A polarization sensitive array amplitude and phase correction method based on spatial spectrum estimation

Abstract

The application belongs to the technical field of polarization sensitive array amplitude-phase inconsistency correction, and particularly relates to a polarization sensitive array amplitude-phase correction method based on spatial spectrum estimation, which is a polarization sensitive array composed of linear polarization antennas with different polarization directions, uses a general polarization sensitive array signal receiving model, solves a correction matrix by traversing the frequency and direction angle coverage range of a coming wave in an external radiation source mode, is used in the estimation of the direction and polarization parameters of the coming wave based on the spatial spectrum algorithm, and has the performance of the algorithm after correction close to an ideal model, improves the estimation accuracy of the polarization parameters while improving the DOA estimation accuracy, can effectively improve the resolution of the spatial spectrum algorithm, and has universality.

Description

Technical Field

[0001] This application belongs to the field of amplitude-phase inconsistency correction technology for polarization-sensitive arrays, specifically involving a polarization-sensitive array amplitude-phase correction method based on spatial spectrum estimation. Background Technology

[0002] Array signal processing is the process of performing specific processing on spatial signals received by an array of multiple sensors at different locations to enhance useful signals of interest, suppress useless interference signals and noise, and extract useful signal features to interpret the information contained therein.

[0003] Traditional signal receiving arrays are mostly regular arrays composed of circularly polarized or linearly polarized antennas pointing in the same direction, such as uniform / non-uniform linear arrays, L-shaped arrays, cross arrays, or circular arrays. These arrays are not sensitive to the polarization characteristics of the signal and their polarization parameters cannot be estimated through signal processing. They are called scalar arrays.

[0004] The polarization state of a signal refers to the way the spatial orientation of the electric field at any point in the propagation space changes with time. It can be described by the shape and rotation of the spatial trajectory formed by the endpoints of the electric field vector as they change over time. Estimating the signal polarization parameters is of great significance for receiving arrays, mainly in the following two aspects:

[0005] 1) It enables the receiving array to have target resolution and identification functions based on signal polarization characteristics;

[0006] 2) The anti-interference capability of the array can be improved by polarization domain filtering.

[0007] To obtain more complete signal characteristic parameters, it is first necessary to construct an array sensitive to signal polarization characteristics. An array consisting of multiple linearly polarized antennas with different polarization orientations, where the array elements are positioned differently in space, is a polarization-sensitive array. This type of array is sensitive to the polarization characteristics of the signal and can be used to estimate its polarization parameters; it is called a vector array, such as... Figure 1 As shown.

[0008] The general polarization-sensitive array signal receiving model is designed as follows:

[0009] Suppose that M uncorrelated narrowband far-field signals are incident simultaneously on an array consisting of N linearly polarized antenna elements, each with distinct element positions in space. Considering the array receiver's thermal noise T, the expression for the received signal X is:

[0010] X = AS + T (1)

[0011] The signal matrix in the above formula It can be represented as:

[0012]

[0013] With (α) m ,β m ,γ m ,η m ) represents the incident azimuth angle, elevation angle, polarization auxiliary angle, and polarization phase difference angle of the m-th signal, where α m ∈[0,2π],β m ∈[0,π / 2], γ m ∈[0,π / 2], η m ∈[-π,π], m=1,2,…M;

[0014] In formula (1) The joint manifold matrix of the polarization domain and the spatial domain can be represented as:

[0015]

[0016] in,

[0017]

[0018]

[0019]

[0020] For a linearly polarized sensitive array, the array elements are displayed in dipole form, and the position of the nth element in the array relative to the origin is (x...). n y n z n In equation (4), the spatial phase delay of the m-th signal received by the n-th array element relative to the origin is... for:

[0021]

[0022] Ideally, the output electrical signal of a dipole antenna is proportional to the electric field component parallel to it; that is, the polarization sensitivity angle depends only on the polarization direction of the array elements. Each array element is a linearly polarized antenna, and the electromagnetic wave that the nth array element can sense is E. x and E y and E z The combination It can be represented as:

[0023] r pn =[cosφ n cosθ n sinφ n cosθ n sinθ n (n = 1, 2, ... N) (6)

[0024] in,

[0025] φ n θ n Represents the polarization matching angle of the nth array element, such as Figure 2 As shown;

[0026] Similarly, since each array element can detect E x and E y and E z The combination Represented as:

[0027]

[0028] And there are

[0029] In summary, for polarization-sensitive arrays, the polarization-spatial joint manifold matrix... for:

[0030]

[0031] in,

[0032] It is the spatial manifold matrix;

[0033] This is the polarization matching matrix;

[0034] The polarization-spatial steering matrix;

[0035] And there are

[0036] a pm =w m ×p m (9)

[0037] From equation (8), it can be seen that when the polarization matching angle φ of each element in the array is... n With θ n At the same time, the values ​​of the polarization matching matrix A are the same in the dimension of the number of array elements N. For the polarization-spatial joint manifold matrix B, it is equivalent to directly applying the values ​​of the spatial manifold matrix A. s Multiplying the array elements by an N×M coefficient matrix where all column vectors have identical elements gives the polarization matching value for different incoming signals. In this case, the electromagnetic field components of the same incident signal received by the array are completely identical, and the polarization matching degree is the same. The array can be considered to be polarization insensitive. Thus, a scalar array is actually a degenerate form of a polarization-sensitive array, where the random pointing angles of the array elements become uniform. Only the phase difference caused by the spacing between the array elements can be used to estimate the direction of arrival (DOA) of the signal, and the polarization parameters of the signal cannot be estimated.

[0038] Compared to the spatial manifold matrix of a scalar array, the polarization-spatial joint manifold matrix of a polarization-sensitive array is more complex, making signal parameter estimation more difficult.

[0039] Accurate estimation of signal characteristic parameters is one of the core tasks of array receivers, and the direction of arrival and polarization characteristics are important parameters to be estimated.

[0040] The basis of polarization characteristic parameter estimation is the accurate estimation and effective resolution of multiple incoming signal directions by the array receiver. Specific methods include amplitude comparison, phase comparison, amplitude and phase comparison, time difference method, and spatial spectrum method. Among them, the spatial spectrum method generally has the advantages of high direction finding accuracy and the ability to simultaneously resolve multiple signals of the same frequency. It is the main development trend of future direction finding technology. In order to meet the requirements of modern advanced array receivers for the accuracy of incoming signal angle, polarization parameter estimation, and angle resolution, it is necessary to adopt a spatial spectrum estimation algorithm based on polarization sensitive array.

[0041] MUSIC, a multi-signal classification algorithm with high accuracy and high resolution, is the most representative spatial spectrum estimation algorithm. This algorithm is essentially a method of parameter estimation using the orthogonality principle of noise subspace and signal subspace, and belongs to the high-resolution parameter estimation algorithm of asymptotic unbiased estimation.

[0042] CN 110488097 A presents a method for solving polarization parameters based on a linearly polarized platform array, which proposes a MUSIC algorithm for the signal DOA and polarization parameters of a polarization-sensitive array. This algorithm separately estimates the signal DOA and polarization parameters, and estimates the signal DOA through a two-dimensional spectral peak search. Based on the DOA estimation result and the corresponding formula, the closed-mode solution of the incoming wave polarization parameters is achieved. However, this type of method uses the assumption of array element isotropy in the formula derivation, and in practical applications, it is necessary to obtain accurate amplitude, phase, and frequency information of the incoming wave signal. The amplitude-phase inconsistency error introduced by the antenna array and channel will cause the actual polarization domain-spatial joint manifold matrix to be inconsistent with the theoretical model. In practice, this will lead to a sharp decline in the direction-finding performance of the algorithm, or even complete failure.

[0043] The errors in antenna array signal reception mainly come from two sources: amplitude-phase inconsistency errors independent of the direction of arrival, and amplitude-phase inconsistency errors related to the direction of arrival. Amplitude-phase inconsistency errors independent of the direction of arrival are typically caused by variations in the performance of components, connectors, and RF cables within the RF front-end channel, as well as digital devices within the receiving equipment, due to changes in ambient temperature and vibration. Amplitude-phase inconsistencies related to the direction of arrival are usually caused by a combination of factors, including antenna pattern inconsistencies, inter-antenna coupling, antenna manufacturing tolerances, antenna installation environment, and installation position errors. Since actual amplitude-phase inconsistency errors are caused by a combination of these factors, it is difficult to fully describe them with a single mathematical model. Therefore, to improve signal processing performance, effective corrections need to be applied to each error source separately.

[0044] CN 109782217 A, a method and apparatus for calibrating the calibration values ​​of an airborne interferometer, points out that for amplitude-phase inconsistency errors that are independent of the direction of arrival, dynamic correction can be performed by a timing or real-time correction signal source built into the radio frequency front end.

[0045] CN 112448774 A self-test method for a broadband radio frequency receiving and processing system based on external radiation signals points out that for amplitude-phase inconsistency errors related to the direction of arrival, static correction is usually achieved by using an external radiation source. That is, in a microwave anechoic chamber, by setting different radiation source frequencies and turntable angles, all frequency and angle ranges are traversed, and finally all the received data is processed, and a corresponding correction table is formed according to the required standards and data formats, and stored in the corresponding storage module.

[0046] CN 111190135 A A calibration method applicable to arbitrary arrays introduces an amplitude-phase inconsistency correction method. For spatial spectrum algorithms, a combination of dynamic and static corrections can be used to perform spectral peak search using the updated steering vector after calibration, thereby improving the angle resolution and direction finding accuracy of the algorithm. However, this calibration method is based on traditional scalar arrays, and its signal receiving model is different from that of vector arrays, so it is not suitable for polarization-sensitive arrays.

[0047] This application is made in view of the aforementioned technical deficiencies.

[0048] It should be noted that the above background information is only used to assist in understanding the inventive concept and technical solution of this invention, and it does not necessarily belong to the prior art of this patent application. In the absence of clear evidence that the above information was disclosed on the filing date of this application, the above background information should not be used to evaluate the novelty and inventiveness of this application. Summary of the Invention

[0049] The purpose of this application is to provide a polarization-sensitive array amplitude and phase correction method based on spatial spectrum estimation to overcome or mitigate at least one of the known technical defects.

[0050] The technical solution of this application is:

[0051] A polarization-sensitive array amplitude and phase correction method based on spatial spectrum estimation includes:

[0052] Constructing the data autocorrelation matrix: In a microwave anechoic chamber, a polarization-sensitive array is interconnected with an RF front-end and a digital receiver, placed on a two-dimensional turntable. Correction signals are emitted through an external radiation source at the corresponding carrier frequency and direction of arrival. The digital receiver digitally samples and obtains multiple snapshots of complex signal data stream X, thus yielding the data autocorrelation matrix. Where snap represents the number of snapshots;

[0053] Calculation of the polarization-spatial steering matrix: Using the polarization and directional parameters of the external radiating source antenna, the polarization-spatial steering matrix is ​​calculated.

[0054] Calculate the correction matrix: using the polarization matching matrix determined by the polarization direction of the linearly polarized antenna. Polarization domain-spatial steering matrix A p Multiplication yields vectors Where N is the number of array elements;

[0055] Using the data autocorrelation matrix R x Calculate the value of the nth element in the correction matrix. By iterating through the range of signal carrier frequencies and direction parameters, a complete correction matrix can be obtained. Where, n f n α n β The specific values ​​are obtained by dividing the difference between the upper and lower limits of the carrier frequency, azimuth angle, and elevation angle by the corresponding step size;

[0056] Calculate the spatial spectral function of the rank-deficient MUSIC algorithm:

[0057]

[0058]

[0059] in,

[0060] w is a function of the incident azimuth and elevation angles of the external radiation source signal.

[0061] According to at least one embodiment of this application, in the above-described polarization-sensitive array amplitude and phase correction method based on spatial spectrum estimation,

[0062] in,

[0063] The incident azimuth angle of the external radiation source signal α∈[0, 2π].

[0064] β∈[0,π / 2] is the incident elevation angle of the external radiation source signal.

[0065] This application has at least the following beneficial technical effects:

[0066] This paper presents a polarization-sensitive array amplitude and phase correction method based on spatial spectrum estimation. The method consists of a polarization-sensitive array composed of linearly polarized antennas with different polarization directions. Using a general polarization-sensitive array signal reception model, the correction matrix is ​​solved by traversing the coverage range of the incoming wave frequency and azimuth angle through an external radiation source. This correction matrix is ​​used in the estimation of the incoming wave direction and polarization parameters based on the spatial spectrum algorithm. After correction, the performance of the algorithm approaches that of the ideal model. It improves the accuracy of DOA estimation and the accuracy of polarization parameter estimation, effectively enhances the resolution of the spatial spectrum algorithm, and has universality. Attached Figure Description

[0067] Figure 1 This is a schematic diagram of a vector array;

[0068] Figure 2 This is a schematic diagram of the polarization matching angle of a linearly polarized array element;

[0069] Figure 3 This is a schematic diagram of the amplitude and phase correction method for polarization-sensitive arrays based on spatial spectrum estimation provided in the embodiments of this application;

[0070] Figure 4 This is a schematic diagram of the polarization-sensitive array provided in an embodiment of this application;

[0071] Figure 5 This is a schematic diagram of the spatial spectrum simulation results before correction provided in the embodiments of this application;

[0072] Figure 6 This is a schematic diagram of the simulation results of the corrected spatial spectrum provided in the embodiments of this application.

[0073] To better illustrate this embodiment, some parts in the accompanying drawings may be omitted, enlarged, or reduced, and do not represent the actual size of the product. Furthermore, the accompanying drawings are for illustrative purposes only and should not be construed as limiting this patent. Detailed Implementation

[0074] To make the technical solution and advantages of this application clearer, the technical solution of this application will be described in a clearer and more complete manner below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only some embodiments of this application, and are only used to explain this application, not to limit this application. It should be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings. Other related parts can be referred to the general design. In the absence of conflict, the embodiments and technical features in the embodiments of this application can be combined with each other to obtain new embodiments.

[0075] Furthermore, unless otherwise defined, the technical or scientific terms used in this application description shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "upper," "lower," "left," "right," "center," "vertical," "horizontal," "inner," and "outer," etc., used in this application description to indicate relative direction or positional relationship are used only to indicate relative orientation or positional relationship, and do not imply that the device or component must have a specific orientation, or be constructed and operated in a specific orientation. When the absolute position of the described object changes, its relative positional relationship may also change accordingly, and therefore should not be construed as a limitation on this application. The terms "first," "second," "third," and similar terms used in this application description are used only for descriptive purposes to distinguish different components, and should not be construed as indicating or implying relative importance. The terms "a," "one," or "the," etc., used in this application description should not be construed as an absolute limitation on quantity, but should be construed as indicating the existence of at least one. The terms "including," "comprising," etc., used in this application description mean that the element or object preceding the word covers the element or object listed after the word and its equivalents, without excluding other elements or objects.

[0076] Furthermore, it should be noted that, unless otherwise explicitly specified and limited, terms such as “installation,” “connection,” and “linkage” used in the description of this application should be interpreted broadly. For example, a connection can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; or it can be a connection within two components. Those skilled in the art can understand its specific meaning in this application according to the specific circumstances.

[0077] The following is in conjunction with the appendix Figures 1 to 6 This application will be described in further detail.

[0078] A polarization-sensitive array amplitude and phase correction method based on spatial spectrum estimation includes:

[0079] S1. Construct the data autocorrelation matrix

[0080] In a microwave anechoic chamber, a polarization-sensitive array is interconnected with an RF front-end and a digital receiver, and placed on a two-dimensional turntable. A correction signal is emitted through an external radiation source at a fixed carrier frequency and direction of arrival. The digital receiver digitally samples the signal to obtain a complex signal data stream X with multiple snapshots, yielding the data autocorrelation matrix.

[0081]

[0082] in,

[0083] Snap is the number of snapshots used for the signal;

[0084] S2 calculates the polarization-spatial steering matrix.

[0085] Using the polarization and directional parameters of the external radiation source antenna, the polarization-spatial steering matrix is ​​calculated using equation (9). Since the number of external radiation sources is 1, the polarization-spatial steering matrix is ​​in vector form, i.e.

[0086] S3. Calculate the correction matrix

[0087] The polarization matching matrix determined by the polarization direction of a linearly polarized antenna Polarization domain-spatial steering matrix A p Multiplication yields vectors

[0088] Using the data autocorrelation matrix R x Calculate the correction matrix The value of the nth element:

[0089]

[0090] By setting a certain frequency and angle step size, and iterating through the signal carrier frequency and directional parameter ranges respectively, a complete correction matrix can be obtained. Stored into the corresponding storage module, where n f n α n β The specific values ​​are obtained by dividing the difference between the upper and lower limits of the carrier frequency, azimuth angle, and elevation angle by the corresponding step size;

[0091] S4. Calculate the spatial spectral function of the rank-deficient MUSIC algorithm.

[0092] See CN 109782217 A A method and apparatus for calibrating calibration values ​​of an airborne interferometer, wherein the formula for calculating the rank-deficient MUSIC spatial spectrum function is as follows:

[0093]

[0094] in,

[0095] The spatial joint steering vector of the array is expressed as:

[0096]

[0097] When uncorrected, the guide vector A used s As an ideal steering vector, the existence of amplitude-phase inconsistency error leads to a deterioration in the orthogonality of the spectral function, which in turn causes the direction finding results to deteriorate or even fail.

[0098] The ideal steering vector A in equation (12) is replaced by a correction vector with the corresponding signal frequency, azimuth angle, and elevation angle. s The expression for the joint spatial guidance vector becomes:

[0099]

[0100] S5. Estimation of incoming signal direction parameters

[0101] By searching the spectral peaks, the arrival direction parameters of multiple signals can be estimated.

[0102] S6. Estimation of polarization parameters of incoming signal

[0103] See CN 109782217 A. A method and apparatus for calibrating calibration values ​​of an airborne interferometer, which calculates the rank deficiency matrix using the spatial joint steering vector corresponding to the direction parameters of the incoming wave signal. Polarization parameter estimation:

[0104]

[0105] The corresponding correction vector in the memory is obtained by using the signal carrier frequency and the estimated direction parameter information of the incoming wave signal. And use it to replace the ideal guidance vector A in the joint guidance vector of the spatial domain. s This improves the accuracy of polarization parameter estimation.

[0106] In a specific simulation example, a uniform circular array with radius R is formed by eight linearly polarized dipole antennas, such as... Figure 5 As shown, a polarization-sensitive array model is constructed, and simulation is performed using the rank-deficient MUSIC algorithm. The azimuth angle α and elevation angle β of the two signal sources are set to 182°, 16° and 179°, 19°, respectively.

[0107] Without correction using a correction matrix, the peak value of the spectral function is low, the angle estimation has some error, and it lacks the ability to distinguish between two signals. Correction using a correction matrix yields a spectral function with higher peak and angle resolution, as well as higher estimation accuracy. See details... Figure 5 , Figure 6 .

[0108] The amplitude and phase correction method for polarization-sensitive arrays based on spatial spectrum estimation provided in this application can be used to correct the amplitude and phase inconsistency error of polarization-sensitive arrays based on spatial spectrum estimation. This can significantly improve the accuracy of angle and polarization parameter estimation and angle resolution. Moreover, this correction method mainly involves iterative calculation operations, which are easy to implement using automated testing systems. It has strong practicality in practical engineering applications.

[0109] The various embodiments in the specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0110] The technical solution of this application has been described in conjunction with the preferred embodiments shown in the accompanying drawings. Those skilled in the art should understand that the scope of protection of this application is obviously not limited to these specific embodiments. Without departing from the principles of this application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of this application.

Claims

1. A polarization sensitive array amplitude and phase correction method based on spatial spectrum estimation, characterized in that, Comprising: Constructing data autocorrelation matrix: in the microwave anechoic chamber, the polarization sensitive array is interconnected with the radio frequency front end and the digital receiver, placed on the two-dimensional turntable, and the correction signal is transmitted by the external radiation source in the carrier frequency and the incoming direction; the complex signal data stream X of multiple shots is obtained by digital sampling of the digital receiver, and the data autocorrelation matrix is obtained Wherein, snap is the number of shots Computing the polarization-domain-spatial steering matrix: by the polarization parameter and the direction parameter information of the external radiation source antenna, the polarization-domain-spatial steering matrix is computed Compute the correction matrix: use the polarization matching matrix determined by the polarization direction of the linear polarization antenna Polarization-domain-spatial direction guiding matrix A p Multiply to obtain the vector Where N is the number of array elements; with the data autocorrelation matrix R x Computing the n-th element of the correction matrix Looping through the signal carrier frequency and direction parameter range to obtain the complete correction matrix where n f , n α , n β The specific values of n, n, and n are obtained by dividing the upper and lower limits of the carrier frequency, azimuth angle, and elevation angle by the step size, respectively. A spatial spectrum function of the rank-deficient MUSIC algorithm: where, w is a function of the incident azimuth and elevation angle of the external source signal.

2. The polarization-sensitive array amplitude and phase correction method based on spatial spectrum estimation according to claim 1, characterized in that, where, α∈[0, 2π] incident azimuth angle of the external source signal; β∈[0, π / 2] incident elevation angle of the external source signal.

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