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CN104868946B - The disturbance restraining method of adaptive weighted Subarray mixing MIMO phased array systems - Google Patents

The disturbance restraining method of adaptive weighted Subarray mixing MIMO phased array systems Download PDF

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CN104868946B
CN104868946B CN201510324632.8A CN201510324632A CN104868946B CN 104868946 B CN104868946 B CN 104868946B CN 201510324632 A CN201510324632 A CN 201510324632A CN 104868946 B CN104868946 B CN 104868946B
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CN104868946A (en
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胡航
宋柯
牟成虎
李绍滨
郭林丽
李毓琦
狄晶莹
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Harbin Institute of Technology Shenzhen
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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Abstract

自适应加权的子阵级混合MIMO‑相控阵系统的干扰抑制方法，属于子阵级混合MIMO‑相控阵系统领域。它是为了解决子阵级混合MIMO‑相控阵系统的自适应干扰抑制的问题。本发明所述的自适应加权的子阵级混合MIMO‑相控阵系统的干扰抑制方法，首先建立子阵级混合MIMO‑相控阵系统，利用虚拟阵列的导向向量和虚拟阵列输出的干扰加噪声协方差矩阵的估值获得子阵级混合MIMO‑相控阵系统的自适应权值，并对子阵级混合MIMO‑相控阵系统的虚拟阵列输出的干扰加噪声信号进行加权，进而实现子阵级混合MIMO‑相控阵系统的自适应干扰抑制。

The invention discloses an interference suppression method for an adaptive weighted sub-array-level hybrid MIMO-phased array system, belonging to the field of sub-array-level hybrid MIMO-phased array systems. It is designed to address the problem of adaptive interference suppression for subarray-level hybrid MIMO‑phased array systems. The interference suppression method of the self-adaptive weighted sub-array-level hybrid MIMO-phased array system of the present invention first establishes the sub-array-level hybrid MIMO-phased array system, and utilizes the steering vector of the virtual array and the interference summing outputted by the virtual array The estimation of the noise covariance matrix obtains the adaptive weight of the subarray-level hybrid MIMO-phased array system, and weights the interference plus noise signal output by the virtual array of the sub-array-level hybrid MIMO-phased array system, thereby realizing Adaptive interference suppression for subarray-level hybrid MIMO‑phased array systems.

Description

Interference suppression method of adaptive weighted subarray level hybrid MIMO-phased array system
Technical Field
The invention belongs to the field of subarray level mixed MIMO-phased array systems.
Background
The subarray-level hybrid MIMO-phased array system is a new system which combines a MIMO (Multiple-Input Multiple-Output) system and a phased array system, and can overcome some limitations of the existing MIMO system and phased array system.
MIMO is a new system and is a very active research hotspot at home and abroad at present. Its advantages are generally compared to conventional phased array systems. Compared with a phased array system, the MIMO system has great advantages, such as better detection performance, higher directional resolution and estimation precision, stronger robustness under electronic countermeasure and multipath environment, and the like.
However, MIMO systems also have some limitations compared to phased array systems, including: 1. each antenna array element transmits orthogonal signals without coherent processing gain of a phased array system, thereby generating beam shape loss and reducing the performance when the scattering sectional area of a target is faded. 2. Signal-to-noise ratio (SNR) loss is generated, which affects target detection and parameter estimation accuracy, etc., and although such SNR loss of the MIMO system can be compensated by increasing the accumulation time, this method has a great limitation due to the limited coherent processing time and propagation path loss, etc. in the application. 3. A modern electronic system often comprises hundreds to thousands of antenna array elements, and if a MIMO system is directly applied, many independent transmitting signals are needed and thousands of digital channels are adopted at a receiving end, which cannot bear the hardware cost and the arithmetic operation cost; and in order to obtain a proper transmitting signal, an optimization problem with huge dimensions needs to be solved.
The subarray level mixed MIMO-phased array system overcomes the limitation of the MIMO system, and can effectively reduce hardware cost and operation cost. It also has the capability of coherent processing gain of a phased array system while maintaining all the advantages of a MIMO system. However, the subarray level hybrid MIMO-phased array system has just started to be researched, and many problems need to be solved, such as the problem of adaptive interference suppression.
Disclosure of Invention
The invention provides an interference suppression method of a sub-array level mixed MIMO-phased array system with self-adaptive weighting, aiming at solving the problem of self-adaptive interference suppression of the sub-array level mixed MIMO-phased array system.
The interference suppression method of the adaptive weighted subarray level mixed MIMO-phased array system comprises the following steps:
establishing a subarray-level hybrid MIMO-phased array system, wherein the system comprises a transmitting array and a receiving array, the transmitting array and the receiving array are completely identical in structure, the receiving array comprises N array elements, the N array elements are divided into L subarrays, the distance between every two adjacent array elements is half-working wavelength, interference and noise signals output by each subarray are subjected to matched filtering through L matched filters, and both N and L are positive integers;
setting array element level steering vector of receiving array asConverting the sub-array of the array into T, and utilizing the sub-array conversion matrix T of the array and the array element level guide vector of the receiving arrayObtaining steering vectors for a receive arraySteering vectors from a receiving arrayObtaining steering vectors for virtual arraysWhere theta represents the pitch angle,representing an azimuth;
sampling the interference and noise signals output by the virtual array for K times, and setting the interference and noise vector output by the virtual array obtained by sampling for the K time as yV(k) Using the interference-plus-noise vector y output by the virtual arrayV(k) Estimating the interference-plus-noise covariance matrix of the virtual array output to obtain an estimate of the interference-plus-noise covariance matrix of the virtual array outputWherein K is more than or equal to 1 and less than or equal to K;
steering vectors using virtual arraysEstimation of interference-plus-noise covariance matrix from virtual array outputObtaining a self-adaptive weight w of a subarray level mixed MIMO-phased array system;
and weighting the interference and noise signals output by the virtual array of the subarray level hybrid MIMO-phased array by using the self-adaptive weight w, thereby realizing the self-adaptive interference suppression of the subarray level hybrid MIMO-phased array system.
The interference suppression method of the adaptive weighted subarray level mixed MIMO-phased array system can adaptively suppress interference at the receiving end of the subarray level mixed MIMO-phased array and enable the signal-to-interference-and-noise ratio output by the system to be maximum.
Drawings
FIG. 1 is a diagram of a subarray division of an array in a subarray level hybrid MIMO-phased array system;
fig. 2 is a schematic structural diagram of a receiving end in a sub-array level hybrid MIMO-phased array system;
fig. 3 is a flowchart of a method for obtaining adaptive weights for a sub-array level hybrid MIMO-phased array system.
Detailed Description
The first embodiment is as follows: the interference suppression method of the adaptive weighted sub-array level hybrid MIMO-phased array system according to the present embodiment will be described in detail with reference to fig. 1, 2 and 3, and the method includes:
establishing a subarray-level hybrid MIMO-phased array system, wherein the system comprises a transmitting array and a receiving array, the transmitting array and the receiving array are completely identical in structure, the receiving array comprises N array elements, the N array elements are divided into L subarrays, the distance between every two adjacent array elements is half-working wavelength, interference and noise signals output by each subarray are subjected to matched filtering through L matched filters, and both N and L are positive integers;
setting array element level steering vector of receiving array asConverting the sub-array of the array into T, and utilizing the sub-array conversion matrix T of the array and the array element level guide vector of the receiving arrayObtaining steering vectors for a receive arraySteering vectors from a receiving arrayObtaining steering vectors for virtual arraysWhere theta represents the pitch angle,representing an azimuth;
sampling the interference and noise signals output by the virtual array for K times, and setting the interference and noise vector output by the virtual array obtained by sampling for the K time as yV(k) Using the interference-plus-noise vector y output by the virtual arrayV(k) Estimating the interference-plus-noise covariance matrix of the virtual array output to obtain an estimate of the interference-plus-noise covariance matrix of the virtual array outputWherein K is more than or equal to 1 and less than or equal to K;
steering vectors using virtual arraysEstimation of interference-plus-noise covariance matrix from virtual array outputObtaining a self-adaptive weight w of a subarray level mixed MIMO-phased array system;
and weighting the interference and noise signals output by the virtual array of the subarray level hybrid MIMO-phased array by using the self-adaptive weight w, thereby realizing the self-adaptive interference suppression of the subarray level hybrid MIMO-phased array system.
In the sub-array level hybrid MIMO-phased array system in the present embodiment, a planar phased array is used for the array, and transmission/reception is shared. The array comprises N array elements, the spacing between the array elements is half-wavelength lambda/2, the array adopts a subarray structure, the array is divided into L subarrays, the transmitting array and the receiving array have the same subarray structure, and a subarray division structure of the array in a subarray-level hybrid MIMO-phased array system is shown in figure 1. In the present embodiment, the array and the sub-array are arbitrary, and fig. 1 illustrates an example in which both the array and the sub-array are rectangular arrays.
In the transmitting array of the subarray level mixed MIMO-phased array, coherent signals are transmitted in each subarray and work in a phased array mode; and orthogonal signals are transmitted among different sub-arrays, and the MIMO mode is operated.
At a receiving end of the subarray level mixed MIMO-phased array, a space-domain self-adaptive interference suppression technology is applied, so that a directional diagram forms null in an interference direction, and interference is suppressed in a self-adaptive mode. The receiving array comprises a phase shifter for controlling the beam direction. The output signals of the elements are weighted (e.g., Taylor weighted) for suppressing the sidelobe levels of the receive pattern. In the receiving array, adjacent array elements form a plurality of sub-arrays (the total number of the sub-arrays is L) through a sub-array synthesis network. The output of each subarray is passed through a matched filter bank for matched filtering. Since there are L transmit signals (the system transmit end has L sub-arrays, each transmitting an orthogonal signal), each matched filter bank has L matched filters. Due to the function of the matched filter bank, a virtual array is formed at the receiving end of the system.
To adaptively suppress the interference, the interference plus noise signals output by the matched filters are weighted, i.e., the interference plus noise signals output by the virtual array, so that L is needed in total2And (4) self-adaptive weight. In this embodiment modeThe adaptive weight value adopts an LCMV (Linear Constrained Minimum Variance) criterion, namely, the signal-to-interference-and-noise ratio (the ratio of signal to interference plus noise power) output by the system is maximized, namely, the optimal adaptive interference suppression performance is achieved.
The second embodiment is as follows: in this embodiment, the interference suppression method of the adaptive weighted sub-array level hybrid MIMO-phased array system described in the first embodiment is further described, in this embodiment, the array element level steering vector of the receiving array isThe obtaining method comprises the following steps:
let 1 st array element in the receiving array be located at the origin of coordinates, i.e. the reference array element, and the coordinates of the nth array element be (xn, yn), where N is 1, …, N, letProjection of unit vector of direction in x direction Projection of unit vector of direction in y directionSetting the phase shift value of the nth array elementComprises the following steps:
in the formula, λ is the working wavelength, the array element-level steering vector of the receiving array is:
the range of N is more than or equal to 1 and less than or equal to N.
In this embodiment, the array element-level steering vector of the receiving arrayIs an N-dimensional column vector in whichTIndicating transposition.
The third concrete implementation mode: in this embodiment, the interference suppression method of the adaptive weighted sub-array level hybrid MIMO-phased array system according to the first embodiment is further explained, and in this embodiment, the steering vector of the receiving array is obtained according to the following formula
In the present embodiment, the subarray transformation matrix T of the array is an N × L-dimensional matrix, which reflects the characteristics of the subarray and is determined by the subarray structure and the phase shift and amplitude weighting values of each array elementIs an L-dimensional column vector.
The fourth concrete implementation mode: in this embodiment, the interference suppression method of the adaptive weighted sub-array level hybrid MIMO-phased array system according to the first embodiment is further explained, and in this embodiment, the steering vector of the virtual array is obtained according to the following formula
Wherein q is [1,1, …,1 ]]T L×1Is an L-dimensional column vector, each element value is 1,representing the Kronecker product.
In the present embodiment, q is [1,1, …,1 ]]T L×1Is an L-dimensional column vector, andrepresents the Kronecker product (tensor product), and thusIs a L2A column vector of dimensions.
The fifth concrete implementation mode: in this embodiment, the interference suppression method of the adaptive weighted sub-array level hybrid MIMO-phased array system described in the first embodiment is further described, and in this embodiment, the obtained interference plus noise vector output by the virtual array is yV(k) The method comprises the following steps:
setting the interference plus noise vector formed by the interference plus noise output by all array elements as yele(k) Using the interference plus noise vector yele(k) The interference-plus-noise vector of the obtained subarray output is y (k) ═ THyele(k) Wherein (K is more than or equal to 1 and less than or equal to K);
let the unit function response of each matched filter be h1(k)，h2(k)，...，hL(k) Where the unit function response of the ith matched filter is hl(k)：
Wherein L is more than or equal to 1 and less than or equal to L, fl(k) For the transmit signal of the first sub-array of the transmit array, k0Is a constant and is a positive integer,*representing taking conjugation;
let the output signal of the first sub-array in the receiving array be yl(k) The output y after passing the first matched filterV_ll(k) Comprises the following steps:
yV_ll(k)＝hl(k)οyl(k)
using y as interference and noise vector output by virtual array obtained by sampling at kth timeV(k) Denotes o denotes convolution operation.
Signal y of matched filter output (i.e. virtual array output) obtained from the k-th samplingV_ll(k) Has a total of L2L is more than or equal to 1 and less than or equal to L, and L is more than or equal to 1 and less than or equal to L, so that an interference and noise vector y output by the virtual array is formedV(k)。
In this embodiment, the output signal of each sub-array passes through one matched filter bank, as shown in fig. 2, the output signal of the matched filter is the output of the virtual array, and the output of each sub-array passes through L matched filters.
Since there are N array elements in total, yele(k) Is an N-dimensional column vector and y (k) is an L-dimensional column vector.
The above interference plus noise vector is yele(k) And interference and noise vectors formed by interference and noise values output by the array elements corresponding to the k-th sampling.
The sixth specific implementation mode: this embodiment is a further description of the interference suppression method of the adaptive weighted sub-array level hybrid MIMO-phased array system described in the first embodiment, and this embodiment is described belowIn the method, an estimate of an interference-plus-noise covariance matrix of the virtual array output is obtained using the following equation
In this embodiment, received data is sampled K times, and y obtained by each sampling is usedV(k) Estimating the interference and noise covariance matrix output by the virtual array to obtainK is the number of samples taken,Hrepresents a conjugate transpose, and thusIs a L2×L2A square matrix of dimensions.
The seventh embodiment: in this embodiment, the interference suppression method for a sub-array level hybrid MIMO-phased array system with adaptive weighting according to the first embodiment is further described, and in this embodiment, the adaptive weight w of the sub-array level hybrid MIMO-phased array system is obtained by using the following formula:
where μ is a constant, let the beam of the array be directed asThenSteering vectors for the virtual array at the beam pointing direction.
The optimal adaptive weight of the subarray level is L2A column vector of dimensions, obtained based on LCMV criteria; steering vectors of virtual arrays at beam pointingIs also L2A column vector of dimensions.

Claims (1)

1.自适应加权的子阵级混合MIMO-相控阵系统的干扰抑制方法，其特征在于，该方法为：1. The interference suppression method of the sub-array level hybrid MIMO-phased array system of self-adaptive weighting, it is characterized in that, this method is: 建立子阵级混合MIMO-相控阵系统，该系统中包括发射阵和接收阵，且发射阵和接收阵的结构完全相同，接收阵包括N个阵元，该N个阵元划分为L个子阵，相邻两个阵元的距离均为半工作波长，且每个子阵的输出的干扰加噪声信号均通过L个匹配滤波器进行匹配滤波，N和L均为正整数；A sub-array-level hybrid MIMO-phased array system is established. The system includes a transmitting array and a receiving array, and the structures of the transmitting array and the receiving array are exactly the same. The receiving array includes N array elements, and the N array elements are divided into L sub-arrays. The distance between two adjacent array elements is half the working wavelength, and the interference and noise signals output by each subarray are matched and filtered by L matched filters, and N and L are both positive integers; 设接收阵的阵元级导向向量为阵列的子阵转换矩阵为T，利用阵列的子阵转换矩阵T和接收阵的阵元级导向向量获得接收阵的导向向量根据接收阵的导向向量获得虚拟阵列的导向向量其中θ表示俯仰角，表示方位角；Let the element-level steering vector of the receiving array be The sub-array transformation matrix of the array is T, using the sub-array transformation matrix T of the array and the element-level steering vector of the receiving array Get the steering vector of the receiving array According to the steering vector of the receiving array get steering vector for virtual array where θ represents the pitch angle, Indicates the azimuth; 对虚拟阵列输出的干扰加噪声信号进行K次采样，设第k次采样获得的虚拟阵列输出的干扰加噪声向量为yV(k)，利用该虚拟阵列输出的干扰加噪声向量yV(k)对虚拟阵输出的干扰加噪声协方差矩阵进行估计，获得虚拟阵列输出的干扰加噪声协方差矩阵的估值其中1≤k≤K；The interference and noise signal output by the virtual array is sampled K times, and the interference and noise vector of the virtual array output obtained by the kth sampling is set to be y V (k), and the interference and noise vector y V (k) of the virtual array output is used ) Estimate the interference-plus-noise covariance matrix output by the virtual array, and obtain the estimate of the interference-plus-noise covariance matrix output by the virtual array where 1≤k≤K; 利用虚拟阵列的导向向量和虚拟阵列输出的干扰加噪声协方差矩阵的估值获得子阵级混合MIMO-相控阵系统的自适应权值w；Steering vectors using virtual arrays and the estimate of the interference-plus-noise covariance matrix output by the virtual array Obtain the adaptive weight w of the subarray-level hybrid MIMO-phased array system; 利用自适应权值w对子阵级混合MIMO-相控阵的虚拟阵列输出的干扰加噪声信号进行加权，进而实现子阵级混合MIMO-相控阵系统的自适应干扰抑制；Using the adaptive weight w to weight the interference plus noise signal output by the virtual array of the sub-array-level hybrid MIMO-phased array, and then realize the adaptive interference suppression of the sub-array-level hybrid MIMO-phased array system; 接收阵的阵元级导向向量为的获得方法为：The element-level steering vector of the receiving array is The method of obtaining is: 设接收阵中第1个阵元位于坐标原点，即参考阵元，第n个阵元的坐标为(xn，yn)，其中n＝1,…,N，令方向的单位向量在x方向的投影 方向的单位向量在y方向的投影设第n个阵元的移相值为：Assume that the first array element in the receiving array is located at the origin of the coordinates, that is, the reference array element, and the coordinates of the nth array element are (x n , y n ), where n=1,...,N, let The projection of the unit vector of the direction in the x direction The projection of the unit vector of the direction in the y direction Set the phase shift value of the nth array element for: 式中，λ为工作波长，则接收阵的阵元级导向向量为：In the formula, λ is the working wavelength, then the element-level steering vector of the receiving array is: 上述n的范围为1≤n≤N；The range of above n is 1≤n≤N; 根据下式获得接收阵的导向向量 The steering vector of the receiving array is obtained according to the following formula 根据下式获得虚拟阵列的导向向量 The steering vector of the virtual array is obtained according to 式中，q＝[1,1,…,1]T L×1为一个L维列向量，各元素值均为1，表示Kronecker积；In the formula, q=[1,1,…,1] T L×1 is an L-dimensional column vector, each element value is 1, Indicates the Kronecker product; 获得的虚拟阵列输出的干扰加噪声向量为yV(k)的方法为：The method of obtaining the interference plus noise vector of the virtual array output as y V (k) is: 设所有阵元输出的干扰加噪声构成的干扰加噪声向量为yele(k)，利用干扰加噪声向量yele(k)获得的子阵输出的干扰加噪声向量为y(k)＝THyele(k)，其中1≤k≤K；Assume that the interference plus noise vector formed by the interference plus noise output by all array elements is y ele (k), and the interference plus noise vector of the subarray output obtained by using the interference plus noise vector y ele (k) is y(k)=T H y ele (k), where 1≤k≤K; 设各匹配滤波器的单位函数响应分别为h1(k)，h2(k)，...，hL(k)，其中第l个匹配滤波器的单位函数响应为hl(k)：Let the unit function response of each matched filter be h 1 (k), h 2 (k), ..., h L (k), where the unit function response of the l-th matched filter is h l (k) : hl(k)＝fl *(k0-k)h l (k) = f l * (k 0 -k) 其中，1≤l≤L，fl(k)为发射阵第l个子阵的发射信号，k0为常数且为正整数,*表示取共轭；Among them, 1≤l≤L, f l (k) is the transmission signal of the lth sub-array of the transmission array, k 0 is a constant and a positive integer, and * means to take the conjugate; 设接收阵中第l个子阵的输出信号为yl(k)，则通过第l个匹配滤波器后的输出yV_ll(k)为：Suppose the output signal of the lth sub-array in the receiving array is yl(k), then the output yV_ll ( k) after passing through the lth matched filter is: 将第k次采样得到的虚拟阵列输出的干扰加噪声向量用yV(k)表示，表示卷积运算；The interference plus noise vector output by the virtual array obtained by the kth sampling is denoted by y V (k), Indicates the convolution operation; 利用下式获得虚拟阵列输出的干扰加噪声协方差矩阵的估值 An estimate of the interference-plus-noise covariance matrix output by the virtual array is obtained using <mrow> <msub> <mover> <mi>R</mi> <mo>^</mo> </mover> <mi>V</mi> </msub> <mo>=</mo> <mfrac> <mn>1</mn> <mi>K</mi> </mfrac> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </munderover> <msub> <mi>y</mi> <mi>V</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <msup> <msub> <mi>y</mi> <mi>V</mi> </msub> <mi>H</mi> </msup> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> </mrow> <mrow><msub><mover><mi>R</mi><mo>^</mo></mover><mi>V</mi></msub><mo>=</mo><mfrac><mn>1</mn><mi>K</mi></mfrac><munderover><mo>&amp;Sigma;</mo><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>y</mi><mi>V</mi></msub><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><msup><msub><mi>y</mi><mi>V</mi></msub><mi>H</mi></msup><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow> 其中，H表示共轭转置；Among them, H represents the conjugate transpose; 利用下式获得子阵级混合MIMO-相控阵系统的自适应权值w：The adaptive weight w of the subarray-level hybrid MIMO-phased array system is obtained by using the following formula: 其中，μ为常数，设阵列的波束指向为则为虚拟阵列在波束指向处的导向向量。Among them, μ is a constant, and the beam pointing of the array is set as but is the steering vector of the virtual array at the point where the beam points.
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