CN107038340B - The device and method of thermal noise data is found in a kind of A/C and S mode overlap signal - Google Patents
The device and method of thermal noise data is found in a kind of A/C and S mode overlap signal Download PDFInfo
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Abstract
The present invention discloses the device and method that thermal noise data are found in a kind of A/C mode and S mode overlap signal.The device includes data acquisition unit, data processing unit and data outputting unit；Data acquisition unit is for acquiring a segment signal data in A/C mode and S mode overlap signal；Data processing unit is sent to the data outputting unit for handling the signal data of acquisition；Data outputting unit is used to export data processing unit treated data；Device and method proposed by the present invention, thermal noise data can be searched out in the Overlapping data section that arbitrarily long A/C mode data and noise, S mode signal data and noise or A/C mode data+S mode signal data and noise are constituted, this method has preferable real-time and adaptivity, can preferably realize the estimation of thermal noise Data Data and its statistical property in Overlapping data.This method can be not limited to the searching of thermal noise data in practice, can be also found that clutter or the searching with random nature data.
Description
Technical field
Heat is found the present invention relates to thermal noise data processing field, in particular in a kind of A/C and S mode overlap signal to make an uproar
The device and method of sound data.
Background technique
A/C mode and S mode are MLAT (multiple spot surveillance technology) system, ADS-B (Automatic dependent surveillance broadcast) and two
The primary communication link agreement of secondary radar system is widely used to civil aviaton's traffic control field.A/C mode and S mode signal
Centre frequency be 1090MHz, and belong to pulse-position modulation, i.e., indicate information using the position of subpulse and level.
In practice, the statistical property for generally requiring accurately to receive thermal noise in signal to A/C mode and S mode carries out
Estimation, the statistical property of estimated thermal noise will play a key effect in subsequent decoding process.
The statistical property estimation method of conventional thermal noise is to find the number of one section of no signal (A/C mode and S mode signal)
Estimated according to section (only existing thermal noise in data).In practice, this method has following two:
(1) when emission source number is more, often there is following situations in real data: different amplitudes, different length A/
C mode and S mode signal are overlapped, and show as in longer receiving data segment that all there is signal+noises, it is difficult to be found
The estimation of one section of data segment (data for only existing thermal noise) Lai Jinhang thermal noise statistical property suitable enough.
(2) in practice, system and environmental properties are all changing, need in real time and adaptively to thermal noise characteristic into
Row estimation, the real-time and adaptivity of conventional method are poor.
The invention proposes a kind of methods, can be in arbitrarily long A/C mode data+noise, S mode signal data+noise
Or thermal noise data are searched out in the blended data section that is constituted of A/C mode data+S mode signal data+noise, this method tool
There are preferable real-time and adaptivity, can preferably realize the estimation of thermal noise statistical property.
This method can be not limited to the searching of thermal noise data in practice, can be also found that clutter or have random nature data
Searching.
Summary of the invention
The object of the present invention is to provide in a kind of A/C and S mode overlap signal find thermal noise data device and method,
In time-domain, a data sliding window is set, the data sliding window is constantly enterprising in the data sequence of received signal
Row sliding judges and searches out the thermal noise data for meeting statistical property requirement, and the data are put into sample estimates and are concentrated；If
A sample estimates collection is set, for storing the thermal noise data met the requirements；It is set when the number of data in sample estimates collection is greater than
When fixed number amount, the searching of abnormal point and rejecting abnormalities point are carried out.When the data number of the sample estimates collection of rejecting abnormalities point is big
When the threshold value of setting, then the statistical property of thermal noise can be estimated.
To achieve the above object, the present invention provides following schemes:
The device of thermal noise data is found in a kind of A/C and S mode overlap signal, including at data acquisition unit, data
Manage unit and data outputting unit；The data acquisition unit is for acquiring a segment signal in A/C mode and S mode overlap signal
Data；The data processing unit is sent to institute for handling the signal data that the data acquisition unit acquires
State data outputting unit；The data outputting unit is used to export the data processing unit treated data.
The method of thermal noise data is found in a kind of A/C mode and S mode overlap signal, comprising:
A segment signal data in step 201, acquisition A/C mode and S mode overlap signal define cycle-index I, initialization
The cycle-index I is 1；
The signal data is stored in data sliding window by step 202；
Step 203, the rising edge and failing edge for deleting the pulse of signal data in the data sliding window；
Signal data is by the ascending sequence of range value in step 204, the data sliding window for obtaining third step；
Step 205 judges whether the cycle-index is 1, is to execute step 206, no execution step 207；
Step 206 obtains top n signal data deposit sample estimates collection in the data sliding window, and described in deletion
The top n signal data in data sliding window, N are greater than 1 and are less than or equal to the data sliding window size value；
The 1st value x in step 207, the acquisition data sliding windoww1, calculate the mean value of the sample estimates collection
And standard deviation sigman；
Step 208, judgementWhether c is greater thannσn, wherein cnIt is to define constant, may be set to 2.6~4, is to delete
Step 210, no execution step 209 are executed in the data sliding window after all data；
Step 209, by the xw1It is put into the sample estimates collection, and out of described data sliding window described in deletion
xw1, execute step 207；
Step 210 judges whether the data number of the assessment sample set is greater than C1, and C1 is to define constant, and C1 can define
For the integer greater than 10, it is more than or equal to C1, then carries out abnormal point removal using the abnormal point processing method in cluster and handle to obtain
Data in sample estimates collection after abnormal point removal, then execute step 211；Less than C1, then the data sliding window along when
Between axis cross over the length of a data sliding window, then reload new data；The cycle-index I adds 1, executes step
203；
Step 211 judges whether data number is greater than C2 in the sample estimates collection after the abnormal point removes, and C2 is definition
Constant is greater than C2, then is handled using the statistical property estimation that the data in the sample estimates collection carry out thermal noise；Less than C2,
Then the data sliding window crosses over the length of a data sliding window along the time axis, then reloads new data；Institute
It states cycle-index I and adds 1, execute step 203；
Data in the sample estimates collection are carried out ascending sequence, and the data after sequence are put by step 212
Enter in sample estimates collection；The subsequent C3 data of the sample estimates collection are deleted, C3 is to define constant, obtains new sample estimates
Collect data.
The specific embodiment provided according to the present invention, the invention discloses following technical effects:
The installation method that thermal noise data are found in of the invention a kind of A/C and S mode overlap signal, can be arbitrarily long
A/C mode data and noise, S mode signal data and noise or A/C mode data+S mode signal data and noise are constituted
Blended data section in search out thermal noise data, this method has preferable real-time and adaptivity, can be preferably real
The estimation of existing thermal noise statistical property.This method can be not limited to the searching of thermal noise data in practice, can be also found that clutter or
Searching with random nature data.
Detailed description of the invention
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is the structural schematic diagram that the device of thermal noise data is found in a kind of A/C of the present invention and S mode overlap signal；
Fig. 2 is the flow diagram that the method for thermal noise data is found in a kind of A/C of the present invention and S mode overlap signal.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The object of the present invention is to provide in a kind of A/C and S mode overlap signal find thermal noise data device and method,
It can be in arbitrarily long A/C mode data and noise, S mode signal data and noise or A/C mode data+S mode signal data
Thermal noise data are searched out in the blended data section constituted with noise, this method has preferable real-time and adaptivity,
It can preferably realize the estimation of thermal noise statistical property.This method can be not limited to the searching of thermal noise data in practice, also
It can find clutter or the searching with random nature data.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to the accompanying drawing and specific real
Applying mode, the present invention is described in further detail.
Embodiment:
As shown in Figure 1 and Figure 2, the device of thermal noise data is found in a kind of A/C and S mode overlap signal, including data are adopted
Collect unit (1), data processing unit (2) and data outputting unit (3)；The data acquisition unit (1) is for acquiring A/C mode
With a segment signal data in S mode overlap signal；The data processing unit (2) is for adopting the data acquisition unit (1)
The signal data of collection is handled, and is sent to the data outputting unit (3)；The data outputting unit (3) is used for institute
State data processing unit (2) treated data output.
The method of thermal noise data is found in a kind of A/C and S mode overlap signal, comprising:
One integer variable is defined as cycle-index, and the initial value of cycle-index is set as 1 by step 201；Setting two
A data set, one is sample estimates collection, in initial setting, element-free in sample estimates collection；One is data sliding window,
Data sliding window contains the data (signal+noise) of one section of real-time reception, and data sliding window can be in received signal
Any position in data sequence starts；
Signal data is stored in data sliding window by step 202；
Step 203, the rising edge and failing edge for deleting pulse in data sliding window.
Step 204 after the data in data sliding window are carried out ascending sequence (range value), and is reentered into
Data sliding window.Because thermal noise values are generally less than signal value, sequence processing is by thermal noise data and there are the numbers of signal
According to separately: thermal noise data come before data sliding window, and after coming data sliding window there are the data of signal
Face, this is conducive to subsequent processing；
Step 205 judges whether the cycle-index is 1, is to execute step 206, no execution step 207；
Step 206 obtains top n signal data deposit sample estimates collection in the data sliding window, and described in deletion
The top n signal data in data sliding window, N are greater than 1 and are less than or equal to the data sliding window size value；
The 1st value x in step 207, the acquisition data sliding windoww1, calculate the mean value of the sample estimates collection
And standard deviation sigman；
Step 208, judgementWhether c is greater thannσn, wherein cnIt is to define constant, may be set to 2.6~4, is to delete
Step 210, no execution step 209 are executed in the data sliding window after all data；
Step 209, by the xw1It is put into the sample estimates collection, and out of described data sliding window described in deletion
xw1；Execute step 207；
Step 210 judges whether the data number of the assessment sample set is greater than C1, and C1 is to define constant, and C1 can define
For the integer greater than 10, it is more than or equal to C1, then carries out abnormal point removal using the abnormal point processing method in cluster and handle to obtain
Data in sample estimates collection after abnormal point removal, then execute step 211；Less than C1, then the data sliding window along when
Between axis cross over the length of a data sliding window, then reload new data；The cycle-index I adds 1, executes step
203；
Data in the sample estimates collection are carried out ascending sequence, and the data after sequence are put by step 211
Enter in sample estimates collection；The subsequent C3 data of the sample estimates collection are deleted, C3 is to define constant, may be defined as sample estimates
The 1/10~1/3 of data number, obtains new sample estimates collection data in collecting.The data sliding window is crossed over along the time axis
The length of one data sliding window, then reload new data；The cycle-index I adds 1, executes step 203；
Step 212, the statistical property estimation that use the data of data in sample estimates collection to carry out thermal noise are handled, then are estimated
Data number needs to be greater than C2 in meter sample set, and C2 is to define constant, and C2 and the estimated accuracy of required noise characteristic have
It closes, can be determined according to required precision.
C in above-mentioned stepsn, C1, C2, C3, N be all positive integer value predetermined.
Used herein a specific example illustrates the principle and implementation of the invention, and above embodiments are said
It is bright to be merely used to help understand method and its core concept of the invention；At the same time, for those skilled in the art, foundation
Thought of the invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not
It is interpreted as limitation of the present invention.
Claims (1)
1. finding the method for thermal noise data in a kind of A/C mode and S mode overlap signal, which is characterized in that comprising steps of
1) a segment signal data in A/C mode and S mode overlap signal, are acquired, cycle-index I is defined, initializes the circulation
Number I is 1；
2) signal data, is stored in data sliding window；
3) rising edge and failing edge of the pulse of signal data in the data sliding window, are deleted；
4), by signal data in 3) the data sliding window that step obtains by the ascending sequence of range value；
5), judge whether the cycle-index is 1, be to execute step 6, no execution step 7；
6) it, obtains top n signal data in the data sliding window and is stored in sample estimates collection, and delete the data sliding window
The top n signal data in mouthful, N are greater than 1 and are less than or equal to the data sliding window size value；
7) the 1st value x in the data sliding window, is obtainedw1, calculate the mean value of the sample estimates collectionAnd standard
Poor σn；
8), judge | xw1-xn| whether it is greater than cnσn, wherein cnIt is 2.6~4 constant, greater than then deleting the data sliding window
Step 10 is executed after interior all data, is less than or equal to execute step 9；
9), by the xw1It is put into the sample estimates collection, and deletes the x out of described data sliding windoww1, execute step
7；
10), judge whether the data number of the sample estimates collection is greater than C1, C1 is greater than 10 integer, is more than or equal to C1 then
Abnormal point removal is carried out using the abnormal point processing method in cluster to handle to obtain number in the sample estimates collection after abnormal point removes
According to, then step 11 is executed, it is less than C1, then the data sliding window crosses over the length of a data sliding window along the time axis
Degree, then reload new data；The cycle-index I adds 1, executes step 3；
11) whether data number is greater than C2 in the sample estimates collection after, judging abnormal point removal, C2 be defined as with it is required
Noise characteristic the related constant of estimated accuracy, be greater than C2, then carry out thermal noise using the data in the sample estimates collection
Statistical property estimation processing；Less than or equal to C2, then the data sliding window crosses over a data sliding window along the time axis
The length of mouth, then reload new data；The cycle-index I adds 1, executes step 3；
12) data in the sample estimates collection, are subjected to ascending sequence, and the data after sequence are put into estimation sample
In this collection；Delete the subsequent C3 data of the sample estimates collection, C3 be defined as data number in sample estimates collection 1/10~
1/3, obtain new sample estimates collection data.
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