CN113534198B - Satellite navigation dynamic anti-interference method and system based on covariance matrix reconstruction - Google Patents
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Abstract
The invention discloses a satellite navigation dynamic anti-interference method and a system based on covariance matrix reconstruction, wherein the method comprises the following steps: constructing a uniform circular array for receiving interference signals and navigation signals, and obtaining baseband signals; performing autocorrelation processing according to snapshot data of the baseband signal to obtain an estimated value of a covariance matrix of the baseband signal in an initial state without interference suppression; processing the estimated value of the covariance matrix in the initial state by adopting a multiple signal classification algorithm to construct a spectrum function; and performing space domain expansion and null depth control on the spectrum function according to a windowing principle, performing reconstruction processing on the covariance matrix in the initial state by using the space domain expansion and null depth control result, and obtaining the null depth and the null width of the uniform circular array in the interference direction according to a solution of minimum variance undistorted response so as to determine the interference suppression degree. The invention can effectively inhibit the interference signal under the dynamic condition of the carrier, and has excellent anti-interference performance.
Description
Technical Field
The invention belongs to the technical field of satellite navigation anti-interference, and particularly relates to a satellite navigation dynamic anti-interference method and a system based on covariance matrix reconstruction.
Background
Conventional adaptive beamforming algorithms are typically derived in an ideal environment. However, in a more complex practical environment, the performance of the conventional adaptive beamforming algorithm is greatly reduced due to factors such as channel errors, array position errors, mutual coupling and the like.
In the military field, the satellite navigation receiver carrier is in a high-speed motion state mostly, and if a spatial filtering algorithm is directly adopted, interference is easily moved out of the null or is not in the deepest part of the null, so that the interference under the dynamic state cannot be effectively restrained. The current common treatment method is to widen the null. The widening zero-sinking method based on differential constraint has the problem of consuming the degree of freedom of interference resistance. In addition, the prior art also adopts covariance matrix tapering algorithm for processing, but the obvious disadvantages are that: the null depth is reduced while widening the null, so that the anti-strong-interference performance is reduced.
Disclosure of Invention
The invention aims to provide a satellite navigation dynamic anti-interference method based on covariance matrix reconstruction and a system thereof, which solve the problem of reduced anti-interference performance caused by the traditional null widening algorithm.
In view of the above, the present invention provides a method for dynamically resisting interference of satellite navigation based on covariance matrix reconstruction, which is characterized by comprising:
constructing a uniform circular array for receiving interference signals and navigation signals, and performing baseband processing on the interference signals and the navigation signals received by each array element of the uniform circular array to obtain baseband signals;
performing autocorrelation processing according to snapshot data of the baseband signal to obtain an estimated value of a covariance matrix of the baseband signal in an initial state without interference suppression;
processing the estimated value of the covariance matrix in the initial state by adopting a multiple signal classification algorithm through the mathematical relationship between the direction vector of the navigation signal and the direction vector of the interference signal so as to construct a spectrum function;
performing space domain expansion and null depth control on the spectrum function according to a windowing principle, and performing reconstruction processing on the covariance matrix in the initial state by using the space domain expansion and null depth control result to obtain a preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression;
based on the preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression, the null depth and the null width of the uniform circular array in the interference direction are obtained according to the solution of the minimum variance distortion-free response, so as to determine the interference suppression degree.
Further, the uniform circular array includes: the L-band right-hand circularly polarized antenna units are uniformly distributed on the circular dielectric substrate, and the array element units are equal in spacing and equal to half wavelength.
Further, the interference signal is a suppressed interference signal.
Further, a Hanning window is adopted to carry out space domain expansion and null depth control on the spectrum function.
Further, the baseband processing includes: down-conversion and low pass filtering.
Further, snapshot data of the baseband signal is obtained through bandpass sampling.
Further, the null depth control is performed by adding a depth coefficient.
Further, obtaining the optimized weight vector according to the solution of the minimum variance undistorted response.
Further, the optimized weight vector minimizes the output power of the uniform circular array.
Another object of the present invention is to provide a satellite navigation dynamic anti-interference system based on covariance matrix reconstruction, which is characterized by comprising:
the acquisition module is used for constructing a uniform circular array for receiving the interference signals and the navigation signals, and carrying out baseband processing on the interference signals and the navigation signals received by each array element of the uniform circular array to acquire baseband signals;
the estimation module is used for carrying out autocorrelation processing according to the snapshot data of the baseband signal to obtain an estimated value of a covariance matrix of the baseband signal in an initial state without interference suppression;
the calculating module is used for processing the estimated value of the covariance matrix in the initial state by adopting a multiple signal classification algorithm through the mathematical relationship between the direction vector of the navigation signal and the direction vector of the interference signal so as to construct a spectrum function;
the control module is used for performing space domain expansion and null depth control on the spectrum function according to a windowing principle, and performing reconstruction processing on the covariance matrix in the initial state by utilizing the space domain expansion and null depth control result to obtain a preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression;
and the determining module is used for obtaining the null depth and the null width of the uniform circular array in the interference direction according to the solution of the minimum variance undistorted response based on the preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression so as to determine the interference suppression degree.
The invention realizes the following remarkable beneficial effects:
the method for dynamically resisting the interference of the satellite navigation based on covariance matrix reconstruction comprises the following steps: constructing a uniform circular array for receiving interference signals and navigation signals, and performing baseband processing on the interference signals and the navigation signals received by each array element of the uniform circular array to obtain baseband signals; performing autocorrelation processing according to snapshot data of the baseband signal to obtain an estimated value of a covariance matrix of the baseband signal in an initial state without interference suppression; processing the estimated value of the covariance matrix in the initial state by adopting a multiple signal classification algorithm through the mathematical relationship between the direction vector of the navigation signal and the direction vector of the interference signal so as to construct a spectrum function; performing space domain expansion and null depth control on the spectrum function according to a windowing principle, and performing reconstruction processing on the covariance matrix in the initial state by using the space domain expansion and null depth control result to obtain a preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression; based on the preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression, the null depth and the null width of the uniform circular array in the interference direction are obtained according to the solution of the minimum variance distortion-free response, so as to determine the interference suppression degree. The spatial domain expansion is carried out on the spatial spectrum function through the windowing function, then the array covariance matrix is reconstructed by applying the expanded spectrum function, and the depth of the null is effectively controlled by adding the depth coefficient, so that the simulation experiment result shows that the anti-interference performance of the method is improved by 20dB compared with that of the traditional null widening method.
In a covariance matrix reconstruction-based satellite navigation dynamic anti-interference system, comprising: the acquisition module is used for constructing a uniform circular array for receiving the interference signals and the navigation signals, and carrying out baseband processing on the interference signals and the navigation signals received by each array element of the uniform circular array to acquire baseband signals; the estimation module is used for carrying out autocorrelation processing according to the snapshot data of the baseband signal to obtain an estimated value of a covariance matrix of the baseband signal in an initial state without interference suppression; the calculating module is used for processing the estimated value of the covariance matrix in the initial state by adopting a multiple signal classification algorithm through the mathematical relationship between the direction vector of the navigation signal and the direction vector of the interference signal so as to construct a spectrum function; the control module is used for performing space domain expansion and null depth control on the spectrum function according to a windowing principle, and performing reconstruction processing on the covariance matrix in the initial state by utilizing the space domain expansion and null depth control result to obtain a preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression; and the determining module is used for obtaining the null depth and the null width of the uniform circular array in the interference direction according to the solution of the minimum variance undistorted response based on the preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression so as to determine the interference suppression degree. The spatial domain expansion is carried out on the spatial spectrum function through the windowing function, then the array covariance matrix is reconstructed by applying the expanded spectrum function, and the depth of the null is effectively controlled by adding the depth coefficient, so that the simulation experiment result shows that the anti-interference performance of the method is improved by 20dB compared with that of the traditional null widening method.
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Fig. 1 is a flowchart of a method for dynamic anti-interference of satellite navigation based on covariance matrix reconstruction according to the present invention.
Description of the preferred embodiments
The advantages and features of the present invention will become more fully apparent from the following description and appended claims, taken in conjunction with the accompanying drawings and detailed description. It should be noted that the drawings are in a very simplified form and are adapted to non-precise proportions, merely for the purpose of facilitating and clearly aiding in the description of embodiments of the invention.
It should be noted that, in order to clearly illustrate the present invention, various embodiments of the present invention are specifically illustrated by the present embodiments to further illustrate different implementations of the present invention, where the various embodiments are listed and not exhaustive. Furthermore, for simplicity of explanation, what has been mentioned in the previous embodiment is often omitted in the latter embodiment, and therefore, what has not been mentioned in the latter embodiment can be referred to the previous embodiment accordingly.
While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof have been shown by way of example in the drawings and are herein described in detail. It should be understood that the invention is not to be limited to the particular embodiments disclosed, but on the contrary, the invention is to cover all modifications, equivalents, and alternatives falling within the spirit or scope of the invention as defined by the appended claims. The same element numbers may be used throughout the drawings to refer to the same or like parts.
Referring to fig. 1, the method for dynamically resisting interference of satellite navigation based on covariance matrix reconstruction of the present invention includes:
step S101, constructing a uniform circular array for receiving interference signals and navigation signals, and performing baseband processing on the interference signals and the navigation signals received by each array element of the uniform circular array to obtain baseband signals;
step S102, performing autocorrelation processing according to snapshot data of the baseband signal to obtain an estimated value of a covariance matrix of the baseband signal in an initial state without interference suppression;
step S103, processing the estimated value of the covariance matrix in the initial state by adopting a multiple signal classification algorithm through the mathematical relationship between the direction vector of the navigation signal and the direction vector of the interference signal so as to construct a spectrum function;
step S104, performing space domain expansion and null depth control on the spectrum function according to a windowing principle, and performing reconstruction processing on the covariance matrix in the initial state by utilizing the space domain expansion and null depth control result to obtain a preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression;
step S105, based on the preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression, obtaining the null depth and width of the uniform circular array in the interference direction according to the solution of the minimum variance distortion-free response so as to determine the interference suppression degree.
In one embodiment of the present application, specifically, the uniform circular array includes: the L-band right-hand circularly polarized antenna units are uniformly distributed on the circular dielectric substrate, and the array element units are equal in spacing and equal to half wavelength.
In one embodiment of the present application, the interference signal is specifically a suppressed interference signal.
In one embodiment of the present application, specifically, a Hanning window is used to perform spatial domain expansion and null depth control on the spectrum function.
In one embodiment of the present application, specifically, the baseband processing includes: down-conversion and low pass filtering.
In one embodiment of the present application, specifically, the snapshot data of the baseband signal is obtained through bandpass sampling.
In one embodiment of the present application, the null depth control is performed specifically by adding a depth coefficient.
In one embodiment of the present application, specifically, obtaining the optimized weight vector based on a solution of the minimum variance distortion-free response.
In one embodiment of the present application, specifically, the optimized weight vector minimizes the output power of the uniform circular array.
Another object of the present invention is to provide a satellite navigation dynamic anti-interference system based on covariance matrix reconstruction, comprising:
the acquisition module is used for constructing a uniform circular array for receiving the interference signals and the navigation signals, and carrying out baseband processing on the interference signals and the navigation signals received by each array element of the uniform circular array to acquire baseband signals;
the estimation module is used for carrying out autocorrelation processing according to the snapshot data of the baseband signal to obtain an estimated value of a covariance matrix of the baseband signal in an initial state without interference suppression;
the calculating module is used for processing the estimated value of the covariance matrix in the initial state by adopting a multiple signal classification algorithm through the mathematical relationship between the direction vector of the navigation signal and the direction vector of the interference signal so as to construct a spectrum function;
the control module is used for performing space domain expansion and null depth control on the spectrum function according to a windowing principle, and performing reconstruction processing on the covariance matrix in the initial state by utilizing the space domain expansion and null depth control result to obtain a preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression;
and the determining module is used for obtaining the null depth and the null width of the uniform circular array in the interference direction according to the solution of the minimum variance undistorted response based on the preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression so as to determine the interference suppression degree.
The method is characterized in that spatial domain expansion is carried out on a spatial spectrum function through a windowing function, then a depth coefficient is added to control the null depth, a new covariance matrix is reconstructed through the expanded spectrum function, an optimized weight vector is obtained, and widening and deepening of interference null are completed.
The following detailed description of specific embodiments of the main steps of the present invention is provided.
The two-dimensional space spectrum function is subjected to airspace expansion by utilizing a Hanning window, and the implementation mode is as follows:
under a uniform circular array, the two-dimensional spatial spectrum function is:
in the formula, theta,
Respectively representing the elevation angle and the azimuth angle of the incoming signal of the uniform circular array, +.>
Representing the direction vector of the uniform circular array received signal, R x Covariance matrix of the received signal of the uniform circular array is represented, (-) H Representing conjugate transpose (.) -1 Representing the matrix inversion. />
Firstly, performing space domain expansion on a two-dimensional space spectrum function:
in the method, in the process of the invention,
w (alpha) and W (beta) are window functions, phi α 、Φ β Is the width of the window.
From equation (2), it can be seen that the characteristics of the window functions W (α), W (β) will determine
Is a characteristic of (a). Here a Hanning window is used:
through the set value phi α 、Φ β The width of the nulls can be controlled.
The depth coefficient b is added to control the null depth as follows:
b is the depth coefficient of the null (b > 1, and b is the normal number). Equation (2) is a spatial function
Is extended by the space domain of (2), thus, ">
Is equivalent to->
From the theory of spatial spectrum estimation, capon spectrum can produce peaks in the interference direction. Therefore, the larger the depth coefficient b is, the larger the peak gain generated in the disturbance direction is, and the deeper the null is.
The covariance matrix R is reconstructed using the spread spectrum function, the implementation is as follows:
novel spatial spectral function
After construction, the array covariance matrix R is reconstructed by using the spectrum function:
in the method, in the process of the invention,
the resulting covariance matrix is reconstructed. Theta (theta) θ 、/>
And respectively defining interference intervals, and ensuring that all interference components are included.
Finally, the optimized weight vector is obtained, and the specific implementation modes are as follows:
(1) Taking a power inversion algorithm as an example, the output of the array is directly used as an error signal, and the minimum error signal is pursued according to an LMS criterion, namely a weighting value w is reasonably selected, so that the output power of the array is minimum. The cost function of the traditional power inversion algorithm is:
min w H R x w s.t.w T u 0 ＝1 (6)
in the constant vector u 0 ＝[1 0…0] T ，R x Is a covariance matrix. s.t. represents constrained, (. Cndot.) T Representing the transpose.
(2) The optimal solution for equation (6) is:
according to the technical scheme, aiming at the problems of the traditional null widening algorithm, the spatial domain expansion is carried out on the spatial spectrum function through the windowing function, then the array covariance matrix is reconstructed by applying the expanded spectrum function, the depth of the null is effectively controlled by adding the depth coefficient, and simulation experiment data show that the anti-interference performance of the method is improved by 20dB compared with that of the traditional null widening method.
From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:
1) The covariance matrix reconstruction-based satellite navigation dynamic anti-interference method comprises the following steps: constructing a uniform circular array for receiving interference signals and navigation signals, and performing baseband processing on the interference signals and the navigation signals received by each array element of the uniform circular array to obtain baseband signals; performing autocorrelation processing according to snapshot data of the baseband signal to obtain an estimated value of a covariance matrix of the baseband signal in an initial state without interference suppression; processing the estimated value of the covariance matrix in the initial state by adopting a multiple signal classification algorithm through the mathematical relationship between the direction vector of the navigation signal and the direction vector of the interference signal so as to construct a spectrum function; performing space domain expansion and null depth control on the spectrum function according to a windowing principle, and performing reconstruction processing on the covariance matrix in the initial state by using the space domain expansion and null depth control result to obtain a preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression; based on the preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression, the null depth and the null width of the uniform circular array in the interference direction are obtained according to the solution of the minimum variance distortion-free response, so as to determine the interference suppression degree. The spatial domain expansion is carried out on the spatial spectrum function through the windowing function, then the array covariance matrix is reconstructed by applying the expanded spectrum function, and the depth of the null is effectively controlled by adding the depth coefficient, so that the simulation experiment result shows that the anti-interference performance of the method is improved by 20dB compared with that of the traditional null widening method.
2) In the covariance matrix reconstruction-based satellite navigation dynamic anti-interference system, the method comprises the following steps: the acquisition module is used for constructing a uniform circular array for receiving the interference signals and the navigation signals, and carrying out baseband processing on the interference signals and the navigation signals received by each array element of the uniform circular array to acquire baseband signals; the estimation module is used for carrying out autocorrelation processing according to the snapshot data of the baseband signal to obtain an estimated value of a covariance matrix of the baseband signal in an initial state without interference suppression; the calculating module is used for processing the estimated value of the covariance matrix in the initial state by adopting a multiple signal classification algorithm through the mathematical relationship between the direction vector of the navigation signal and the direction vector of the interference signal so as to construct a spectrum function; the control module is used for performing space domain expansion and null depth control on the spectrum function according to a windowing principle, and performing reconstruction processing on the covariance matrix in the initial state by utilizing the space domain expansion and null depth control result to obtain a preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression; and the determining module is used for obtaining the null depth and the null width of the uniform circular array in the interference direction according to the solution of the minimum variance undistorted response based on the preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression so as to determine the interference suppression degree. The spatial domain expansion is carried out on the spatial spectrum function through the windowing function, then the array covariance matrix is reconstructed by applying the expanded spectrum function, and the depth of the null is effectively controlled by adding the depth coefficient, so that the simulation experiment result shows that the anti-interference performance of the method is improved by 20dB compared with that of the traditional null widening method.
Any other suitable modification may also be made according to the technical solution and the idea of the invention. All such alternatives, modifications and improvements will readily occur to those skilled in the art and are intended to be within the scope of the invention as defined in the appended claims.
Claims (10)
1. The method for dynamically resisting the interference of the satellite navigation based on covariance matrix reconstruction is characterized by comprising the following steps of:
constructing a uniform circular array for receiving interference signals and navigation signals, and performing baseband processing on the interference signals and the navigation signals received by each array element of the uniform circular array to obtain baseband signals;
performing autocorrelation processing according to snapshot data of the baseband signal to obtain an estimated value of a covariance matrix of the baseband signal in an initial state without interference suppression;
processing the estimated value of the covariance matrix in the initial state by adopting a multiple signal classification algorithm through the mathematical relationship between the direction vector of the navigation signal and the direction vector of the interference signal so as to construct a spectrum function;
performing space domain expansion and null depth control on the spectrum function according to a windowing principle, and performing reconstruction processing on the covariance matrix in the initial state by using the space domain expansion and null depth control result to obtain a preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression;
based on the preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression, the null depth and the null width of the uniform circular array in the interference direction are obtained according to the solution of the minimum variance distortion-free response, so as to determine the interference suppression degree.
2. The covariance matrix reconstruction-based dynamic anti-interference method for satellite navigation as recited in claim 1, wherein the uniform circular array comprises: the L-band right-hand circularly polarized antenna units are uniformly distributed on the circular dielectric substrate, and the array element units are equal in spacing and equal to half wavelength.
3. The covariance matrix reconstruction-based dynamic anti-interference method for satellite navigation as recited in claim 1, wherein the interference signal is a suppressed interference signal.
4. The covariance matrix reconstruction-based dynamic anti-interference method for satellite navigation according to claim 1, wherein the spatial domain expansion and null depth control are performed on the spectral function by using a Hanning window.
5. The covariance matrix reconstruction-based dynamic anti-interference method for satellite navigation as recited in claim 1, wherein the baseband processing comprises: down-conversion and low pass filtering.
6. The covariance matrix reconstruction-based dynamic anti-interference method for satellite navigation according to claim 1, wherein the snapshot data of the baseband signal is obtained by bandpass sampling.
7. The covariance matrix-reconstruction-based dynamic anti-interference method for satellite navigation as recited in claim 1, wherein the null depth control is performed by adding a depth coefficient.
8. The method of claim 7, wherein obtaining the optimized weight vector based on a solution of a minimum variance distortion-free response.
9. The covariance matrix reconstruction-based dynamic anti-interference method as recited in claim 8, wherein the optimized weight vector minimizes the output power of the uniform circular array.
10. A covariance matrix reconstruction-based satellite navigation dynamic anti-interference system, comprising:
the acquisition module is used for constructing a uniform circular array for receiving the interference signals and the navigation signals, and carrying out baseband processing on the interference signals and the navigation signals received by each array element of the uniform circular array to acquire baseband signals;
the estimation module is used for carrying out autocorrelation processing according to the snapshot data of the baseband signal to obtain an estimated value of a covariance matrix of the baseband signal in an initial state without interference suppression;
the calculating module is used for processing the estimated value of the covariance matrix in the initial state by adopting a multiple signal classification algorithm through the mathematical relationship between the direction vector of the navigation signal and the direction vector of the interference signal so as to construct a spectrum function;
the control module is used for performing space domain expansion and null depth control on the spectrum function according to a windowing principle, and performing reconstruction processing on the covariance matrix in the initial state by utilizing the space domain expansion and null depth control result to obtain a preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression;
and the determining module is used for obtaining the null depth and the null width of the uniform circular array in the interference direction according to the solution of the minimum variance undistorted response based on the preprocessing value of the covariance matrix of the baseband signal in the current state without interference suppression so as to determine the interference suppression degree.
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