 | 2018-06-15 | 中国民用航空总局第二研究所 | The appraisal procedure that ground aviation device dynamic operation influences downslide structure |
| CN108614485A (en) * | 2018-05-24 | 2018-10-02 | 杨翼 | A kind of system of Global Airports barrier screening assessment |
| US20190392718A1 (en) * | 2018-06-20 | 2019-12-26 | Honeywell International Inc. | Apparatus and method for assisting flight crew during an approach to an airport with restrictions for non-standard conditions |
| CN110008389A (en) * | 2019-02-13 | 2019-07-12 | 浩亚信息科技有限公司 | A kind of real-time measuring method of visual flight barrier, electronic equipment, storage medium |
| US20210358309A1 (en) * | 2019-02-15 | 2021-11-18 | Fujitsu Limited | Collision risk calculation method, storage medium, and collision risk calculation device |
| CN110097645A (en) * | 2019-05-16 | 2019-08-06 | 中国人民解放军95927部队 | A kind of flight simulation emulated interface removal dither method and flight simulator |
| CN110580381A (en) * | 2019-08-16 | 2019-12-17 | 中国民用航空总局第二研究所 | method for quickly simulating civil aviation course beacon antenna array |
| CN112748421A (en) * | 2019-10-30 | 2021-05-04 | 陕西汽车集团有限责任公司 | Laser radar calibration method based on automatic driving of straight road section |
| CN111103566A (en) * | 2019-11-28 | 2020-05-05 | 中国科学院上海微系统与信息技术研究所 | Course angle determining method, course angle determining system, electronic equipment and storage medium |
| CN110991153A (en) * | 2019-12-05 | 2020-04-10 | 北京天华航宇科技有限公司 | Flight verification report automatic generation method of instrument landing system |
| CN111340389A (en) * | 2020-03-16 | 2020-06-26 | 民航数据通信有限责任公司 | Method and device for standardized control and evaluation of airport clearance obstacle |
| CN111526284A (en) * | 2020-04-03 | 2020-08-11 | 中国民用航空总局第二研究所 | Intelligent identification system and identification method for civil aviation gliding beacon interference source |
| CN111627108A (en) * | 2020-05-22 | 2020-09-04 | 邹仲恒 | Navigation airport low-altitude chart based on AR display technology and implementation system thereof |
| CN111824453A (en) * | 2020-06-08 | 2020-10-27 | 中国民用航空中南地区空中交通管理局 | Method and system for contrastively analyzing flight verification results of instrument landing system equipment |
| CN112173141A (en) * | 2020-09-25 | 2021-01-05 | 中国直升机设计研究所 | Helicopter synthetic view display method |
| CN112201082A (en) * | 2020-10-27 | 2021-01-08 | 上海行沙科技有限公司 | N-point replacement method for flight release time slot |
| CN112329101A (en) * | 2020-10-30 | 2021-02-05 | 中国航空国际建设投资有限公司 | Method for evaluating clearance of airport runway |
| CN112255612A (en) * | 2020-11-03 | 2021-01-22 | 中国电子科技集团公司第二十八研究所 | Radar track random jitter assessment method |
| CN112528793A (en) * | 2020-12-03 | 2021-03-19 | 上海汽车集团股份有限公司 | Method and device for eliminating shaking of obstacle detection frame of vehicle |
| CN112632795A (en) * | 2020-12-30 | 2021-04-09 | 中国民用航空总局第二研究所 | Implementation method for reducing beam width of course beacon array antenna |
| CN112669652A (en) * | 2021-01-08 | 2021-04-16 | 武汉凌云长空机场保障技术有限公司 | Airport sign light guide system |
| CN113205706A (en) * | 2021-04-22 | 2021-08-03 | 九州云(北京)科技发展有限公司 | ILS signal quality monitoring method based on flight QAR data |
| CN113460328A (en) * | 2021-06-09 | 2021-10-01 | 中国商用飞机有限责任公司 | System and method for civil aircraft ground comprehensive dynamic detection |
| CN113421030A (en) * | 2021-07-21 | 2021-09-21 | 西安科优诚机场设计咨询有限公司 | Airport clearance obstacle standardized assessment method based on GIS system |
Non-Patent Citations (10)
| Title |
|---|
| XIGUANG CHEN: "A New Flight Procedure and Obstacle Limitation Surface Based Approach to Airport Clearance Area Analysis", 《2020 IEEE 2ND INTERNATIONAL CONFERENCE ON CIVIL AVIATION SAFETY AND INFORMATION TECHNOLOGY (ICCASIT)》 * |
| YUKUN CHEN: "Big Data Platform of Air Traffic Management", 《2019 IEEE 1ST INTERNATIONAL CONFERENCE ON CIVIL AVIATION SAFETY AND INFORMATION TECHNOLOGY (ICCASIT)》 * |
| 叶家全: "多径效应对航向信标系统电磁环境影响分析", 《系统工程与电子技术》 * |
| 吴鹏: "飞机位置预测模型的净空区障碍物评定方法", 《空军工程大学学报（自然科学版）》 * |
| 王新东: "基于机器视觉的无人机避障技术研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
| 翁文雯: "典型障碍物及地形对仪表着陆系统电磁环境影响研究", 《中国优秀博硕士学位论文全文数据库(硕士)工程科技Ⅱ辑》 * |
| 胡智敏: "浅谈下滑余隙在飞行校验中的遇到的问题及实际案例分析", 《中国新通信》 * |
| 赵庆田: "基于Deygout算法的航向台信号遮蔽分析", 《民航学报》 * |
| 钱亚明: "西安咸阳机场23L航向余隙信号不对称技术分析", 《通讯世界》 * |
| 马华蔚: "关于下滑余隙飞行校验标准的研究和探讨", 《民航学报》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116774207A (en) * | 2023-08-22 | 2023-09-19 | 中国民用航空总局第二研究所 | Obstacle recognition method and device for course beacon channel structure shake |
| CN116774207B (en) * | 2023-08-22 | 2023-10-24 | 中国民用航空总局第二研究所 | Obstacle recognition method and device for course beacon channel structure shake |
| CN117711208A (en) * | 2024-02-05 | 2024-03-15 | 中国民用航空总局第二研究所 | Method for analyzing influence of building position and distribution on course beacon channel jitter |
| CN117711208B (en) * | 2024-02-05 | 2024-04-23 | 中国民用航空总局第二研究所 | Method for analyzing influence of building position and distribution on course beacon channel jitter |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113838313B (en) | 2022-02-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9947109B2 (en) | Method and apparatus for direct detection, location, analysis, identification, and reporting of vegetation clearance violations | |
| Shi et al. | Automatic generation of road network map from massive GPS, vehicle trajectories | |
| CN108181635B (en) | Laser point cloud classification method for cross crossing analysis of power transmission line | |
| CN104931022B (en) | Satellite image stereoblock adjustment method based on spaceborne laser altimeter system data | |
| Truong-Hong et al. | Quantitative evaluation strategies for urban 3D model generation from remote sensing data | |
| Contreras et al. | Improving accuracy in earthwork volume estimation for proposed forest roads using a high-resolution digital elevation model | |
| CN113838313B (en) | Obstacle identification method for course beacon channel clearance jitter | |
| Wang et al. | Discontinuity interpretation and identification of potential rockfalls for high-steep slopes based on UAV nap-of-the-object photogrammetry | |
| Long | Modeling movement probabilities within heterogeneous spatial fields | |
| Timothée et al. | A network based kernel density estimator applied to Barcelona economic activities | |
| Fan et al. | Cooperative localization of 3D mobile networks via relative distance and velocity measurement | |
| CN108596397B (en) | Hydrological model-based multi-aircraft route planning method | |
| Pradhan et al. | Application of LiDAR in rockfall hazard assessment in tropical region | |
| CN111681313B (en) | Space vision analysis method based on digital topography and electronic equipment | |
| Johnson et al. | Can Loran meet GPS backup requirements? | |
| Kubička et al. | On designing robust real-time map-matching algorithms | |
| Ryan et al. | Review of trajectory accuracy methodology and comparison of error measurement metrics | |
| Lin et al. | Validation of mobile laser scanning for understory tree characterization in urban forest | |
| CN114443763A (en) | Big data synchronization method based on distributed network | |
| Kawecki et al. | The use of Multiwall model for reference RSSI data preparation for indoor localization purposes | |
| CN110148218B (en) | Method for integrally optimizing large-batch airborne LiDAR point cloud data | |
| Asavasuthirakul et al. | Integrated GNSS QoS prediction for navigation services | |
| Ren et al. | Search path planning algorithm based on the probability of containment model | |
| Xiaofang et al. | Intelligent planning of tourism scenic routes based on genetic algorithm in coal WANBEI mining subsidence | |
| Peng et al. | 3D City Map Reconstruction from LEO Communication Satellite SNR Measurements |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |