Dual MIMO (Multiple Input Multiple Output) receiver combining all-digital subarray and heterogeneous mixed structure

Abstract

The invention discloses an all-digital subarray and heterogeneous mixed structure combined dual MIMO receiver, which comprises an all-digital FD subarray structure and a heterogeneous mixed H2AD structure, and is characterized in that the FD subarray structure is provided with M antennas; in the H2AD structure, the array is divided into H sub-array groups, each sub-array group comprises Kh sub-arrays, each sub-array comprises Mh antennas, h = 1, 2,..., H, M1 is not equal to M2,..., and MH, and values of M1, M2,..., and MH are co-prime. According to the invention, the H2AD-FD structure is designed by integrating the advantages of a heterogeneous mixed structure and an all-digital MIMO receiver structure, the phase ambiguity problem can be quickly eliminated, and the same advantages of high energy efficiency, low cost and low complexity are achieved; a radiation source direction rough angle pre-estimated by a full-digital MIMO receiver is used as an initial clustering center of a true solution class in a candidate solution set, so that rapid clustering of positive and false solution classes can be remarkably accelerated, false solutions in the candidate solution set can be removed, and the calculation complexity of an H2AD structure can be reduced.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a dual MIMO receiver combining a full digital subarray with a heterogeneous hybrid structure. Background Art

[0002] DOA estimation technology can improve the performance, capacity and coverage of wireless communication systems and radar systems, realize functions such as spatial separation, beamforming and anti-interference, and thus provide more reliable and efficient solutions for various application scenarios.

[0003] Fully digital (FD) massive multiple-input multiple-output (MIMO) antenna arrays have been widely used in data transmission, direction of arrival (DOA) measurement, etc. due to their excellent rate and resolution performance. However, they face two major challenges: high computational complexity and circuit cost. The hybrid analog-digital (HAD) structure can solve these two problems well, but HAD generally requires at least two time slots to eliminate phase ambiguity, which has the challenges of low efficiency or high latency. 2 The HAD structure can achieve low latency and high efficiency, but the computational complexity of this structure is high. The clustering process of true and false solutions can be accelerated by introducing a fully digital array. Therefore, it is urgent to develop a method combining a fully digital subarray with a heterogeneous hybrid structure (H 2 AD-FD) dual MIMO receiver structure. Summary of the invention

[0004] The purpose of the present invention is to provide a low-cost, low-power, low-latency and high-time-effective all-digital subarray combined with a heterogeneous hybrid structure (H 2 AD-FD) dual MIMO receiver.

[0005] The technical solution to achieve the purpose of the present invention is: a dual MIMO receiver combining a fully digital subarray with a heterogeneous hybrid structure, including a fully digital FD subarray structure and a heterogeneous hybrid H 2 AD structure, where:

[0006] The FD subarray structure has M antennas;

[0007] In H 2 In the AD structure, the array is divided into H sub-array groups, each of which has K h subarrays, each of which contains M h antennas, h = 1, 2, ..., H, M1 ≠ M2 ≠ ... ≠ M H And M1,M2,…,M H The values ​​of are mutually prime.

[0008] Furthermore, when M1=M2=…=MH When H 2 The AD structure degenerates into the isomorphic HAD structure, so the isomorphic HAD structure is H 2 A special case of the AD structure.

[0009] Furthermore, when M1=M2=…=M H =1, H 2 The AD structure further degenerates into an all-digital array, which is a special case of the homogeneous HAD structure.

[0010] Furthermore, the specific parameters of the receiver are as follows:

[0011] A far-field narrowband signal where x(t) and f c are the baseband signal and the carrier frequency respectively, t represents the time, considering the FD with M antennas, the output signal is expressed as:

[0012] y FD (t) = a FD (θ0)x(t)+w(t)(1.1)

[0013] in is the additive white Gaussian noise (AWGN) vector, is the noise variance, I is the identity matrix, a FD The vector representation of the array manifold is:

[0014]

[0015] Where d = λ / 2 represents the antenna element spacing, which is half of the wavelength λ;

[0016] In H 2 In the AD structure, a uniform linear array containing M antennas is divided into H groups, each containing N h antennas, and each group is divided into K h subarrays, each containing M h Antenna, that is In this array, M1≠M2≠…≠M H And M1, M2, ..., M are preferred. H The value of is considered a prime number;

[0017] Considering ψ h,k,m represents the phase corresponding to the simulated beamforming, then the output of the kth subarray is:

[0018]

[0019] in represents the noise of the kth subarray in the hth group, τh,k,m is the propagation delay established by the direction of the signal source relative to the array and is expressed as:

[0020]

[0021] Where τ0 represents the propagation delay from the radiation source to the reference point of the antenna array, and c represents the speed of light;

[0022] All K h The output y of the subarray h,k (t) superposition, the baseband signal vector of the hth group is expressed as:

[0023]

[0024] Among them, y h (t) is the output signal y of the kth subarray of the hth group h,k (t) vector formed by stacking; The dimension is K h ×1 additive Gaussian white noise complex vector, M h is the number of antennas contained in the h-th subarray, It is the Mth h Noise at the root antenna, (·) H represents the conjugate transpose operation, is an array manifold vector, represented as:

[0025]

[0026] And A,h Represents a block diagonal matrix:

[0027]

[0028] Among them, γ A,h,k is the kth block diagonal element:

[0029]

[0030] in, represents the phase shift of the kth subarray in the hth group; through the analog-to-digital converter ADC, y h (t) is transformed into:

[0031]

[0032] Where n = 1, 2, ..., L, L is the number of snapshots; θ0 is the ideal incident angle, a h (θ0) represents the array manifold vector of the ideal incident angle θ0, and w(n) is the noise.

[0033] Furthermore, when M1=M2=…=MH When H 2 The AD structure degenerates into the isomorphic HAD structure, and the specific parameters are as follows:

[0034] In the HAD structure, a uniform linear array containing N antennas is divided into K subarrays, each of which contains M antennas, that is, N = MK. Considering ψ h,k,m represents the phase corresponding to the simulated beamforming, then the output of the kth subarray is:

[0035]

[0036] in represents the noise in the kth subarray, τ k,m is the propagation delay established by the direction of the signal source relative to the array and is expressed as:

[0037]

[0038] Where τ0 represents the propagation delay from the radiation source to the reference point of the antenna array, and c represents the speed of light;

[0039] The output of all subarrays is represented as:

[0040]

[0041] in is the AWGN vector, is an array manifold vector, represented as:

[0042]

[0043] And A Represents a block diagonal matrix:

[0044]

[0045] Among them, γ A,k is the kth block diagonal element:

[0046]

[0047] in, represents the phase shift at the kth subarray; through the analog-to-digital converter ADC, y(t) is converted to:

[0048]

[0049] Where n = 1, 2, …, L, L is the number of snapshots; θ0 is the ideal incident angle, a(θ0) represents the array manifold vector of the ideal incident angle θ0, and w(n) is the noise.

[0050] Furthermore, when M1=M2=…=M H =1, H 2 The AD structure further degenerates into a full digital array, and the specific parameters are as follows:

[0051] In the FD structure, after passing through the parallel RF radio frequency link and analog-to-digital converter, the vector expression of the antenna subarray receiving signal is:

[0052] y(n)=a(θ0)x(n)+w(n)(1.17)

[0053] in is the AWGN vector, is an array manifold vector, represented as:

[0054]

[0055] A working method of a dual MIMO receiver combining the all-digital subarray and the heterogeneous hybrid structure as described above comprises the following steps:

[0056] Step 1: For H 2 AD structure, each subarray in the hth group is regarded as a virtual antenna, and the output vector of the subarray is determined;

[0057] Step 2: Calculate the covariance matrix of the output vector of the virtual antenna array and determine the pseudo spectrum of the virtual antenna array;

[0058] Step 3: Use the Root-MUSIC algorithm to estimate DOA.

[0059] Furthermore, the step 1 is specifically as follows:

[0060] For H 2 AD structure, each subarray in the hth group is regarded as a virtual antenna, and the simulated beamforming vector is set K h The output vector of the subarray in time slot b for:

[0061]

[0062] in, represents a series of received signals in the hth group, represents a series of noises in the h-th group, Indicates M h The array manifold vector of the root virtual antenna is defined as:

[0063]

[0064] r h(θ0) is a constant obtained by adding all elements of each subarray and is expressed as:

[0065]

[0066] Furthermore, the step 2 is specifically as follows:

[0067] The output vector of the virtual antenna array The covariance matrix R h for:

[0068]

[0069] in Expressing hope, represents the variance of the received signal, is the noise variance;

[0070] R h The eigenvalue decomposition EVD is:

[0071] R q =UΣU H =[U S U N ]Σ[U S U N ] H (1.23)

[0072] Among them U S and U N represent the signal and noise subspaces respectively;

[0073] K q ×K q The specific form of the diagonal matrix Σ is:

[0074]

[0075] The pseudo spectrum P corresponding to the virtual antenna array RM (θ) is:

[0076]

[0077] where θ represents the angle of arrival of the initial input and the spectrum peak corresponds to the desired DOA estimate.

[0078] Furthermore, the step 3 is specifically as follows:

[0079] The Root-MUSIC algorithm is used to estimate DOA, and the definition is Then the polynomial equation is expressed as:

[0080]

[0081] Where Q ij represents the element located in the i-th row and j-th column of the matrix Q, and z is a function containing θ, expressed as:

[0082]

[0083] in And f(z) has 2K h -2 roots, i.e. z i , where i = 1, 2, ..., 2K h -2, so there are multiple transmission directions, and the DOA estimation set is obtained as follows:

[0084]

[0085] Where each emission direction is:

[0086]

[0087] Among them, z i represents the i-th root of the polynomial equation (1.26);

[0088] DOA estimation of the hth array group We can select the root closest to the unit circle and further get an estimate of ξ

[0089]

[0090] Since each virtual antenna corresponds to a subarray, there is a phase ambiguity that needs to be eliminated, expressed as:

[0091]

[0092] Therefore, a h The feasible solution set of a solution is:

[0093]

[0094] in,

[0095]

[0096] Combining all H groups gives:

[0097]

[0098] where j h ∈{1,2,…,M h},M H is the number of subarray antennas in the Hth group, where H represents the number of groups. represents the candidate solution set of group H, represents the estimated value of group H, j H is the imaginary unit of group H, indicating The cyclic period index in is 2π; therefore, the candidate angle set is expressed as:

[0099]

[0100] Total candidate set include Solution, where each candidate set There is a true solution and M h -1 pseudo solution, for the FD subarray, the initial rough DOA value is estimated by the Root-MUSIC method:

[0101] y FD The covariance matrix of (n) is:

[0102]

[0103] Where E S and E N represent the signal and noise subspaces respectively, represents the signal-to-noise ratio of the received signal,

[0104] The corresponding spatial spectrum function is as follows:

[0105]

[0106] where a FD (θ) represents the array manifold vector;

[0107] By constructing 2(M-1) polynomial equations through Root-MUSIC, where M represents the number of antennas in the FD subarray, the root closest to the unit circle is the DOA estimate

[0108]

[0109] Compared with the prior art, the present invention has the following significant advantages: (1) The present invention integrates the advantages of heterogeneous hybrid structure and all-digital MIMO receiver structure to design H 2AD-FD structure, compared with the traditional hybrid structure, the proposed new structure can quickly eliminate the phase ambiguity problem and has the same advantages of high energy efficiency, low cost and low complexity; (2) Compared with the full digital MIMO structure, while having the same low latency, it has higher energy efficiency, low cost and low complexity. Therefore, the present invention is a green communication technology and is very suitable for application in the next-generation wireless communication systems such as 6G in the future; (3) The present invention uses the rough angle of the radiation source direction estimated in advance by the full digital MIMO receiver as the initial clustering center of the true solution class in the candidate solution set, which can significantly accelerate the rapid clustering of the positive and false solution classes, and remove the pseudo solutions in the candidate solution set, which can reduce H 2 Computational complexity of the AD structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0110] Figure 1 It is a structural diagram of a dual MIMO receiver combining a fully digital subarray with a heterogeneous hybrid structure according to the present invention.

[0111] Figure 2 The heterogeneous mixed structure (H 2 AD) MIMO receiver structure diagram.

[0112] Figure 3 This is a structural diagram of a traditional hybrid architecture (HAD) MIMO receiver provided by the present invention.

[0113] Figure 4 This is a structural diagram of a traditional all-digital structure (FD) MIMO receiver provided by the present invention. DETAILED DESCRIPTION

[0114] In order to make the purpose, technical scheme and advantages of the present invention more obvious, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described herein. Based on the embodiments of the present invention described in the present invention, all other embodiments obtained by those skilled in the art without creative work should fall within the protection scope of the present invention.

[0115] In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is apparent to those skilled in the art that the present invention can be implemented without one or more of these details. In other examples, in order to avoid confusion with the present invention, some technical features well known in the art are not described.

[0116] It should be understood that the present invention can be implemented in different forms and should not be interpreted as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to make the disclosure thorough and complete and to fully convey the scope of the present invention to those skilled in the art.

[0117] Combination Figure 1 to Figure 4 The present invention provides a combination of a fully digital subarray and a heterogeneous hybrid structure (H 2 The dual MIMO receiver of AD-FD is as follows:

[0118] The FD structure has M antennas. In H2AD, the array is divided into H sub-array groups, each with K h subarrays, each of which contains M h antennas. In this array, M1≠M2≠…≠M H And M1, M2, ..., M are preferred. H The values ​​of are mutually prime.

[0119] When M1=M2=…=M H When H 2 AD will degenerate into the traditional HAD structure, also known as the isomorphic HAD structure. Therefore, the traditional HAD structure can be called H 2 A special case of the AD structure.

[0120] When M1=M2=…=M H = 1, the array will further degenerate into a full digital array. Therefore, the full digital array can also be regarded as a special case of the HAD structure.

[0121] As a specific example, the FD structure has M antennas. 2 In AD, the array is divided into H sub-array groups, each with K h subarrays, each of which contains M h antennas. In this array, M1≠M2≠…≠M H And M1, M2, ..., M are preferred. H The values ​​of are mutually prime. The specific parameters of this structure are:

[0122] A far-field narrowband signal where x(t) and f c are the baseband signal and carrier frequency respectively, and t represents time. Considering the FD with M antennas, the output signal is expressed as:

[0123] y FD (t) = a FD (θ0)x(t)+w(t)(2.1)

[0124] in is the additive white Gaussian noise (AWGN) vector, is the noise variance, I is the identity matrix, a FD The array manifold vector can be expressed as:

[0125]

[0126] Where d = λ / 2 represents the antenna element spacing, which is half of the wavelength λ; 2 In the AD structure, a uniform linear array containing M antennas is divided into H groups, each containing N h antennas, and each group is divided into K h subarrays, each containing M h Antenna, that is In this array, M1≠M2≠…≠M H And M1, M2, ..., M are preferred. H The value of is considered a prime number.

[0127] Considering ψ h,k,m represents the phase corresponding to the simulated beamforming, then the output of the kth subarray is:

[0128]

[0129] in represents the noise of the kth subarray in the hth group. τ h,k,m is the propagation delay established by the direction of the signal source relative to the array and is expressed as:

[0130]

[0131] Where τ0 represents the propagation delay from the radiation source to the reference point of the antenna array, and c represents the speed of light.

[0132] All K h The output y of the subarray h,k (t) superposition, the baseband signal vector of the hth group is expressed as:

[0133]

[0134] Among them, y h (t) is the output signal y of the kth subarray of the hth group h,k (t) is a vector formed by stacking. In addition, The dimension is K h ×1 additive Gaussian white noise complex vector, M h is the number of antennas contained in the h-th subarray, It is the Mth h Noise at the root antenna, (·)H represents the conjugate transpose operation, is an array manifold vector, represented as:

[0135]

[0136] And A,h Represents a block diagonal matrix:

[0137]

[0138] Among them, γ A,h,k is the kth block diagonal element:

[0139]

[0140] in, represents the phase shift of the kth subarray in the hth group. Through the analog-to-digital converter (ADC), y h (t) is transformed into:

[0141]

[0142] Where n = 1, 2, ..., L, L is the number of snapshots. θ0 is the ideal incident angle, a h (θ0) represents the array manifold vector of the ideal incident angle θ0, and w(n) is the noise.

[0143] As a specific example, when M1=M2=…=M H When H 2 AD will degenerate into the traditional HAD structure, also known as the isomorphic HAD structure. Therefore, the traditional HAD structure can be called H 2 A special case of the AD structure. The specific parameters of this structure are:

[0144] In the HAD structure, a uniform linear array containing N antennas is divided into K subarrays, each of which contains M antennas, that is, N = MK. Considering ψ h,k,m represents the phase corresponding to the simulated beamforming, then the output of the kth subarray is:

[0145]

[0146] in represents the noise in the kth subarray. τ k,m is the propagation delay established by the direction of the signal source relative to the array and is expressed as:

[0147]

[0148] Where τ0 represents the propagation delay from the radiation source to the reference point of the antenna array, and c represents the speed of light.

[0149] The output of all subarrays is represented as:

[0150]

[0151] in is the AWGN vector, is an array manifold vector, represented as:

[0152]

[0153] And A Represents a block diagonal matrix:

[0154]

[0155] Among them, γ A,k is the kth block diagonal element:

[0156]

[0157] in, represents the phase shift at the kth subarray. Through the analog-to-digital converter (ADC), y(t) is converted to:

[0158]

[0159] Where n = 1, 2, …, L, L is the number of snapshots, θ0 is the ideal incident angle, a(θ0) represents the array manifold vector of the ideal incident angle θ0, and w(n) is the noise.

[0160] As a specific example, when M1=M2=…=M H = 1, the array will further degenerate into a full digital array. Therefore, the full digital array can also be regarded as a special case of the HAD structure. The specific parameters of this structure are:

[0161] In the FD structure, after passing through the parallel RF radio frequency link and analog-to-digital converter, the vector expression of the antenna subarray receiving signal is:

[0162] y(n)=a(θ0)x(n)+w(n)(2.17)

[0163] in is the AWGN vector. is an array manifold vector, represented as:

[0164]

[0165] The present invention also provides a working method of a dual MIMO receiver combining the all-digital subarray and the heterogeneous hybrid structure, comprising the following steps:

[0166] Step 1: For H 2 AD structure, each subarray in the hth group is regarded as a virtual antenna, and the output vector of the subarray is determined;

[0167] Step 2: Calculate the covariance matrix of the output vector of the virtual antenna array and determine the pseudo spectrum of the virtual antenna array;

[0168] Step 3: Use the Root-MUSIC algorithm to estimate DOA.

[0169] As a specific example, step 1 is as follows:

[0170] For H 2 AD structure, each subarray in the hth group is regarded as a virtual antenna, and the simulated beamforming vector is set K h The output vector of the subarray in time slot b for:

[0171]

[0172] in, represents a series of received signals in the hth group, represents a series of noises in the h-th group, Indicates M h The array manifold vector of the root virtual antenna is defined as:

[0173]

[0174] r h (θ0) is a constant obtained by adding all elements of each subarray and is expressed as:

[0175]

[0176] As a specific example, step 2 is as follows:

[0177] The output vector of the virtual antenna array The covariance matrix R h for:

[0178]

[0179] in Expressing hope, represents the variance of the received signal, is the noise variance;

[0180] R h The eigenvalue decomposition (EVD) of is:

[0181] R q =UΣU H =[U S U N ]Σ[U S U N ] H (2.23)

[0182] Among them U S and U N represent the signal and noise subspaces respectively;

[0183] K q ×K q The specific form of the diagonal matrix Σ is:

[0184]

[0185] The pseudo spectrum P corresponding to the virtual antenna array RM (θ) is:

[0186]

[0187] Where θ represents the angle of arrival of the initial input, and the spectrum peak corresponds to the desired DOA estimate;

[0188] As a specific example, step 3 is as follows:

[0189] The Root-MUSIC algorithm is used to estimate DOA, and the definition is Then the polynomial equation is expressed as:

[0190]

[0191] Where Q ij represents the element located in the i-th row and j-th column of the matrix Q, and z is a function containing θ, expressed as:

[0192]

[0193] in And f(z) has 2K h -2 roots, i.e. z i , where i = 1, 2, ..., 2K h -2, so there are multiple transmission directions, and the DOA estimation set is obtained as follows:

[0194]

[0195] Where each emission direction is:

[0196]

[0197] Among them, zi represents the i-th root of the polynomial equation (16);

[0198] Then, the DOA estimate of the hth array group is We can select the root closest to the unit circle and further get an estimate of ξ

[0199]

[0200] Since each virtual antenna corresponds to a subarray, there is a phase ambiguity that needs to be eliminated, expressed as:

[0201]

[0202] Therefore, a h The feasible solution set of a solution is:

[0203]

[0204] in,

[0205]

[0206] Combining all H groups gives:

[0207]

[0208] where j h ∈{1,2,…,M h},M H is the number of subarray antennas in the Hth group, where H represents the number of groups. represents the candidate solution set of group H, represents the estimated value of group H, j H is the imaginary unit of group H, indicating The cyclic period index in is 2π. Therefore, the candidate angle set is expressed as:

[0209]

[0210] Total candidate set include Solution, where each candidate set There is a true solution and M h -1 pseudo solution, for the FD subarray, the initial rough DOA value is estimated by the Root-MUSIC method:

[0211] y FD The covariance matrix of (n) is:

[0212]

[0213] Where E S and E N represent the signal and noise subspaces respectively, represents the signal-to-noise ratio of the received signal,

[0214] Then, the corresponding spatial spectrum function is as follows:

[0215]

[0216] where a FD (θ) represents the array popularity vector. By constructing 2(M-1) polynomial equations through Root-MUSIC, where M represents the number of antennas in the FD subarray, the root closest to the unit circle is the DOA estimate

[0217]

[0218] Therefore, finding the true solution is a challenging task.

[0219] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

[0220] It should be understood that in order to simplify the present invention and help those skilled in the art understand the various aspects of the present invention, in the above description of the exemplary embodiments of the present invention, the various features of the present invention are sometimes described in a single embodiment or described with reference to a single figure. However, the present invention should not be interpreted as the features included in the exemplary embodiments are all necessary technical features of the patent claims.

Claims

1. A dual MIMO receiver combining a fully digital subarray with a heterogeneous hybrid structure, characterized in that: Including all-digital FD sub-array structure and heterogeneous hybrid H 2 AD structure, where: The FD subarray structure has M antennas; In H 2 In the AD structure, the array is divided into H sub-array groups, each of which has K h subarrays, each of which contains M h antennas, h = 1, 2, ..., H, M1 ≠ M2 ≠ ... ≠ M H And M1,M2,…,M H The values ​​of are mutually prime.

2. The dual MIMO receiver combining the all-digital sub-array and the heterogeneous hybrid structure according to claim 1, characterized in that: When M1=M2=…=M H When H 2 The AD structure degenerates into the isomorphic HAD structure, so the isomorphic HAD structure is H 2 A special case of the AD structure.

3. The dual MIMO receiver combining the all-digital sub-array and the heterogeneous hybrid structure according to claim 2, characterized in that: When M1=M2=…=M H =1, H 2 The AD structure further degenerates into an all-digital array, which is a special case of the homogeneous HAD structure.

4. The dual MIMO receiver combining a fully digital subarray and a heterogeneous hybrid structure according to claim 3, characterized in that: The specific parameters of the receiver are as follows: A far-field narrowband signal where x(t) and f c are the baseband signal and carrier frequency respectively, t represents time, considering the FD with M antennas, the output signal is expressed as: y FD (t)=a FD (θ0)x(t)+w(t)(1.1) in is the additive white Gaussian noise (AWGN) vector, is the noise variance, I is the identity matrix, a FD The vector representation of the array manifold is: Where d = λ / 2 represents the antenna element spacing, which is half of the wavelength λ; In H 2 In the AD structure, a uniform linear array containing M antennas is divided into H groups, each containing N h antennas, and each group is divided into K h subarrays, each containing M h Antenna, that is In this array, M1≠M2≠…≠M H And M1, M2, ..., M are preferred. H The value of is considered a prime number; Considering ψ h,k,m represents the phase corresponding to the simulated beamforming, then the output of the kth subarray is: in represents the noise of the kth subarray in the hth group, τ h,k,m is the propagation delay established by the direction of the signal source relative to the array and is expressed as: Where τ0 represents the propagation delay from the radiation source to the reference point of the antenna array, and c represents the speed of light; All K h The output y of the subarray h,k (t) superposition, the baseband signal vector of the hth group is expressed as: Among them, y h (t) is the output signal y of the kth subarray of the hth group h,k (t) vector formed by stacking; The dimension is K h ×1 additive Gaussian white noise complex vector, M h is the number of antennas contained in the h-th subarray, It is the Mth h Noise at the root antenna, (·) H represents the conjugate transpose operation, is an array manifold vector, represented as: And A,h Represents a block diagonal matrix: Among them, γ A,h,k is the kth block diagonal element: in, represents the phase shift of the kth subarray in the hth group; through the analog-to-digital converter ADC, y h (t) is transformed into: Where n = 1, 2, ..., L, L is the number of snapshots; θ0 is the ideal incident angle, a h (θ0) represents the array manifold vector of the ideal incident angle θ0, and w(n) is the noise.

5. The dual MIMO receiver combining a fully digital subarray and a heterogeneous hybrid structure according to claim 4, characterized in that: When M1=M2=…=M H When H 2 The AD structure degenerates into the isomorphic HAD structure, and the specific parameters are as follows: In the HAD structure, a uniform linear array containing N antennas is divided into K subarrays, each of which contains M antennas, that is, N = MK. Considering ψ h,k,m represents the phase corresponding to the simulated beamforming, then the output of the kth subarray is: in represents the noise in the kth subarray, τ k,m is the propagation delay established by the direction of the signal source relative to the array and is expressed as: Where τ0 represents the propagation delay from the radiation source to the reference point of the antenna array, and c represents the speed of light; The output of all subarrays is represented as: in is the AWGN vector, is an array manifold vector, represented as: And A Represents a block diagonal matrix: Among them, γ A,k is the kth block diagonal element: in, represents the phase shift at the kth subarray; through the analog-to-digital converter ADC, y(t) is converted to: Where n = 1, 2, …, L, L is the number of snapshots; θ0 is the ideal incident angle, a(θ0) represents the array manifold vector of the ideal incident angle θ0, and w(n) is the noise.

6. The dual MIMO receiver combining all-digital subarrays and heterogeneous hybrid structures according to claim 5, characterized in that: When M1=M2=…=M H =1, H 2 The AD structure further degenerates into a full digital array, and the specific parameters are as follows: In the FD structure, after passing through the parallel RF radio frequency link and analog-to-digital converter, the vector expression of the antenna subarray receiving signal is: y(n)=a(θ0)x(n)+w(n)(1.17) in is the AWGN vector, is an array manifold vector, represented as:

7. A working method of a dual MIMO receiver combining a fully digital subarray with a heterogeneous hybrid structure as claimed in any one of claims 1 to 6, characterized in that: The following steps are involved: Step 1: For H 2 AD structure, each subarray in the hth group is regarded as a virtual antenna, and the output vector of the subarray is determined; Step 2: Calculate the covariance matrix of the output vector of the virtual antenna array and determine the pseudo spectrum of the virtual antenna array; Step 3: Use the Root-MUSIC algorithm to estimate DOA.

8. The working method of the dual MIMO receiver combining the all-digital sub-array and the heterogeneous hybrid structure according to claim 7, characterized in that: The step 1 is specifically as follows: For H 2 AD structure, each subarray in the hth group is regarded as a virtual antenna, and the simulated beamforming vector is set K h The output vector of the subarray in time slot b for: in, represents a series of received signals in the hth group, represents a series of noises in the h-th group, Indicates M h The array manifold vector of the root virtual antenna is defined as: r h (θ0) is a constant obtained by adding all elements of each subarray and is expressed as:

9. The working method of the dual MIMO receiver combining the all-digital sub-array and the heterogeneous hybrid structure according to claim 8, characterized in that: The step 2 is specifically as follows: The output vector of the virtual antenna array The covariance matrix R h for: in Expressing hope, represents the variance of the received signal, is the noise variance; R h The eigenvalue decomposition EVD is: Among them U S and U N represent the signal and noise subspaces respectively; K q ×K q The specific form of the diagonal matrix Σ is: The pseudo spectrum P corresponding to the virtual antenna array RM (θ) is: where θ represents the angle of arrival of the initial input and the spectrum peak corresponds to the desired DOA estimate.

10. The working method of the dual MIMO receiver combining the all-digital sub-array and the heterogeneous hybrid structure according to claim 9, characterized in that: The step 3 is specifically as follows: The Root-MUSIC algorithm is used to estimate DOA, and the definition is The polynomial equation is then expressed as: Where Q ij represents the element located in the i-th row and j-th column of the matrix Q, and z is a function containing θ, expressed as: with=e jξq (1.27) in M h dsinθ0; and f(z) has 2K h -2 roots, i.e. z i , where i=1,2,…,2K h -2, so there are multiple transmission directions, and the DOA estimation set is obtained as follows: Where each emission direction is: Among them, z i represents the i-th root of the polynomial equation (1.26); DOA estimation of the hth array group We can select the root closest to the unit circle and further get an estimate of ξ Since each virtual antenna corresponds to a subarray, there is a phase ambiguity that needs to be eliminated, expressed as: Therefore, a h The feasible solution set of a solution is: in, Combining all H groups gives: where j h ∈{1,2,…,M h },M H is the number of subarray antennas in the Hth group, where H represents the number of groups. represents the candidate solution set of group H, represents the estimated value of group H, j H is the imaginary unit of group H, indicating The cyclic period index in is 2π; therefore, the candidate angle set is expressed as: Total candidate set include Solution, where each candidate set There is a true solution and M h -1 pseudo solution, for the FD subarray, the initial rough DOA value is estimated by the Root-MUSIC method: y FD The covariance matrix of (n) is: Where E S and E N represent the signal and noise subspaces respectively, represents the signal-to-noise ratio of the received signal, The corresponding spatial spectrum function is as follows: where a FD (θ) represents the array manifold vector; By constructing 2(M-1) polynomial equations through Root-MUSIC, where M represents the number of antennas in the FD subarray, the root closest to the unit circle is the DOA estimate

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