CN113341370B - Optimized beam scanning method in single-channel spatial spectrum direction finding system - Google Patents
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- G01S3/02—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
- G01S3/14—Systems for determining direction or deviation from predetermined direction
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Abstract
The invention discloses an optimized beam scanning method in a single-channel spatial spectrum direction-finding system, which is characterized in that a preset beam scanning angle design method in the existing method is adjusted, so that the calculation load can be greatly reduced, the number of preset beam scanning angles can be reduced, and the comprehensive performance of the existing single-channel spatial spectrum direction-finding system can be effectively improved. Meanwhile, the calculation method of the airspace covariance matrix is optimized, the reconstruction precision identical to that of the existing scheme can be achieved by using a small number of preset beam scanning angles, so that the number of preset angles required to be scanned is obviously reduced, and the execution period of an algorithm is shortened.
Description
Technical Field
The invention relates to the field of radio monitoring, in particular to an optimized beam scanning method in a single-channel spatial spectrum direction finding system.
Background
The radio direction finding system is an important component of a radio monitoring system and has very important application in the military and civil fields. As a novel radio direction finding system, the spatial spectrum direction finding system is a novel radio signal direction finding system, has higher direction finding resolution and sensitivity, can also be used for direction finding of a plurality of signals on the same frequency, and is the future development direction of the radio monitoring system.
The spatial spectrum direction-finding system becomes the development direction of the future radio monitoring system construction due to the multi-signal high-resolution characteristic. In order to solve the problems of high system cost, large development risk and the like faced by the traditional spatial spectrum direction-finding system based on the multichannel digital receiver, the traditional spatial spectrum direction-finding system can be replaced by adopting a single-channel spatial spectrum direction-finding system. The single-channel spatial spectrum direction-finding system only needs one digital receiving channel on hardware, and realizes a spatial spectrum direction-finding algorithm through beam scanning under the control of an analog circuit, thereby greatly reducing the system cost.
Reconstructing the spatial covariance matrix by beam scanning is the most critical step in the single-channel spatial spectrum direction finding system. The schematic block diagram of the existing single-channel spatial spectrum direction-finding system is shown in fig. 1, and only one digital receiving channel is needed in the single-channel spatial spectrum direction-finding system. The spatial covariance matrix required by the spatial spectrum direction finding algorithm can be obtained by means of analog beam scanning under the control of an analog phase shifter. After the airspace covariance matrix information is obtained, a multi-signal classification algorithm (MUSIC) can be executed in the direction-finding receiver to complete the incoming wave direction estimation.
For the principle structure shown in fig. 1, the calculation flow of the existing single-channel spatial spectrum direction-finding system is as follows:
the first step: presetting a beam scanning angle
In the scheme of the existing single-channel space spectrum direction-finding system, the preset beam scanning angle is uniformly faceted within the (-90 degrees, 90 degrees) range. Assuming that there are Q preset beam scan angles, the preset beam scan angles can be expressed as
And a second step of: performing beam scanning and collecting scanning results
If the current azimuth angle is theta (q) The beam forming device composed of analog phase shifters adjusts the beam direction theta of the beam forming device (q) Then the steering vector is a (θ (q) ) The received signal scanned on the qth beam at this time can be expressed as
c q [n]＝a H (θ (q) )y[n] (2)
In the formula (2), n represents the sampling time of time, a H Representing the conjugate transpose of the column vectors, y [ n ]]The sampled values of the vector representing the received signal contribution of each antenna at different times. Accordingly, the current average power can be calculated as
In the expression (3), N represents the number of all sampling times, R represents the spatial covariance matrix, and a vector represents the steering vector.
Using the matrix transformation relationship, equation (3) can be rewritten as
Wherein, the liquid crystal display device comprises a liquid crystal display device,where r=vec (R), vec (R) represents vectorizing the matrix R, converting the matrix into a vector R. Considering that there are Q known azimuth angles, equation (4) can be extended to a system of Q equations. Thus, the collected sampling results can be expressed as
Ar＝p (5)
Wherein a represents a steering matrix composed of steering vectors, a= (a) 1 ，a 2 ，…，a Q ) T The P vector represents the scan result of the Q directional beam scans, p= (P 1 ，P 2 ，…，P Q ) T 。
And a third step of: reconstructing airspace covariance matrix
Since the steering matrix A is a non-full order matrix, the unknown vector r in equation (4) can be solved by using the diagonal loading method, i.e
Wherein I represents M 2 ×M 2 Identity matrix, sigma of (a) 2 Representing the diagonal loading coefficients. After obtainingAfter that, the airspace covariance matrix can be reconstructed by the following method
Fourth step: executing a direction finding algorithm
After the airspace covariance matrix is obtained, DOA estimation operation can be performed by using a standard MUSIC algorithm or other similar spatial spectrum direction finding algorithms, and azimuth information of the unknown signals can be obtained.
By adopting the first step to the fourth step, the existing spatial spectrum direction-finding system can realize accurate estimation of the incoming wave direction. However, since the preset beam scanning angle is not optimally designed, the existing scheme has the following two problems:
(1) Algorithm execution period is long
In order to reconstruct the airspace covariance matrix accurately, a large number of scans are required for airspace angles, which results in a large number of preset azimuth angles. In order to perform full scanning, each preset azimuth angle needs to stay for a long enough time on the current preset angle, and a large number of angles to be scanned lead to a long beam scanning execution period, so that the execution efficiency of an algorithm is affected.
(2) The calculated amount is large
In the third step of the existing scheme, matrix inversion operation is needed to reconstruct the airspace covariance matrix. The flow of the existing scheme is observed to find that the matrix size to be inverted is M 2 ×M 2 The computational complexity of the matrix inversion operation can therefore be expressed as O (M 6 ). When the number of antennas is large, O (M 6 ) A huge computational burden will be created, which is detrimental to the practical implementation of the whole solution.
Disclosure of Invention
The invention provides an optimized beam scanning method in a single-channel spatial spectrum direction-finding system by comprehensively considering the problems of long algorithm execution period and large calculated amount in the existing scheme, and adjusts the design method of the preset beam scanning angle, so that the calculation burden can be greatly reduced, the number of the preset beam scanning angles can be reduced, and the comprehensive performance of the existing single-channel spatial spectrum direction-finding system can be effectively improved.
The invention discloses an optimized beam scanning method in a single-channel spatial spectrum direction-finding system, which comprises the following specific steps:
step one: presetting a beam scanning angle;
assuming that there are Q preset beam scan angles, the preset beam scan angles may be expressed as:
step two: performing beam scanning and collecting scanning results;
step three: reconstructing a airspace covariance matrix;
definition of gamma m 1 -m 2 ](m) th (m) representing spatial covariance matrix R 1 ，m 2 ) An item; at the same time, define vectors
Represents a (2M-1) x 1 vector containing all unrepeated unknown variable components in R, and the relationship of gamma to R can be expressed as
r=e·γ, where r=vec (R), vec (R) represents vectorizing the matrix R, converting the matrix into a vector R; matrix E represents an M 2 Matrix x (2M-1);
under the above definition conditions, the scan result in the second step can be written as
AEγ＝p
Wherein A represents a steering matrix composed of steering vectors, and E H A H AE is a full rank diagonal matrix; the p vector represents the scanning result of the Q directional beam scanning; therefore, the vector gamma can be recovered by the following method,
wherein D represents a diagonal matrix of (2M-1) x (2M-1).
Step four: and executing a direction finding algorithm.
The invention has the advantages that:
1. the optimized beam scanning method in the single-channel spatial spectrum direction finding system can reduce the calculation complexity of the airspace covariance matrix reconstruction algorithm, and is beneficial to improving the instantaneity of the reconstruction algorithm;
2. the optimized beam scanning method in the single-channel spatial spectrum direction-finding system can reduce the number of preset beam scanning angles and shorten the time required by beam scanning.
Drawings
Fig. 1 is a schematic block diagram of a conventional single-channel spatial spectrum direction finding system.
Fig. 2 is a flow chart of an optimized beam scanning method in the single-channel spatial spectrum direction finding system of the invention.
Fig. 3 is a comparison result of different preset beam scanning angle schemes in the single-channel spatial spectrum direction finding system according to the present invention.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings.
The optimized beam scanning method in the single-channel spatial spectrum direction-finding system of the invention, as shown in figure 2, comprises the following specific steps:
step one: presetting a beam scanning angle
Assuming that there are Q preset beam scan angles, the preset beam scan angles may be expressed as:
step two: performing beam scanning and collecting scanning results
If the current beam azimuth angle is theta (q) The beam forming device composed of analog phase shifters adjusts the beam direction theta of the beam forming device (q) Then the steering vector is (a (θ) (q) ) The received signal scanned on the qth beam at this time can be expressed as
c q [n]＝a H (θ (q) )y[n] (2)
In the formula (2), n represents the sampling time of time, a H Representing the conjugate transpose of the column vectors, y [ n ]]The sampled values of the vector representing the received signal contribution of each antenna at different times. Accordingly, the current average power can be calculated as
In the expression (3), N represents the number of all sampling times, R represents the spatial covariance matrix, and a vector represents the steering vector.
Using the matrix transformation relationship, equation (3) can be rewritten as
Wherein, the liquid crystal display device comprises a liquid crystal display device,a represents complex conjugation; r=vec (R), vec (R) representing the vectorization of the matrix R, converting it into a vector R. Considering that there are Q known azimuth angles, equation (4) can be extended to a system of Q equations. Thus, the collected sampling results can be expressed as
Ar＝p (5)
Wherein a represents a steering matrix composed of steering vectors, a= (a) 1 ，a 2 ，…，a Q ) T The P vector represents the scan result of the Q directional beam scans, p= (P 1 ，P 2 ，…，P Q ) T 。
And a third step of: reconstructing airspace covariance matrix
For a spatial covariance matrix of size M, although the matrix has M 2 The term, but the number of unknown variables is only 2M-1. Let v=vec (R) be considered to have more repetitive variables, and γm is defined 1 -m 2 ]Representing airspace(m) th covariance matrix R 1 ，m 2 ) An item. At the same time, define vectors
Represents a (2M-1) x 1 vector containing all unrepeated unknown variable constituents in R, and the relationship of gamma to R can be expressed as
r＝E·γ (7)
Wherein matrix E represents one M 2 Matrix of X (2M-1), i.e
Under the above definition, equation (5) can be rewritten as
AEγ＝p (9)
And has E H A H AE is a full rank diagonal matrix. Therefore, the vector gamma can be recovered by the following method,
here, D represents a diagonal matrix of (2M-1) × (2M-1).
Fourth step: executing a direction finding algorithm
After the airspace covariance matrix is obtained, DOA estimation operation can be performed by using a standard MUSIC algorithm or other similar spatial spectrum direction finding algorithms, and azimuth information of the unknown signals can be obtained.
In the scheme of the existing single-channel space spectrum direction-finding system, the preset beam scanning angles are uniformly distributed in the (-90 degrees, 90 degrees) range, and are expressed as
The preset beam scanning angle proposed by the formula 1 can reduce the number of beam angles to be scanned, so that the execution period of the algorithm is reduced. As shown in fig. 3, in the single-channel spatial spectrum estimation algorithm of a 64-element linear antenna array, different preset beam scanning angle schemes are considered in fig. 3 for the result of the spatial covariance matrix estimation.
As can be seen from fig. 3, the method provided by the present invention can achieve the same reconstruction accuracy as the existing scheme by using a smaller number of preset beam scanning angles, so that the number of preset angles required to be scanned is significantly reduced, and the execution period of the algorithm is shortened.
Reconstructing an airspace covariance matrix in the existing single channel, and solving an unknown vector r in the formula (4) by adopting a diagonal loading method, namely
Wherein I represents M 2 ×M 2 Identity matrix, sigma of (a) 2 Representing the diagonal loading coefficients. After obtainingAfter that, the airspace covariance matrix can be reconstructed by the following method
Compared with the matrix inversion operation in the formula (12), the main calculation amount in the formula (10) is Q times of vector multiplication, and the corresponding calculation complexity is O (M). Thus, the sum complexity is O (M 6 ) The matrix inversion operation complexity is a cubic of the dimension, and since the matrix dimension is M2, the calculation in equation (12) can significantly reduce the calculation amount compared with the matrix inversion operation whose overall complexity is M6).
Claims (1)
1. The optimized beam scanning method in the single-channel space spectrum direction finding system is characterized in that: the method comprises the following steps:
step one: presetting a beam scanning angle;
assuming that there are Q preset beam scan angles, the preset beam scan angles may be expressed as:
step two: performing beam scanning and collecting scanning results;
step three: reconstructing a airspace covariance matrix;
definition of gamma m 1 -m 2 ](m) th (m) representing spatial covariance matrix R 1 ，m 2 ) An item; at the same time, define vectors
Represents a (2M-1) x 1 vector containing all unrepeated unknown variable components in R, and the relationship of gamma to R can be expressed as
r＝E·γ
Where r=vec (R), vec (R) represents vectorizing the matrix R, converting the matrix into a vector R; matrix E represents an M 2 Matrix x (2M-1);
under the above definition conditions, the scan result in the second step can be written as
AEγ＝p
Wherein A represents a steering matrix composed of steering vectors, and E H A H AE is a full rank diagonal matrix; the p vector represents the scanning result of the Q directional beam scanning; therefore, the vector gamma can be recovered by the following method,
wherein D represents a diagonal matrix of (2M-1) x (2M-1).
Step four: and executing a direction finding algorithm.
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| CN1752771A (en) * | 2005-10-20 | 2006-03-29 | 武汉大学 | Single channel phase control array receiving signal reconstruction and space signal treatment method |
| CN109459744A (en) * | 2018-12-19 | 2019-03-12 | 西北工业大学 | A kind of robust adaptive beamforming method for realizing more AF panels |
| CN110531311A (en) * | 2019-08-27 | 2019-12-03 | 武汉大学深圳研究院 | A kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination |
| CN111427006A (en) * | 2020-04-27 | 2020-07-17 | 北京交通大学 | Single-channel spatial spectrum direction finding method based on phased array |
| CN111913157A (en) * | 2020-08-17 | 2020-11-10 | 西安空间无线电技术研究所 | Sea clutter suppression method based on radar signal space-time decorrelation model |
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| US8026841B2 (en) * | 2008-09-18 | 2011-09-27 | Bae Systems Controls Inc. | Range and azimuth resolution enhancement for real-beam radar |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN1752771A (en) * | 2005-10-20 | 2006-03-29 | 武汉大学 | Single channel phase control array receiving signal reconstruction and space signal treatment method |
| CN109459744A (en) * | 2018-12-19 | 2019-03-12 | 西北工业大学 | A kind of robust adaptive beamforming method for realizing more AF panels |
| CN110531311A (en) * | 2019-08-27 | 2019-12-03 | 武汉大学深圳研究院 | A kind of LTE external illuminators-based radar DOA estimation method based on matrix recombination |
| CN111427006A (en) * | 2020-04-27 | 2020-07-17 | 北京交通大学 | Single-channel spatial spectrum direction finding method based on phased array |
| CN111913157A (en) * | 2020-08-17 | 2020-11-10 | 西安空间无线电技术研究所 | Sea clutter suppression method based on radar signal space-time decorrelation model |
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