CN104794334B - A kind of processing method of ADS B datas - Google Patents
A kind of processing method of ADS B datas Download PDFInfo
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Abstract
A kind of processing method of ADS B datas is disclosed, it can obtain the descending C mode altitude informations of airborne vehicle ADS B and geometric height data smoothing result data, as the follow-up related valid data source resolved.The processing method of this ADS B datas, including step：(1) the optimal smoothing section of initial data is calculated；(2) initial data is utilized, according to optimal smoothing section, altitude information array in initial data is smoothly solved one by one.
Description
Technical field
The present invention relates to the technical field of data processing, particularly a kind of ADS-B (Automatic Dependent
Surveillance-Broadcast, Automatic dependent surveillance broadcast) data processing method.
Background technology
Traditional aircraft altitude retention property monitoring means be based on (Enhanced GPS Monitoring Unit,
EGMU) geometric height of airborne vehicle is acquired with multipoint positioning technology, more a height of foot of rank of its geometric height precision, it is beautiful
Federal Aviation Administration of state (Federal Aviation Administration, FAA) technique center have developed the 1980s
Resolving software based on this kind of data, for track points altimetry systematic error (Altimetry System Error,
ASE) value is resolved.With the continuous development of new technology, outside EGMU and multipoint positioning technology, ADS-B technologies are built a station due to it
Easily, the features such as coverage is big, an emerging aircraft altitude retention property resolved data source is become.Based on ADS-
In the airborne vehicle monitoring of B data, the airborne vehicle geometric height data that ADS-B stations collect can be as the true height of airborne vehicle
Degree, and then by the step such as meteorological interpolation and the conversion of altitude datum face, complete the resolving for airborne vehicle altimetry systematic error.
This method has obtained applying more and more widely at present, the U.S., and Australia and Thailand successively start with this number
The resolving of altimetry systematic error (Altimetry System Error, ASE) value of track points is carried out according to source.
But EGMU and multipoint positioning data are compared, the geometric height precision of airborne vehicle decreases in ADS-B data, is
25 feet, and the U.S. is not improved for this change to its algorithm from its construction cost angle, but based on
The track points ASE of ADS-B data points has directly continued to use its existing algorithm in resolving, and Australia and Thailand are then directly to use
U.S. FAA software completes the data analysis of its own.
At present, China is in terms of ADS-B data smoothings or blank, if in the height retentivity based on ADS-B data
The method is used in assessing, then can obtain more accurate assessment result.
The content of the invention
The defects of to overcome prior art, the technical problem to be solved in the present invention is to provide a kind of place of ADS-B data
Reason method, it can obtain the descending C mode altitude informations of airborne vehicle ADS-B and geometric height data smoothing result data, make
For the follow-up related valid data source resolved.
The technical scheme is that：The processing method of this ADS-B data, comprises the following steps：
(1) the optimal smoothing section for treating initial data is calculated；
(2) initial data is utilized, according to optimal smoothing section, altitude information array in initial data is carried out one by one smoothly
Solve.
The present invention is smoothly solved one by one according to optimal smoothing section to altitude information sequence, so aviation can be obtained
C mode altitude information and geometric height data smoothing result data descending device ADS-B, as the follow-up related significant figure resolved
According to source.
Brief description of the drawings
Fig. 1 show the flow chart of the step (1) of the present invention；
Fig. 2 show the flow chart of the step (2) of the present invention；
Fig. 3 show the result figure of the present invention compared with U.S.'s FAA smoothing algorithms；
Fig. 4 show the result figure of the present invention compared with Australian smoothing algorithm.
Embodiment
Below by drawings and examples, technical scheme is described in further detail.
The parameters symbol used in calculating and its meaning are provided first：
x：Time array；
y：Flying height array；
hx：Time array median；
hy：Flying height array median；
K：Smooth function in section；
M：Sharpening result array.
The processing method of this ADS-B data, comprises the following steps：
(1) the optimal smoothing section of initial data is calculated；
(2) initial data is utilized, according to optimal smoothing section, altitude information array in initial data is carried out one by one smoothly
Solve.
The present invention is smoothly solved one by one according to optimal smoothing section to altitude information sequence, so aviation can be obtained
C mode altitude information and geometric height data smoothing result data descending device ADS-B, as the follow-up related significant figure resolved
According to source.
Preferably, as shown in figure 1, the step (1) include it is following step by step：
(1.1) start data smoothing, obtain time array x from ADS-B flight paths and flying height array y, its type are equal
For floating point type；
(1.2) calculate time array x median and be designated as hx1, calculate flying height array y medians and be designated as hy1；
(1.3) each element and median hx in x arrays are calculated1Difference absolute value, calculate y arrays in each element with
Digit hy1The absolute value of difference；
(1.4) intermediate variable is calculated according to the result of step (1.3), is designated as hx, hy；
(1.5) h is calculatedxAnd hyThe evolution of product, as optimal smoothing section, its formula are：
(1.6) terminate.
Preferably, the step (1.2) include it is following step by step：
(1.2.1) is replicated array x or y；
(1.2.2) calculates array length n, and array is since 0；
(1.2.3) judges whether array length is even number, and perform step (1.2.4) if even number performs step if odd number
(1.2.5)；
(1.2.4) median is arrayIndividual element andThe average of individual element, jumps to step
(1.2.6)；
(1.2.5) median is arrayIndividual element；
(1.2.6) terminates.
Preferably, the step (1.4) include it is following step by step：
(1.4.1) is by step (1.3) result divided by 0.6745；
(1.4.2) calculates array length n；
(1.4.3) calculates its five/first power again with 4 divided by 3n；
Step (1.4.1) result is multiplied by (1.4.4) with step (1.4.3) result；
(1.4.5) returns to step (1.4.4) result.
Preferably, as shown in Fig. 2 the step (2) include it is following step by step：
(2.1) according to formula (1), section smooth function is used as using normal distyribution function：
(2.2) normal distribution is set as standardized normal distribution, μ=0, σ=1；
(2.3) x, y arrays are introduced；
(2.4) i-th of element in traversal array x, access group x is denoted as xi；
(2.5) x in judgment step (2.4)iWhether can get, be then to perform step (2.6), otherwise perform step
(2.12)；
(2.6) x is usediEach element in array x is subtracted, generates interim array m；
(2.7) interim array l is calculated with array m and optimal smoothing section h；
(2.8) smooth function value is asked each element in array l to generate interim array k, ki=K (li)；
(2.9) result of step (2.8) is summed to obtain variable s；
(2.10) interim array p is calculated with array k and array y；
(2.11) array p sums to obtain variable t；
(2.12) s in step (2.9) divided by the t in step (2.11) are obtained into f, as calculating sharpening result array
I-th of element, it is put into sharpening result array M；
(2.13) i=i+1, and return to step (2.5) are made；
(2.14) it is smooth to terminate to return to array M.
Preferably, the step (2.4) include it is following step by step：
(2.4.1) is by xiSubtracted each other with array x all elements；
The result of step (2.4.1) is combined into a new array s and returned by (2.4.2).
Preferably, the step (2.7) include it is following step by step：
Each element in (2.7.1) traversal array s；
The element and optimal smoothing section h are divided by by (2.7.2)；
The result of step (2.7.2) is combined into a new array l and returned by (2.7.3).
Preferably, the step (2.10) include it is following step by step：
Each element in (2.10.1) traversal array y and array k；
(2.10.2) will be multiplied in array y with the corresponding element in array k；
The result of step (2.10.2) is combined into a new array p and returned by (2.10.3).
Preferably, the step (2.12) include it is following step by step：
(2.12.1) obtaining step (2.9) result；
(2.12.2) obtaining step (2.11) result；
The result of step (2.12.1) and step (2.12.2) is divided by by (2.12.3)；
(2.12.4) returns to the result of step (2.12.3).
It is described above, be only presently preferred embodiments of the present invention, any formal limitation not made to the present invention, it is every according to
Any simple modification, equivalent change and modification made according to the technical spirit of the present invention to above example, still belong to the present invention
The protection domain of technical scheme.
Claims (7)
1. a kind of processing method of ADS-B data, it is characterised in that comprise the following steps：
(1) the optimal smoothing section of initial data is calculated；
(2) initial data is utilized, according to optimal smoothing section, altitude information array in initial data is smoothly asked one by one
Solution；
The step (1) include it is following step by step：
(1.1) start data smoothing, time and altitude information array are obtained from ADS-B flight paths, is designated as x, y respectively, its type
It is floating point type；
(1.2) calculate time array x median and be designated as hx1, calculate flying height array y medians and be designated as hy1；
(1.3) each element and median hx in x arrays are calculated1The absolute value of difference, calculate each element and median in y arrays
hy1The absolute value of difference；
(1.4) intermediate variable is calculated according to the result of step (1.3), is designated as hx, hy；
(1.5) h is calculatedxAnd hyThe evolution of product, as optimal smoothing section, its formula are：
<mrow>
<mi>h</mi>
<mo>=</mo>
<msqrt>
<mrow>
<msub>
<mi>h</mi>
<mi>x</mi>
</msub>
<mo>&CenterDot;</mo>
<msub>
<mi>h</mi>
<mi>y</mi>
</msub>
</mrow>
</msqrt>
<mo>;</mo>
</mrow>
(1.6) terminate；
The step (1.4) include it is following step by step：
(1.4.1) is by step (1.3) result divided by 0.6745；
(1.4.2) calculates array length n；
(1.4.3) calculates its five/first power again with 4 divided by 3n；
Step (1.4.1) result is multiplied by (1.4.4) with step (1.4.3) result；
(1.4.5) returns to step (1.4.4) result.
2. the processing method of ADS-B data according to claim 1, it is characterised in that the step (1.2) includes following
Step by step：
(1.2.1) is replicated array x or y；
(1.2.2) calculates array length n, and array is since 0；
(1.2.3) judges whether array length is even number, and perform step (1.2.4) if even number performs step if odd number
(1.2.5)；
(1.2.4) median is arrayIndividual element andThe average of individual element, jump to step (1.2.6)；
(1.2.5) median is arrayIndividual element；
(1.2.6) terminates.
3. the processing method of ADS-B data according to claim 2, it is characterised in that the step (2) includes following point
Step：
(2.1) according to formula (1), section smooth function is used as using normal distyribution function：
<mrow>
<mi>K</mi>
<mrow>
<mo>(</mo>
<mi>u</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mrow>
<msqrt>
<mrow>
<mn>2</mn>
<mi>&pi;</mi>
</mrow>
</msqrt>
<mi>&sigma;</mi>
</mrow>
</mfrac>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mrow>
<mo>-</mo>
<mfrac>
<msup>
<mrow>
<mo>(</mo>
<mrow>
<mi>u</mi>
<mo>-</mo>
<mi>&mu;</mi>
</mrow>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mrow>
<mn>2</mn>
<msup>
<mi>&sigma;</mi>
<mn>2</mn>
</msup>
</mrow>
</mfrac>
</mrow>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
<mo>;</mo>
</mrow>
(2.2) normal distribution is set as standardized normal distribution, μ=0, σ=1；
(2.3) x, y arrays are introduced；
(2.4) i-th of element in traversal array x, access group x is denoted as xi；
(2.5) x in judgment step (2.4)iWhether can get, be then to perform step (2.6), otherwise perform step (2.12)；
(2.6) x is usediEach element in array x is subtracted, generates interim array m；
(2.7) interim array l is calculated with array m and optimal smoothing section h；
(2.8) smooth function value is asked each element in array l to generate interim array k, ki=K (li)；
(2.9) result of step (2.8) is summed to obtain variable s；
(2.10) interim array p is calculated with array k and array y；
(2.11) array p sums to obtain variable t；
(2.12) s in step (2.9) divided by the t in step (2.11) are obtained into f, i-th as calculating sharpening result array
Individual element, it is put into sharpening result array M；
(2.13) i=i+1, and return to step (2.4) are made；
(2.14) it is smooth to terminate to return to array M.
4. the processing method of ADS-B data according to claim 3, it is characterised in that the step (2.4) includes following
Step by step：
(2.4.1) is by xiSubtracted each other with array x all elements；
The result of step (2.4.1) is combined into a new array s and returned by (2.4.2).
5. the processing method of ADS-B data according to claim 4, it is characterised in that the step (2.7) includes following
Step by step：
Each element in (2.7.1) traversal array s；
The element and optimal smoothing section h are divided by by (2.7.2)；
The result of step (2.7.2) is combined into a new array l and returned by (2.7.3).
6. the processing method of ADS-B data according to claim 5, it is characterised in that the step (2.10) include with
Under step by step：
Each element in (2.10.1) traversal array y and array k；
(2.10.2) will be multiplied in array y with the corresponding element in array k；
The result of step (2.10.2) is combined into a new array p and returned by (2.10.3).
7. the processing method of ADS-B data according to claim 6, it is characterised in that the step (2.12) include with
Under step by step：
(2.12.1) obtaining step (2.9) result；
(2.12.2) obtaining step (2.11) result；
The result of step (2.12.1) and step (2.12.2) is divided by by (2.12.3)；
(2.12.4) returns to the result of step (2.12.3).
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Citations (1)
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|---|---|---|---|---|
| CN101110164A (en) * | 2007-08-15 | 2008-01-23 | 民航数据通信有限责任公司 | ADS-B control workstation data processing system |
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| US20110246001A1 (en) * | 2010-04-02 | 2011-10-06 | Cloudahoy Inc., | Systems and methods for aircraft flight tracking and emergency location |
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Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101110164A (en) * | 2007-08-15 | 2008-01-23 | 民航数据通信有限责任公司 | ADS-B control workstation data processing system |
Non-Patent Citations (3)
| Title |
|---|
| ADS-B数据评估技术研究;张军 等;《Chinese Journal of Aeronautics》;20110815(第4期);第460-466页 * |
| 基于ADS-B统计数据的航路安全间隔研究;王红勇 等;《中国安全科学学报》;20130215;第23卷(第2期);第103-108页 * |
| 机场三维态势呈现中IMMKF平滑ADS-B数据;李新胜 等;《系统工程与电子技术》;20140924;第37卷(第1期);第206-211页 * |
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