CN108923869A - A kind of Capon noise power estimation method based on orthogonal operators - Google Patents
A kind of Capon noise power estimation method based on orthogonal operators Download PDFInfo
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- CN108923869A CN108923869A CN201810860790.9A CN201810860790A CN108923869A CN 108923869 A CN108923869 A CN 108923869A CN 201810860790 A CN201810860790 A CN 201810860790A CN 108923869 A CN108923869 A CN 108923869A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04B17/00—Monitoring; Testing
- H04B17/20—Monitoring; Testing of receivers
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- H—ELECTRICITY
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- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
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Abstract
The invention belongs to signal processing technology fields, are related to a kind of Capon noise power estimation method based on orthogonal operators.The present invention composes direction finding result according to low-resolution spatial first and obtains signal distributions orientation, the orthogonal operators orthogonal with each orientation is found out again and classical Capon power estimator is reconstructed, any one azimuthal point with the amendment Capon power estimator of reconstruct in non-signal region carries out power estimation, in this, as noise power.The invention relative characteristic decomposition method does not need to carry out feature decomposition, classics Capon power estimator does not need to be calculated in all non-signal regions relatively, operand can be effectively reduced, and due to its orthogonal property, even if there are still can be with accurate estimation noise power when deviation in aspect estimation.
Description
Technical field
The invention belongs to signal processing technology fields, are related to a kind of noise power estimation side Capon based on orthogonal operators
Method.
Background technique
With the development of radio technology, the application such as mobile communication, broadcast, TV, navigation, remote-control romote-sensing, radar is
The every aspect of present national defence and people's daily life is gradually covered, researcher passes through sensor array or aerial array
Time-domain sampling is become temporal and spatial sampling, so that many theoretical results of signal procesing in time domain are generalized to airspace.Carrying out space
When Power estimation, spatial noise power is a very important parameter, and there are mainly two types of current spatial noise estimation methods：Base
In the noise power estimation of classical Capon spatial spectrum and based on the noise power estimation of Eigenvalues Decomposition.
When carrying out spacing wave Mutual coupling, classical Capon spatial power estimator since it is easily achieved,
Large-scale application is obtained.But this method has that power crosses estimation when carrying out noise estimation, especially more
It under a signal scene, can sharply amplify spatial noise, cause the subsequent estimation presence to signal power and direction of arrival very big
Error has seriously affected the performance of Estimation of Spatial Spectrum.
Although the noise power estimation method based on feature decomposition can in high s/n ratio more accurately estimating noise power,
But this method is with respect to Capon method that there are following two points defects：Firstly because it is related to feature decomposition, so relatively classical
Capon Estimation of Spatial Spectrum method, calculation amount are very big；Secondly it will appear signal subspace and noise subspace in low signal-to-noise ratio
The problem of obscuring causes power estimation error occur.
The precise degrees of spatial noise power estimation can produce bigger effect array signal treatment effect, estimate in spatial spectrum
On meter, if noise power estimation not will lead to the estimation of signal power precisely, there are errors；In Wave beam forming, receiving end noise
Power estimation is not allowed will lead to the weight design of final Adaptive beamformer and ideal weight there are relatively large deviation, causes to connect
Receiving end output signal-to-noise ratio relative theory value is greatly reduced, and seriously affects the overall performance of system.Therefore need one it is new high-precision
The noise power estimator spend, having a wide range of application.
Summary of the invention
The present invention provides a kind of Capon noise power estimation method based on orthogonal operators, realizes low operand premise
Under high-precision spatial noise estimation.Relatively classical Capon spatial noise estimation, the present invention do not need to carry out in entire airspace
Noise power calculation, it is only necessary to be estimated in an azimuthal point, and not need to carry out feature decomposition, greatly reduce operation
Amount.Further, since having carried out the amendment of orthogonal operators, the present invention may be implemented the accurate spatial noise under array error scene and estimate
Meter.
In order to make it easy to understand, the technology used to the present invention is explained as follows：
Traditional Capon power estimator can carry out the estimation of spatial noise power, but due to the remaining shadow of signal
It rings, the reason of the estimating, being crossed estimation of crossing that will lead to noise power is analyzed as follows.Firstly, the power at azimuth angle theta is estimated
It is represented by
Wherein, the theoretical data covariance matrix of R expression, is usually replaced with data covariance matrix in practice.In Gauss
Under white noise scene, it can be expressed as follows when only existing a signal：
Wherein a0It indicates to be located at angle, θ0Signal guide vector,WithThe power of signal and noise is respectively indicated, I is
Unit matrix.With matrix inversion lemma, above formula is represented by
The power estimation of Capon power estimator can be expressed as at azimuth angle theta at this time
Wherein M is element number of array, i.e., when orientation θ carries out power estimation, can be positive always and lead because of Section 2 in denominator
Crossing for power is caused to estimate.
To solve the above problems, the technical scheme is that：
One kind being based on the modified Capon spatial noise power estimation method of orthogonal operators, by orthogonal operators to classics
Capon power estimator is reconstructed, and this method is for the accurate estimation to spatial noise, which is characterized in that including following step
Suddenly：
S1, firstly, the Estimation of Spatial Spectrum method by low resolution detects signal distributions, determine signal in space
Number and angle；
S2, L be suppose there is positioned at angle, θl, l=1, the signal of 2 ..., L, obtain its steering vector composition matrix be
A=[a1,...,aL]；
S3, the orthogonal of above-mentioned matrix is taken, obtain orthogonal matrix and takes first to be classified as Δ；
S4, by a (θ) in classical Capon power estimator rebuild forWherein 0 is dimension
For the full null matrix of M × M-1.
S5, the Capon power estimator of reconstruct is subjected to power estimation in any one orientation in non-signal region, obtained
Value be spatial noise power.
Beneficial effects of the present invention are that the Capon power estimator based on orthogonal operators can remove the signal in space
Residual realizes accurately noise power estimation, and its result is unrelated with angle, it is only necessary to count to a space angle point
Accurately noise estimation can be obtained in calculation, greatly reduces calculation amount, provides for subsequent direction finding and signal power estimation
Reliable priori knowledge.
Detailed description of the invention
The flow chart of Fig. 1 present invention realization process；
Noise power estimation comparison diagram under Fig. 2 difference number of snapshots；
Noise power estimation comparison diagram under Fig. 3 difference signal-to-noise ratio；
Specific embodiment
Below in conjunction with drawings and examples, technical solution of the present invention is further described.
Embodiment 1
The purpose of the present embodiment is to compare under different number of snapshots scenes to different noise power estimation methods, is tested
Accurately noise power estimation may be implemented in the method for card invention.Number of snapshots are 50 to 500 in the present embodiment, respectively with classics
Capon method, feature decomposition method and improved Capon method carry out noise power estimation, and 200 tests are repeated under each number of snapshots.
The noise power estimation implementation method of embodiment is as shown in Fig. 1.It is known that there are four estimate through low-resolution spatial spectrum
The signal being located at -35,0,40 and 70 degree after meter, signal-to-noise ratio are about 20dB, 10dB, 20dB and 20dB, noise function
Rate is 0dB.The even linear array for selecting 10 array element half-wavelengths to structure the formation in test, it is assumed that there are the uncertainty of arrival bearing, i.e., low
The orientation of resolution ratio estimation is there are error and error obeys zero-mean, variance as 2 normal distribution.50 are taken to the data received
A snap, and do auto-correlation to replace the theoretical autocorrelation matrix in Capon power estimator and feature decomposition method, it is then right
Aspect steering vector after Estimation of Spatial Spectrum takes orthogonal to construct the modified Capon power estimator of orthogonal operators.It needs
Illustrate, classical Capon method is needed in all areas progress noise power estimation removed other than signal area and is averaged；
And feature decomposition method is to correspond to after carrying out feature decomposition to data autocorrelation matrix according to sequence removal signal from big to small
Feature after the average estimated value as noise power is taken to remaining characteristic value；Modified Capon method is only needed to signal
Any point calculated power value other than region can be used as accurate noise estimation.This example is after each test all to three kinds
Method power estimation stored, finish 200 times test after respectively summation take the average power as under this snap scene
Estimation.It is subsequent with 50 for step-length fetch evidence, terminate until getting 500 snaps.The comparing result of three kinds of method power estimation is as schemed
Shown in 2, the results showed that the mentioned method of the present invention signal estimation orientation there are remain unchanged when deviation can with accurate estimation noise power,
Without especially dividing when number of snapshots are greater than 200 with feature with the same noise power for amplifying estimation at double of classics Capon method
The estimated value of solution is bonded close and all approximation theory noise power 0dB, illustrates that this method can be smart under the premise of low operand
Really estimation noise.
Embodiment 2
The purpose of the present embodiment is to compare under different signal-to-noise ratio scenes to different noise power estimation methods, is tested
Accurately noise power estimation may be implemented in the method for card invention.Number of snapshots are 200 in the present embodiment, use classics Capon respectively
Method, feature decomposition method and improved Capon method carry out noise power estimation, and 200 tests are repeated under each signal-to-noise ratio.
The noise power estimation implementation method of embodiment is as shown in Fig. 1.Generation is located at -35,0,40 and 70 degree
Signal, the SNR ranges of second signal are -20dB to 20dB and using 5dB as step-length, and the signal-to-noise ratio of other signals is
20dB, noise power 0dB.The even linear array for selecting 10 array element half-wavelengths to structure the formation in test, it is assumed that there are arrival bearings not
The orientation of certainty, i.e. low resolution estimation is there are error and error obeys zero-mean, variance as 2 normal distribution.To reception
To data do auto-correlation to replace the theoretical autocorrelation matrix in Capon power estimator and feature decomposition method, it is then right
Aspect steering vector after Estimation of Spatial Spectrum takes orthogonal to construct the modified Capon power estimator of orthogonal operators.Three kinds
The comparing result of method power estimation is as shown in Figure 3, it can be seen that of the invention with the promotion of signal-to-noise ratio in 200 snap
The noise power that method and feature decomposition method are estimated fits closely and all approximation theory noise power 0dB, and classics Capon method
Noise power estimation near 3dB, has serious cross to estimate noise always, and it is inclined to illustrate that this method exists in aspect estimation
Still there is good noise estimation performance when poor.
Claims (1)
1. a kind of Capon noise power estimation method based on orthogonal operators, which is characterized in that include the following steps：
S1, signal distributions are detected by the Estimation of Spatial Spectrum method of low resolution, determine the number of signal in space with
And angle；
S2, L are set with positioned at angle, θl, l=1, the signal of 2 ..., L, the matrix for obtaining its steering vector composition is A=
[a1,...,aL]；
S3, the orthogonal of matrix A is taken, obtain orthogonal matrix and takes first to be classified as Δ；
In S4, classics Capon power estimator, the power estimation at azimuth angle theta is expressed as：
R is theoretical data covariance matrix；By a in above formula (θ) rebuild forWherein 0 is dimension
For the full null matrix of M × M-1；
S5, the Capon power estimator of reconstruct is subjected to power estimation, obtained value in any one orientation in non-signal region
As spatial noise power.
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Citations (3)
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| US6839574B2 (en) * | 2000-12-20 | 2005-01-04 | Arraycomm, Inc. | Method and apparatus for estimating downlink beamforming weights in a communications system |
| CN103000185A (en) * | 2011-09-30 | 2013-03-27 | 斯凯普公司 | Processing signals |
| US9559417B1 (en) * | 2010-10-29 | 2017-01-31 | The Boeing Company | Signal processing |
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2018
- 2018-08-01 CN CN201810860790.9A patent/CN108923869B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6839574B2 (en) * | 2000-12-20 | 2005-01-04 | Arraycomm, Inc. | Method and apparatus for estimating downlink beamforming weights in a communications system |
| US9559417B1 (en) * | 2010-10-29 | 2017-01-31 | The Boeing Company | Signal processing |
| CN103000185A (en) * | 2011-09-30 | 2013-03-27 | 斯凯普公司 | Processing signals |
Non-Patent Citations (2)
| Title |
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| XIAOPENG YANG等: "Improved orthogonal projection adaptive beamforming by using reconstructed interference covariance matrix", 《2014 INTERNATIONAL RADAR CONFERENCE》 * |
| 王安义等: "一种新的二维Capon算法的研究", 《西安科技学院学报》 * |
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