CN109754193A - ADS-B track denoising method based on aircraft performance - Google Patents
ADS-B track denoising method based on aircraft performance Download PDFInfo
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Abstract
The present invention relates to a kind of based on aircraft performanceADS‑BTrack denoising method, comprising: establish flight number information, flightADS‑BThe database of track data and civil aircraft model-performance data;Obtain specified flight crucial moment information andADS‑BTrack data;To the flightADS‑BTrack data carries out logic denoising;To the flightADS‑BTrack data carries out numerical value denoising.Based on aircraft performanceADS‑BTrack denoising method can not be byADS‑BThe limitation of track variable time step-length is simultaneously effectively identified and is deleted to noise, isADS‑BTrack denoising provides a feasible program, and the research work development for the Performance Evaluation research and green civil aviaton that are run based on track provides technical support.
Description
Technical field
The present invention relates to civil aviation air path data processing field, and in particular to a kind of based on aircraft performance
ADS-B track denoising method.
Background technique
Automatic dependent surveillance broadcast (Automatic Dependent Surveillance-Broadcast, ADS-B),
Hereinafter referred to as ADS-B, ADS-B terminal device are during Civil Aviation Flight state transfer, due to various signal interferences,
Obtained track point data has usually contained random mutation by a relatively large margin, causes track point data to deviate normal range (NR), in this way
Track points be noise.
Current main-stream denoising method is mainly the methods of Wavelet Denoising Method, Kalman filtering and Bayesian filter, but these sides
Method is only applicable to the case where time step immobilizes, such as radar data, and these methods need known probability density letter
The conditions such as the several or regularity of distribution.Since ADS-B is limited to the Distribution Breadth of geoceiver, and the receiver of different regions is anti-
There is differences for interference environment, therefore a feature of ADS-B track data is, time step is not equal and step-length span it is big (when
Between step-length minimum value be about 3 seconds, maximum value even up to by 10 minutes or more).This makes current main-stream Denoising Algorithm (comprising spreading out
Raw algorithm) application effect in ADS-B track data is unable to reach expection.
How to solve the above problems, is urgently to be resolved at present.
Summary of the invention
The ADS-B track denoising method based on aircraft performance that the object of the present invention is to provide a kind of.
In order to solve the above-mentioned technical problems, the present invention provides a kind of ADS-B track denoising side based on aircraft performance
Method, comprising:
Establish the database of flight number information, flight ADS-B track data and civil aircraft model-performance data;
Obtain the crucial moment information and ADS-B track data of specified flight;
Logic denoising is carried out to the ADS-B track data of the flight;
Numerical value denoising is carried out to the ADS-B track data of the flight.
The invention has the advantages that the present invention provides a kind of ADS-B track denoising method based on aircraft performance,
It include: the database for establishing flight number information, flight ADS-B track data and civil aircraft model-performance data;It obtains
The crucial moment information and ADS-B track data of specified flight;Logic denoising is carried out to the ADS-B track data of the flight;It is right
The ADS-B track data of the flight carries out numerical value denoising.ADS-B track denoising method based on aircraft performance can not be by ADS-
The limitation of B track variable time step-length simultaneously effectively identified and deleted to noise, and providing one for the denoising of ADS-B track can
Row scheme, and the research work development for the Performance Evaluation research and green civil aviaton that are run based on track provides technical support.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples.
Fig. 1 is the flow chart of the provided ADS-B track denoising method based on aircraft performance of the invention.
Fig. 2 is that flight number information with ADS-B track data field is associated with schematic diagram.
Fig. 3 is that Nanjing is flown to certain flight ADS-B altitude profile figure (before denoising) in Sydney.
Fig. 4 is that Nanjing is flown to certain flight ADS-B altitude profile figure (after denoising) in Sydney.
Specific embodiment
In conjunction with the accompanying drawings, the present invention is further explained in detail.These attached drawings are simplified schematic diagram, only with
Illustration illustrates basic structure of the invention, therefore it only shows the composition relevant to the invention.
Embodiment 1
As shown in Figure 1, the present embodiment 1 provides a kind of ADS-B track denoising method based on aircraft performance.Based on boat
The ADS-B track denoising method of pocket performance can not be limited by ADS-B track variable time step-length and be carried out to noise effective
It identifies and deletes, provide a feasible program, and the Performance Evaluation research to run based on track for the denoising of ADS-B track
Research work with green civil aviaton, which is carried out, provides technical support.Specifically, the ADS-B track denoising method based on aircraft performance
Include:
S110: the data of flight number information, flight ADS-B track data and civil aircraft model-performance data are established
Library.
In the present embodiment, the flight number information includes aircraft type information, actual time of departure ATOT and reality
Land time ALDT in border;The civil aircraft model-performance data include type fundamental performance parameter such as minimum operation weight
WOp, min, referential weight Wref, takeoff configuration stalling speed VS, ref_TOAnd Maximum Endurance pressure height HPmax.When Fig. 2 is flight
It carves information and is associated with schematic diagram with ADS-B track data field.
S120: the crucial moment information and ADS-B track data of specified flight are obtained.
Specifically, step S120 includes, monitor that the time carries out ascending order arrangement according to track points;
Other tracing points with the identical monitoring time are rejected, i.e., only retain a track points under a monitoring time;
It for scene track point data, i.e. field OnGround=1, is deleted, wherein OnGround=1 indicates aviation
Device is in ground taxi, this means that aircraft, on airport hardstand, taxiway or runway, such track data is known as scene
Track point data.
S130: logic denoising is carried out to the ADS-B track data of the flight.
Specifically, step S130 includes: the ADS-B track points queue { A for obtaining flight according to ADS-B track data0, A1,
A2, A3... An, wherein AnIndicate n-th of ADS-B track points;
Track points Ai, judge that it monitors time MTimeiWhether in actual time of departure ATOT to Actual Time Of Landing ALDT
In range, that is, MTimei∈ [ATOT, ALDT], if being unsatisfactory for this condition, way point AiIt is judged to noise, is directly navigated from ADS-B
It is rejected in mark point queue, wherein AiIndicate i-th of ADS-B track points;
Minimum flight altitude HP is defined according to model-performanceminWith highest cruising altitude HPmax, to ADS-B track points Ai, sentence
Its pressure height of breaking HPiWhether between minimum flight altitude and highest cruising altitude, that is, HPi∈[HPmin, HPmax], if discontented
This condition of foot, then way point AiIt is judged to noise, is directly rejected from ADS-B track points queue;
To track points Ai, according to the pressure height HP of the pointi, first calculate in this height under international Standard atmosphere conditions ISA
Atmospheric temperature Ti, finally calculate velocity of sound aI, ISA, it may be assumed that
Wherein air adiabatic coefficient k=1.4, gas constant R=287.05287m2/(K·s2);
Judge ground velocity GSiWhether in minimum stalling speed VS, minWith the velocity of sound a in this heightI, ISABetween, that is, GSi∈
[VS, min, aI, ISA], if being unsatisfactory for this condition, way point AiIt is judged to noise, is directly rejected from ADS-B track points queue.
In the present embodiment, the minimum stalling speed VS, minCalculation method are as follows:
According to the W for changing flight typeOp, min、WrefAnd VS, ref_TOStall speed of the type under takeoff configuration is calculated
Degree, i.e., minimum stalling speed VS, min:
S140: numerical value denoising is carried out to the ADS-B track data of the flight.
Specifically, step S140 includes: to way point Ai, define pressure altitude rate RI, i+1With its threshold function table
FI, i+1, form are as follows:
Wherein, RCmaxAnd RDmaxRespectively maximum climbing and MAX DES, and be positive number, threshold function table FI, i+1It is
Noise for identification is defined as according to the threshold function table of several adjacent track point pressure height as a result, identifying to noise
The function of two neighboring track point pressure altitude rate returns to different numbers according to by threshold range where altitude rate
It is worth result;
Calculate R0,1、R0,2And R0,3, and find out F0,1+F0,2+F0,3If end value is greater than or equal to 2, then it is assumed that A0Point
For noise, i.e. A0Height value is relative to A1And A2For noise, at this time by A0Rejecting is positive with first point for guaranteeing track points queue
Normal tracing point, A after deletion1It is changed to A0, A2It is changed to A1... ..., AnIt is changed to An-1And so on;
Calculate FI-1, i(i=1,2 ..., n), if FI-1, i=1, then tracing point AiIt is judged to noise and rejects it, successively
Analogize, last end value denoises process.
With one day from the Nanjing International airport Lu Kou (tetra- character code of ICAO: ZSNJ) Sydney International airport that flies to (tetra- character code of ICAO:
YSSY for certain flight ADS-B track data), Fig. 3 is the flying height section before denoising, and Fig. 4 is to be implemented using the present invention
Scheme denoised after flying height section.As it can be seen that the flight is within 190-550 minutes flight time in transoceanic flight
In the stage, ground ADS-B terminal device can not receive aircraft track data, but this has no effect on the reality of Denoising Algorithm of the present invention
It applies.Negative altitude noise and height catastrophe point when in Fig. 3 close to 610 minutes have all been identified and have deleted in Fig. 4.Following table
The noise statistic of classification of two aspects is denoised in logic denoising and numerical value for the flight:
By this example it can be proved that the present invention can not be limited by ADS-B track variable time step-length and to noise into
Row is effectively identified and is deleted, and provides a feasible program for the denoising of ADS-B track, and comment for the performance run based on track
Estimate research and offer technical support is carried out in the research work of green civil aviaton.
In conclusion the present invention provides a kind of ADS-B track denoising method based on aircraft performance, comprising: establish
The database of flight number information, flight ADS-B track data and civil aircraft model-performance data;Obtain specified flight
Crucial moment information and ADS-B track data;Logic denoising is carried out to the ADS-B track data of the flight;To the flight
ADS-B track data carries out numerical value denoising.ADS-B track denoising method based on aircraft performance can not can by ADS-B track
The limitation of variable time step is simultaneously effectively identified and is deleted to noise, provides a feasible program for the denoising of ADS-B track,
And the research work development for the Performance Evaluation research and green civil aviaton that are run based on track provides technical support.
Taking the above-mentioned ideal embodiment according to the present invention as inspiration, through the above description, relevant staff is complete
Various changes and amendments can be carried out without departing from the scope of the technological thought of the present invention' entirely.The technology of this invention
Property range is not limited to the contents of the specification, it is necessary to which the technical scope thereof is determined according to the scope of the claim.
Claims (6)
1. a kind of ADS-B track denoising method based on aircraft performance characterized by comprising
Establish the database of flight number information, flight ADS-B track data and civil aircraft model-performance data;
Obtain the crucial moment information and ADS-B track data of specified flight;
Logic denoising is carried out to the ADS-B track data of the flight;
Numerical value denoising is carried out to the ADS-B track data of the flight.
2. the ADS-B track denoising method based on aircraft performance as described in claim 1, which is characterized in that the flight
Time information includes aircraft model information, actual time of departure ATOT and practical landing time ALDT;
The civil aircraft model-performance data include type fundamental performance parameter such as minimum operation weight WOp, min, with reference to weight
Measure Wref, takeoff configuration stalling speed VS, ref_TOAnd Maximum Endurance pressure height HPmax。
3. the ADS-B track denoising method based on aircraft performance as claimed in claim 2, which is characterized in that the acquisition
The crucial moment information of specified flight and the method for ADS-B track data include:
Monitor that the time carries out ascending order arrangement according to track points;
Other tracing points with the identical monitoring time are rejected, i.e., only retain a track points under a monitoring time;
For scene track point data, i.e. field OnGround=1, deleted.
4. the ADS-B track denoising method based on aircraft performance as claimed in claim 3, which is characterized in that described pair should
The method that the ADS-B track data of flight carries out logic denoising includes:
The ADS-B track points queue { A of flight is obtained according to ADS-B track data0, A1, A2, A3... An, wherein AnIndicate n-th
A ADS-B track points;
Track points Ai, judge that it monitors time MTimeiWhether in actual time of departure ATOT to Actual Time Of Landing ALDT range
It is interior, that is, MTimei∈ [ATOT, ALDT], if being unsatisfactory for this condition, way point AiIt is judged to noise, directly from ADS-B track points
It is rejected in queue, wherein AiIndicate i-th of ADS-B track points;
Minimum flight altitude HP is defined according to model-performanceminWith highest cruising altitude HPmax, to ADS-B track points Ai, judge it
Pressure height HPiWhether between minimum flight altitude and highest cruising altitude, that is, HPi∈[HPmin, HPmax], if being unsatisfactory for this
Condition, then way point AiIt is judged to noise, is directly rejected from ADS-B track points queue;
To track points Ai, according to the pressure height HP of the pointi, first calculate big under international Standard atmosphere conditions ISA in this height
Temperature degree Ti, finally calculate velocity of sound aI, ISA, it may be assumed that
Wherein air adiabatic coefficient k=1.4, gas constant R=287.05287m2/(K·s2);
Judge ground velocity GSiWhether in minimum stalling speed VS, minWith the velocity of sound a in this heightI, ISABetween, that is, GSi∈[VS, min,
aI, ISA], if being unsatisfactory for this condition, way point AiIt is judged to noise, is directly rejected from ADS-B track points queue.
5. the ADS-B track denoising method based on aircraft performance as claimed in claim 4, which is characterized in that the minimum
Stalling speed VS, minCalculation method are as follows:
According to the W for changing flight typeOp, min、WrefAnd VS, ref_TOStalling speed of the type under takeoff configuration is calculated, i.e.,
Minimum stalling speed VS, min:
6. the ADS-B track denoising method based on aircraft performance as claimed in claim 5, which is characterized in that described pair should
The method that the ADS-B track data of flight carries out numerical value denoising includes:
To way point Ai, define pressure altitude rate RI, i+1With its threshold function table FI, i+1, form are as follows:
Wherein, RCmaxAnd RDmaxRespectively maximum climbing and MAX DES, and be positive number;
Calculate R0,1、R0,2And R0,3, and find out F0,1+F0,2+F0,3If end value is greater than or equal to 2, then it is assumed that A0Point is to make an uproar
Point, i.e. A0Height value is relative to A1And A2For noise, at this time by A0It rejects to guarantee that first point of track points queue is positive normal practice
Mark point, A after deletion1It is changed to A0, A2It is changed to A1... ..., AnIt is changed to An-1And so on;
Calculate FI-1, i(i=1,2 ..., n), if FI-1, i=1, then tracing point AiIt is judged to noise and rejects it, successively class
It pushes away, last end value denoises process.
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Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111538050A (en) * | 2020-04-17 | 2020-08-14 | 拉货宝网络科技有限责任公司 | GPS trajectory deviation rectifying method based on speed calculation strategy |
CN111785095A (en) * | 2020-07-31 | 2020-10-16 | 北京航空航天大学 | Monitoring performance index evaluation method |
CN112070305A (en) * | 2020-09-07 | 2020-12-11 | 民航数据通信有限责任公司 | Method for evaluating ADS-B four-dimensional track quality |
CN113254432A (en) * | 2021-05-25 | 2021-08-13 | 中国民航大学 | ADS-B flight trajectory data cleaning method based on fuzzy clustering |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20080004792A1 (en) * | 2006-06-29 | 2008-01-03 | Gerald Bowden Wise | Air traffic demand prediction |
CN104715154A (en) * | 2015-03-23 | 2015-06-17 | 西安交通大学 | Nuclear K-mean value track correlation method based on KMDL criteria |
-
2019
- 2019-01-28 CN CN201910084630.4A patent/CN109754193B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20080004792A1 (en) * | 2006-06-29 | 2008-01-03 | Gerald Bowden Wise | Air traffic demand prediction |
CN104715154A (en) * | 2015-03-23 | 2015-06-17 | 西安交通大学 | Nuclear K-mean value track correlation method based on KMDL criteria |
Non-Patent Citations (1)
Title |
---|
张余 等: "基于航迹数据的飞行状态识别方法研究", 《航空计算技术》 * |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111538050A (en) * | 2020-04-17 | 2020-08-14 | 拉货宝网络科技有限责任公司 | GPS trajectory deviation rectifying method based on speed calculation strategy |
CN111785095A (en) * | 2020-07-31 | 2020-10-16 | 北京航空航天大学 | Monitoring performance index evaluation method |
CN112070305A (en) * | 2020-09-07 | 2020-12-11 | 民航数据通信有限责任公司 | Method for evaluating ADS-B four-dimensional track quality |
CN113254432A (en) * | 2021-05-25 | 2021-08-13 | 中国民航大学 | ADS-B flight trajectory data cleaning method based on fuzzy clustering |
CN113254432B (en) * | 2021-05-25 | 2022-04-29 | 中国民航大学 | ADS-B flight trajectory data cleaning method based on fuzzy clustering |
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