CN109188347B - Signal polarization mode three-classification method based on MUSIC spectrum - Google Patents

Signal polarization mode three-classification method based on MUSIC spectrum Download PDF

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CN109188347B
CN109188347B CN201811183028.8A CN201811183028A CN109188347B CN 109188347 B CN109188347 B CN 109188347B CN 201811183028 A CN201811183028 A CN 201811183028A CN 109188347 B CN109188347 B CN 109188347B
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郭元元
薛峰涛
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Beijing Institute of Remote Sensing Equipment
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Abstract

The invention discloses a signal polarization mode three-classification method based on a MUSIC spectrum, which specifically comprises the following steps: calculating the MUSIC spectrum of the received signal of the polarization sensitive array; extracting features based on MUSIC spectrum; and designing a polarization mode three classifier. The invention can realize high-precision angle estimation and polarization mode three-classification of the polarization sensitive array receiving signals on the premise of not increasing the testing workload.

Description

Signal polarization mode three-classification method based on MUSIC spectrum
Technical Field
The invention relates to a polarization mode three-classification method for polarization sensitive array received signals, in particular to a polarization mode three-classification method for polarization sensitive array received signals based on MUSIC spectrums.
Background
Recently, the polarization sensitive array is limited by factors such as wide attention of researchers and tested workload, and generally only performs a plane scan test that the polarization sensitive array receives two linear polarization signals of horizontal polarization and vertical polarization in a test stage with a cover, stores amplitude and phase information received by each array element, and then synthesizes horizontal and vertical polarization guide vectors of the polarization sensitive array by using the information.
However, the polarization sensitive array is usually sensitive to the polarization mode of the received signal, i.e. the polarization sensitive array only carries the guide vectors of the horizontal and vertical polarization modes, and for the received signal with the polarization mode matched with the guide vector, the angle estimation with higher precision can be respectively realized through the spatial spectrum estimation based on the MUSIC algorithm; for the received signals with the polarization mode not matched with the guide vector, the angle estimation with higher precision is difficult to realize through the spatial spectrum estimation based on the MUSIC algorithm.
Therefore, on the premise of not increasing the test workload, if the closed loop of the polarization sensitive array angle estimation system is to be completed, namely for the received signals of different polarization modes, the angle estimation with higher precision can be realized through the spatial spectrum estimation (based on the MUSIC algorithm), a polarization mode three-classification method of the polarization sensitive array received signals is designed, and the polarization mode three-classification of the polarization sensitive array received signals is realized, namely, the polarization mode class 1 (assuming H-type) γ,1 ): linear polarization angle γ =0 ° "," polarization mode class 2 (assuming H) γ,2 ): linear polarization angle γ ≠ 0 ° and γ ≠ 90 ° "and" polarization system class 3 "(assuming that H is γ,3 ): the linear polarization angle γ =90 ° ", is a problem to be solved.
Disclosure of Invention
In view of the above technical problems, an object of the present invention is to provide a polarization-sensitive array received signal polarization mode three-classification method based on MUSIC spectra, so as to implement polarization mode three-classification of polarization-sensitive array received signals.
A signal polarization mode three-classification method based on MUSIC spectrum specifically comprises the following steps:
s1, calculating an MUSIC spectrum of a polarization sensitive array receiving signal;
s2, extracting characteristics based on the MUSIC spectrum;
and S3, designing a polarization mode three classifier.
Further, the step S1 specifically includes:
according to the amplitude of each channel obtained by testing the polarization sensitive array under the conditions of horizontal polarization and vertical polarization respectively:
Figure BDA0001825466310000021
and phase difference:
Figure BDA0001825466310000022
wherein N is E Is the number of array elements (number of channels) of the polarization sensitive array, theta and
Figure BDA0001825466310000023
respectively outputting an incident azimuth angle and a pitch angle of a test result;
Figure BDA0001825466310000024
and
Figure BDA0001825466310000025
respectively indicate an incident direction of
Figure BDA0001825466310000026
The horizontally polarized reception amplitude and the vertically polarized reception amplitude of the time array element i,
Figure BDA0001825466310000027
and
Figure BDA0001825466310000028
respectively indicate an incident direction of
Figure BDA0001825466310000029
The horizontal polarization phase difference and the vertical polarization phase difference of the time array element i and the array element 1 (reference array element).
Respectively calculating horizontal polarization guide vectors a of the polarization sensitive array h And a perpendicular polarization steering vector a v Namely:
Figure BDA0001825466310000031
and
Figure BDA0001825466310000032
calculating a signal S with a real linear polarization angle gamma received by the polarization sensitive array γ Respectively based on horizontal polarization steering vector
Figure BDA0001825466310000033
And a perpendicular polarization steering vector
Figure BDA0001825466310000034
MUSIC spectrum P of γh And P γv The calculation formula is as follows:
Figure BDA0001825466310000035
Figure BDA0001825466310000036
wherein
Figure BDA0001825466310000037
For receiving a signal S γ The noise subspace feature vector matrix of (1).
Further, the step S2 specifically includes the steps of:
s201, according to a signal S with a real linear polarization angle gamma received by the polarization sensitive array γ MUSI of (A)C spectrum P γh And P γv Extracting statistical characteristics based on the MUSIC spectrum;
s202, respectively calculating the ratio of the MUSIC spectrum peak value to the MUSIC spectrum mean value, respectively calculating the ratio of the MUSIC spectrum standard deviation to the MUSIC spectrum mean value, and respectively calculating the ratio of the MUSIC spectrum peak value to the MUSIC spectrum base;
s203, calculating a spectrum P based on MUSIC γh Characteristic X of γh (S γ ) And based on MUSIC spectrum P γv Characteristic X of γv (S γ ) Obtaining a characteristic X (S) based on the MUSIC spectrum γ )。
Further, the step S201 specifically includes:
respectively calculating MUSIC spectral peak value x γh,1 ＝max(P γh ) And x γv,1 ＝max(P γv )。
Further, the step S201 specifically includes:
respectively calculating the average value x of the MUSIC spectrums γh,2 ＝μ(P γh ) And x γv,2 ＝μ(P γv )。
Further, the step S201 specifically includes:
respectively calculating the standard deviation x of the MUSIC spectrum γh,3 ＝σ(P γh ) And x γv,3 ＝σ(P γv )。
Further, the step S201 specifically includes:
calculating the MUSIC spectrum bases respectively:
Figure BDA0001825466310000041
and
Figure BDA0001825466310000042
wherein
Figure BDA0001825466310000043
And respectively have:
Figure BDA0001825466310000044
and
Figure BDA0001825466310000045
wherein theta is H And
Figure BDA0001825466310000046
upper bound, theta, of search for azimuth and pitch angles, respectively L And
Figure BDA0001825466310000047
lower bound, θ, of the search for azimuth and pitch angles, respectively S And
Figure BDA0001825466310000048
the search step lengths of the azimuth angle and the pitch angle are respectively.
Further, the step S202 specifically includes:
the ratio of the MUSIC spectrum peak value to the MUSIC spectrum mean value is calculated,
Figure BDA0001825466310000051
and
Figure BDA0001825466310000052
calculating the ratio of standard deviation of MUSIC spectrum to mean value of MUSIC spectrum,
Figure BDA0001825466310000053
and
Figure BDA0001825466310000054
respectively calculating the ratio of the MUSIC spectrum peak value to the MUSIC spectrum base,
Figure BDA0001825466310000055
and
Figure BDA0001825466310000056
further, the step S203 specifically includes:
X γh (S γ )＝{x γh,i :i＝1,...,7}；
X γv (S γ )＝{x γv,i :i＝1,...,7}；
X(S γ )＝X γh (S γ )∪X γv (S γ )。
further, the step S3 specifically includes:
the polarization mode three classifiers are H γ (S γ )＝C[X(S γ )]。
The invention can realize high-precision angle estimation and polarization mode three-classification of the polarization sensitive array receiving signals on the premise of not increasing the test workload.
Drawings
FIG. 1 is a schematic flow chart of a polarization-sensitive array received signal polarization-based three-classification method according to the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present 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.
In this embodiment, taking a polarization sensitive array in a certain structural state as an example, as shown in fig. 1, a polarization sensitive array received signal polarization mode three-classification method based on MUSIC spectrum includes the following specific steps:
in the first step, the MUSIC spectrum of the polarization sensitive array receiving signal is calculated.
According to the amplitude of each channel obtained by testing the polarization sensitive array under the conditions of horizontal polarization and vertical polarization respectively:
Figure BDA0001825466310000061
and phase difference:
Figure BDA0001825466310000062
wherein N is E Is the number of array elements (number of channels) of the polarization sensitive array, theta and
Figure BDA0001825466310000063
an incident azimuth angle and a pitch angle for outputting a test result are respectively;
Figure BDA0001825466310000064
and
Figure BDA0001825466310000065
respectively indicate an incident direction of
Figure BDA0001825466310000066
The horizontally polarized reception amplitude and the vertically polarized reception amplitude of the time array element i,
Figure BDA0001825466310000067
and
Figure BDA0001825466310000068
respectively indicate an incident direction of
Figure BDA0001825466310000069
The horizontal polarization phase difference and the vertical polarization phase difference of the time array element i and the array element 1 (reference array element).
Respectively calculating horizontal polarization guide vectors a of the polarization sensitive array h And a perpendicular polarization steering vector a v Namely:
Figure BDA0001825466310000071
and
Figure BDA0001825466310000072
calculating a signal S with a real linear polarization angle gamma received by the polarization sensitive array γ Respectively based on horizontally polarized steering vectors
Figure BDA0001825466310000073
And a perpendicular polarization steering vector
Figure BDA0001825466310000074
MUSIC spectrum P of γh And P γv The calculation formula is as follows:
Figure BDA0001825466310000075
Figure BDA0001825466310000076
wherein
Figure BDA0001825466310000077
For receiving a signal S γ The noise subspace feature vector matrix of (2).
And secondly, extracting features based on the MUSIC spectrum.
According to a signal S with a real linear polarization angle gamma received by a polarization sensitive array γ MUSIC spectrum P of γh And P γv Extracting statistical characteristics based on the MUSIC spectrum,
respectively calculating MUSIC spectrum peak values x γh,1 ＝max(P γh ) And x γv,1 ＝max(P γv ) Where the operator max (·) represents the calculated maximum value.
Respectively calculating the average value x of the MUSIC spectrums γh,2 ＝μ(P γh ) And x γv,2 ＝μ(P γv ) Where the operator μ (·) represents the calculated average.
Respectively calculating MUSIC spectrum standardDifference x γh,3 ＝σ(P γh ) And x γv,3 ＝σ(P γv ) Where the operator σ (·) represents the calculated standard deviation.
Calculating the MUSIC spectrum bases respectively:
Figure BDA0001825466310000081
and
Figure BDA0001825466310000082
wherein
Figure BDA0001825466310000083
And respectively have:
Figure BDA0001825466310000084
and
Figure BDA0001825466310000085
wherein theta is H And
Figure BDA0001825466310000086
upper bound, theta, of search for azimuth and pitch angles, respectively L And
Figure BDA0001825466310000087
lower bound, theta, of search for azimuth and pitch angles, respectively S And
Figure BDA0001825466310000088
the search step lengths of the azimuth angle and the pitch angle are respectively.
Respectively calculating the ratio of the peak value of the MUSIC spectrum to the mean value of the MUSIC spectrum according to the statistical characteristics based on the MUSIC spectrum
Figure BDA0001825466310000089
And
Figure BDA00018254663100000810
respectively calculating the ratio of the standard deviation of the MUSIC spectrum and the mean value of the MUSIC spectrum
Figure BDA00018254663100000811
And
Figure BDA00018254663100000812
and respectively calculating the ratio of the MUSIC spectrum peak value to the MUSIC spectrum base
Figure BDA00018254663100000813
And
Figure BDA00018254663100000814
the calculation is based on the MUSIC spectrum P γh Characteristic X of γh (S γ ) And based on MUSIC spectrum P γv Characteristic X of γh (S γ ) Obtaining a characteristic X (S) based on the MUSIC spectrum γ )，
X γh (S γ )＝{x γh,i :i＝1,...,7}；
X γv (S γ )＝{x γv,i :i＝1,...,7}；
X(S γ )＝X γh (S γ )∪X γv (S γ )。
And thirdly, designing a polarization mode three classifier. According to the feature X (S) based on the MUSIC spectrum γ )＝X γh (S γ )∪X γv (S γ ) Design polarization mode three classifiers H γ (S γ )＝C[X(S γ )]Three categories of polarization modes of the polarization sensitive array receiving signals, namely 'polarization mode class 1' (supposing H) γ,1 ): linear polarization angle γ =0 ° "," polarization mode class 2 (assuming H) γ,2 ): linear polarization angle γ ≠ 0 ° and γ ≠ 90 ° "and" polarization mode class 3 (assume H) γ,3 ): linear polarization angle γ =90 ° ".
It should be understood that the above embodiments are only examples for clarity of description, and are not limiting. Other variations and modifications will be apparent to persons skilled in the art upon reference to the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are intended to be within the scope of the invention.

Claims (9)

1. A signal polarization mode three-classification method based on MUSIC spectrum is characterized by comprising the following steps:
s1, calculating an MUSIC spectrum of a polarization sensitive array receiving signal;
s2, extracting characteristics based on the MUSIC spectrum;
s3, designing a polarization mode three classifier;
the step S1 specifically includes:
according to the amplitude of each channel obtained by testing the polarization sensitive array under the conditions of horizontal polarization and vertical polarization respectively:
Figure RE-FDA0003796125220000011
and phase difference:
Figure RE-FDA0003796125220000012
wherein N is E Is the array element number of the polarization sensitive array, theta and
Figure RE-FDA0003796125220000013
an incident azimuth angle and a pitch angle for outputting a test result are respectively;
Figure RE-FDA0003796125220000014
and
Figure RE-FDA0003796125220000015
respectively indicate an incident direction of
Figure RE-FDA0003796125220000016
The horizontally polarized reception amplitude and the vertically polarized reception amplitude of the time array element i,
Figure RE-FDA0003796125220000017
and
Figure RE-FDA0003796125220000018
respectively indicate an incident direction of
Figure RE-FDA0003796125220000019
The horizontal polarization phase difference and the vertical polarization phase difference of the time array element i and the array element 1;
respectively calculating horizontal polarization guide vectors a of the polarization sensitive array h And a perpendicular polarization steering vector a v Namely:
Figure RE-FDA00037961252200000110
and
Figure RE-FDA0003796125220000021
calculating a signal S with a real linear polarization angle gamma received by the polarization sensitive array γ Respectively based on horizontally polarized steering vectors
Figure RE-FDA0003796125220000022
And a perpendicular polarization steering vector
Figure RE-FDA0003796125220000023
MUSIC spectrum P of γh And P γv The calculation formula is as follows:
Figure RE-FDA0003796125220000024
Figure RE-FDA0003796125220000025
wherein
Figure RE-FDA0003796125220000026
For receiving a signal S γ The noise subspace feature vector matrix of (2).
2. The signal polarization mode three-classification method according to claim 1, wherein the step S2 specifically comprises the steps of:
s201, receiving a signal S with a true linear polarization angle gamma according to a polarization sensitive array γ MUSIC spectrum P of γh And P γv Extracting statistical characteristics based on the MUSIC spectrum;
s202, respectively calculating the ratio of the MUSIC spectrum peak value to the MUSIC spectrum mean value, respectively calculating the ratio of the MUSIC spectrum standard deviation to the MUSIC spectrum mean value, and respectively calculating the ratio of the MUSIC spectrum peak value to the MUSIC spectrum base according to the statistical characteristics based on the MUSIC spectrum;
s203, calculating the spectrum P based on the MUSIC γh Characteristic X of γh (S γ ) And based on MUSIC spectrum P γv Characteristic X of γv (S γ ) Obtaining a characteristic X (S) based on the MUSIC spectrum γ )。
3. The method for three classification of signal polarization modes according to claim 2, wherein the step S201 specifically comprises:
respectively calculating MUSIC spectral peak value x γh,1 ＝max(P γh ) And x γv,1 ＝max(P γv )。
4. The method for three classification of signal polarization modes according to claim 3, wherein the step S201 specifically comprises:
respectively calculating the average value x of the MUSIC spectrums γh,2 ＝μ(P γh ) And x γv,2 ＝μ(P γv )。
5. The method for three classification of signal polarization modes according to claim 4, wherein the step S201 specifically comprises:
respectively calculating the standard deviation x of the MUSIC spectrum γh,3 ＝σ(P γh ) And x γv,3 ＝σ(P γv )。
6. The method for three classification of signal polarization modes according to claim 5, wherein the step S201 specifically comprises:
calculating the MUSIC spectrum bases respectively:
Figure RE-FDA0003796125220000031
and
Figure RE-FDA0003796125220000032
wherein
Figure RE-FDA0003796125220000033
And respectively have:
Figure RE-FDA0003796125220000034
and
Figure RE-FDA0003796125220000035
wherein theta is H And
Figure RE-FDA0003796125220000036
upper bound, theta, of the search for azimuth and pitch angles, respectively L And
Figure RE-FDA0003796125220000037
lower bound, θ, of the search for azimuth and pitch angles, respectively S And
Figure RE-FDA0003796125220000038
the search step lengths of the azimuth angle and the pitch angle are respectively.
7. The method for three classification of signal polarization modes according to claim 6, wherein the step S202 specifically includes:
the ratio of the MUSIC spectrum peak value to the MUSIC spectrum mean value is calculated,
Figure RE-FDA0003796125220000041
and
Figure RE-FDA0003796125220000042
calculating the ratio of standard deviation of MUSIC spectrum to mean value of MUSIC spectrum,
Figure RE-FDA0003796125220000043
and
Figure RE-FDA0003796125220000044
respectively calculating the ratio of the MUSIC spectrum peak value to the MUSIC spectrum base,
Figure RE-FDA0003796125220000045
and
Figure RE-FDA0003796125220000046
8. the method for three classification of signal polarization modes according to claim 7, wherein the step S203 specifically comprises:
X γh (S γ )＝{x γh,i :i＝1,...,7}；
X γv (S γ )＝{x γv,i :i＝1,...,7}；
X(S γ )＝X γh (S γ )∪X γv (S γ )。
9. the method for three classification of signal polarization modes according to claim 8, wherein the step S3 specifically comprises:
the polarization mode three classifiers are H γ (S γ )＝C[X(S γ )]。
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