1. A distributed array angle measurement method for array decomposition is characterized by comprising the following steps:

step one, decomposing a distributed radar array:

the distributed radar comprises a main array and M auxiliary arrays, and the main array and the M auxiliary arrays are all in a phased array system, wherein the main array comprises N_MArray elements are arranged, and the distance between the array elements is lambda/2; the auxiliary array comprises N_AThe array elements have a spacing of lambda/2, and the number of the main array elements and the number of the auxiliary array elements satisfy an integral multiple relation, i.e. N_M＝K·N_A(ii) a λ represents a signal wavelength;

the distributed radar has (K + M) N_AAn array element is decomposed into N_BK + M sub-arrays, each sub-array comprising N_AMarking an array element level subarray as an array A and a subarray level subarray as an array B;

step two, array A single pulse angle measurement:

with the array A symmetrically placed about the antenna center, the antenna aperture should be divided into two quadrants, each quadrant having N_AThe/2 array elements are used for completing target angle measurement by the array elements in the two quadrants, so as to determine a weight vector of the array A, and the weight vector is set as W_A(θ)；

Step three, adopting array B inhibitorMaking the main lobe interfere, thereby obtaining the weight vector of the array B, and setting the weight vector as W_B(θ)；

Step four, calculating the weight vector of the distributed radar according to the following formula:

using weight vector W_C(θ) effecting measurement of the target angle.

2. The method of claim 1, wherein array B is formed by N_BA linear array of array elements, N_BThe array elements are non-uniformly arranged to form a large-caliber distributed array.

3. The distributed array angle measurement method for array decomposition of claim 1, wherein in step three, the main lobe interference is suppressed by using adaptive beamforming or principal component inversion.

4. The distributed array angle measurement method for array decomposition according to claim 3, wherein when the principal component inversion method is adopted to suppress the main lobe interference, the specific process is as follows:

in the far field, a desired signal and a disturbance are incident as plane waves with the arrival angles theta_tAnd theta_jThe snapshot data received by array B is represented as:

X＝a(θ_t)s_t+a(θ_j)s_j+n (2)

wherein X is N_BX 1 array data vector, N is N_BA x 1-dimensional array noise vector; s_tIs the complex envelope, s, of the target source_jFor the complex envelope of the interfering source, a (theta)_t),a(θ_j) Respectively are guiding vectors of a target information source and an interference information source;

the weight vector is obtained by projecting the desired signal steering vector to a space orthogonal to the interference subspace, and the projection matrix is:

p is an N_B×N_BThe diagonal of the coefficient matrix is the anti-mainlobe interference weight vector W_B(θ), echo after interference cancellation is written as:

5. the distributed array goniometry method of array decomposition as claimed in claim 1, wherein in said second step, a set of weighting vectors is selected to construct sum and difference beams, and the target angle measurement is performed by comparison.

Background

The target angle estimation has very important significance for target positioning and tracking, and is an important factor for restricting radar detection performance. The monopulse angle measurement method measures the target angle within the beam width range by using the sum beam and the difference beam which are simultaneously generated, has simple principle, is easy to realize in engineering, and is widely applied to radar systems.

With the continuous development of electronic interference technology, radar target detection environment becomes more and more complex, the self-adaptive monopulse angle measurement method effectively combines the self-adaptive beam forming technology and the monopulse angle measurement method, when a target is covered by an interference signal, firstly, the self-adaptive beam forming technology is adopted to effectively restrain the interference signal, and then, the monopulse angle measurement method is adopted to measure the target angle. When the interference signal is located at the radar side lobe position, the method has good performance, however, when the interference signal is located at the radar main lobe position, the adaptive beam forming can cause serious loss of target echo energy while canceling interference, and target detection cannot be completed.

Therefore, aiming at the scene of main lobe interference, an auxiliary receiving unit can be added around the main radar to form a distributed array, and the performance of the distributed array is equivalent to that of a large-aperture radar by performing signal-level fusion processing on a plurality of small-aperture unit radars. By means of the advantage of high spatial resolution of the large-aperture array, interference of a main lobe is eliminated while target echo energy is protected. However, the large aperture array has grating lobes and angular ambiguity to the detriment of angular measurement. Therefore, intensive research needs to be carried out on the target angle estimation algorithm of the distributed array under the condition of canceling the main lobe interference.

Disclosure of Invention

In view of the above, the present invention provides a distributed array angle measurement method for array decomposition, which can accurately measure a target angle while effectively suppressing main lobe interference.

A distributed array angle measurement method for array decomposition comprises the following steps:

step one, decomposing a distributed radar array:

the distributed radar comprises a main array and M auxiliary arrays, and the main array and the M auxiliary arrays are all in a phased array system, wherein the main array comprises N_MArray elements are arranged, and the distance between the array elements is lambda/2; the auxiliary array comprises N_AThe array elements have a spacing of lambda/2, and the number of the main array elements and the number of the auxiliary array elements satisfy an integral multiple relation, i.e. N_M＝K·N_A(ii) a λ represents a signal wavelength;

the distributed radar has (K + M) N_AAn array element is decomposed into N_BK + M sub-arrays, each sub-array comprising N_AMarking an array element level subarray as an array A and a subarray level subarray as an array B;

step two, array A single pulse angle measurement:

with the array A symmetrically placed about the antenna center, the antenna aperture should be divided into two quadrants, each quadrant having N_AThe/2 array elements are used for completing target angle measurement by the array elements in the two quadrants, so as to determine a weight vector of the array A, and the weight vector is set as W_A(θ)；

Step three, adopting the array B to restrain the main lobe interference, thereby obtaining a weight vector of the array B, and setting the weight vector as W_B(θ)；

Step four, calculating the weight vector of the distributed radar according to the following formula:

using weight vector W_C(θ) effecting measurement of the target angle.

Preferably, array B is composed of N_BA linear array of array elements, N_BThe array elements are non-uniformly arranged to form a large-caliber distributed array.

Preferably, in the third step, the main lobe interference is suppressed by using an adaptive beamforming or principal component inversion method.

Preferably, when the main lobe interference is suppressed by using the principal component inversion method, the specific process is as follows:

in the far field, there is a desired signal and a disturbanceIncident with plane waves and having respective arrival angles of theta_tAnd theta_jThe snapshot data received by array B is represented as:

X＝a(θ_t)s_t+a(θ_j)s_j+n (2)

wherein X is N_BX 1 array data vector, N is N_BA x 1-dimensional array noise vector; s_tIs the complex envelope, s, of the target source_jFor the complex envelope of the interfering source, a (theta)_t),a(θ_j) Respectively are guiding vectors of a target information source and an interference information source;

the weight vector is obtained by projecting the desired signal steering vector to a space orthogonal to the interference subspace, and the projection matrix is:

p is an N_B×N_BThe diagonal of the coefficient matrix is the anti-mainlobe interference weight vector W_B(θ), echo after interference cancellation is written as:

preferably, in the second step, a set of weighting vectors is selected to construct sum and difference beams, and the target angle measurement is completed through comparison.

The invention has the following beneficial effects:

the invention provides a distributed array angle measurement method for array decomposition, which decomposes an array into N based on the thought of sub-array division_BK + M sub-arrays, each sub-array comprising N_AIf the array elements are individual, the array element level subarray is marked as an array A, and the subarray level subarray is marked as an array B; a large-caliber distributed array is formed, so that interference is effectively inhibited; the target angle is accurately measured while interference is suppressed; the method is suitable for the distributed anti-interference array, is a method for accurately measuring the target angle on the premise of effectively inhibiting interference, and can effectively solve the problem that the traditional method is in the dry stateAfter interference suppression, the array and the difference directional diagram are distorted, and the angle cannot be measured.

Drawings

FIG. 1 is a schematic diagram of a distributed radar;

FIG. 2 is an exploded schematic view of a distributed radar array;

FIG. 3 is a sum and difference pattern for a first stage sub-array;

fig. 4 is a second stage sub-array adaptive interference rejection pattern;

FIG. 5 is a full array sum and difference directional diagram of a distributed array radar;

fig. 6 is a full array angular discrimination curve of the distributed array radar.

Detailed Description

The invention is described in detail below by way of example with reference to the accompanying drawings.

A distributed array angle measurement method for array decomposition comprises the following steps:

step one, distributed radar array decomposition

The distributed radar comprises a main array and M auxiliary arrays, which are all in a phased array system, wherein the main array comprises N_MArray elements are arranged, and the distance between the array elements is lambda/2; the auxiliary array comprises N_AThe array elements have the same array element spacing of lambda/2, and it is noted that the main array element number and the auxiliary array element number satisfy an integral multiple relation, namely N_M＝K·N_A. Distributed radar is shown in figure 1.λ represents a signal wavelength;

thus, distributed radars have (K + M) N in common_AThe array element can be decomposed into N based on the thought of sub-array division_BK + M sub-arrays, each sub-array comprising N_AFor each array element, the array element level sub-array is denoted as an array A, the sub-array level sub-array is denoted as an array B, and the decomposition of the array is shown in FIG. 2.

The relative position vector of array A is d_A＝[d_A(1),d_A(2),...,d_A(N_A)]^TThe relative position vector of array B is d_B＝[d_B(1),d_B(2),...,d_B(N_B)]^TThe relative position vector of the resultant array is then the two corresponding sub-arraysKronecker and, written as:

the relative steering vector of array A is a_A(theta), the relative steering vector of array B is a_B(θ), then the relative steering vector of the resultant array is the Kronecker product of the relative steering vectors of the two corresponding sub-arrays, written as:

the weight vector of array A is W_A(θ) the weight vector of array B is W_B(θ), then the weight vector of the composite array is the Kronecker product of the weight vectors of the two corresponding sub-arrays, written as

The directional diagram of the array A is F_A(θ；W_A(θ)), the directivity pattern of array B is F_B(θ；W_B(theta)), the directional diagram of the original distributed radar is the product of the directional diagrams of the two corresponding sub-arrays, written as the mixed product property of the Kronecker product

Therefore, the array decomposition of the distributed radar is realized through the steps.

And step two, measuring the angle of the array A by using a single pulse.

Suppose array A is composed of N_AThe array radar comprises a linear array formed by array elements, and in order to realize monopulse angle estimation, antenna units of the array radar are symmetrically arranged around the center of an antenna. N is a radical of_AThe antenna aperture of the element linear array should be divided into two quadrants, each quadrant having N_A2 array elements, select a groupWeighting vector w_∑，w_ΔAnd constructing a sum beam and a difference beam, and completing target angle measurement through comparison.

Step three, array B interference suppression

Array B is composed of N_BLinear array of individual array elements, N for effective suppression of array interference_BThe array elements are non-uniformly arranged to form a large-caliber distributed array. In the far field, a desired signal and a disturbance are incident as plane waves (with wavelength λ) and reach angles θ_tAnd theta_jThe snapshot data received by the array may be represented as

X＝a(θ_t)s_t+a(θ_j)s_j+n (5)

Wherein X is N_BX1 array data vector, X ═ X₁,x₂,…,x_NB]^T。[]^TRepresenting a matrix transposition, N being N_BThe x 1 array of noise vectors is then used,s_tis the complex envelope, s, of the target source_jFor the complex envelope of the interfering source, a (theta)_t),a(θ_j) Respectively, the steering vectors of the target information source and the interference information source.

Then, the main lobe interference can be suppressed by using methods of adaptive beam forming, principal component inversion and the like. The analysis is performed using principal component inversion. The basic idea of principal component inversion is to estimate the strong interference components from the array received data, then subtract these components from the original data (to suppress interference), and then perform spatial matched filtering on the remaining data vectors (with the desired signal steering vector a (θ)₀) A vector of filter weights) to obtain an array output. In other words, the weight vector is projected from the desired signal steering vector into a space (noise subspace) orthogonal to the interference subspace. Writing

X_c＝(I-a(θ_j)a^H(θ_j))X (6)

＝PX

Wherein, P ═ a (θ)_j)a^H(θ_j) Is an N_B×N_BThe coefficient matrix of (2). The output signal X obtained_cNo interfering signal is already contained.

Step four, completing target angle measurement under interference suppression

The array A obtains a single-pulse angle measurement sum and difference directional diagram, the array B obtains an interference position null directional diagram, and after the processing, the distributed radar can obtain the sum and difference directional diagram which generates the null at the interference position, the target echo energy is not lost, and the sum and difference directional diagram is not distorted. Therefore, the target angle can be measured on the premise of effectively suppressing interference.

The following gives a simulation example to which the present invention is applied, and analyzes and explains the angle measurement process.

The distributed array radar comprises a main radar and a plurality of auxiliary radars, wherein the main radar and the auxiliary radars are all in a phased array system, and the main and auxiliary radars meet two conditions:

the main array and the auxiliary array adopt the same array element interval;

the size of the main array and the size of the auxiliary array are in integral multiple relation;

thus, the distributed array can be divided into two stages according to the above analysis.

The simulation parameters are shown in the following table.

TABLE 1 simulation parameters Table

Step 1: the first-stage sub-array adopts a phase sum difference monopulse angular measurement method, and calculates sum and difference antenna directional patterns according to sum and difference beam weight vectors, as shown in fig. 3.

Step 2: the second-stage sub-array obtains the anti-interference weight vector by adopting a principal component phase cancellation method, so as to obtain a self-adaptive interference suppression directional diagram generating null at an interference position, as shown in fig. 4. The antenna pattern is somewhat cluttered due to the sparse arrangement of the array, but it is evident from the figure that deep nulls are formed at the interference locations.

And step 3: the sum and difference beam weight vectors are multiplied by the anti-interference weight vector respectively to obtain the sum and difference beam weight vectors of each array element of the distributed array radar under the anti-interference condition, so that the sum and difference directional diagrams generating the null at the interference position are calculated, as shown in fig. 5.

And 4, step 4: and constructing sum and difference beams to finish the target angle measurement of the distributed array radar under the interference, wherein the angle identifying curve is shown in fig. 6, and as can be seen from the figure, the angle identifying curve does not generate sudden change due to interference suppression, so that the target angle can be accurately measured.

In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.