Antenna array design method for moving unmanned platform

Abstract

The invention relates to the technical field of virtual array design, and discloses a method for designing an antenna array of a moving unmanned platform, which comprises the following steps of: carrying out phase correction processing on signals acquired in each time period of the antenna array of the moving unmanned platform, and then moving the signals into the same reference time period according to transverse motion and longitudinal motion phases; and obtaining an expanded passive synthesis virtual array, and enabling the signal subjected to phase shift to be equivalent to signal data of the synthesized virtual array in the reference time period. The constructed virtual array is divided into a transverse array and a longitudinal array which are virtually expanded into a longer linear array and a longer area array respectively. Through the expansion of the virtual array elements, the degree of freedom of the original array is improved by integral multiples, and the DOA estimation precision is also remarkably improved along with the increase of the number of the array elements.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual formation design, and particularly to a method for designing an antenna array of a moving unmanned platform. Background Art

[0002] With the wide application of unmanned aerial vehicles (UAVs) in reconnaissance and surveillance, precision strike, electronic jamming, camouflage and deception, target guidance, etc. in local wars, unmanned platforms have attracted worldwide attention due to their unique tactical and strategic advantages. The airborne reconnaissance system with UAVs as the carrier has the advantages of being flexible, having a large coverage area, and being less restricted by terrain, and can complete reconnaissance tasks that are difficult for ground systems to accomplish. However, with the development of small-sized UAV reconnaissance platforms, the array aperture carried by the UAV platform is greatly restricted. According to the array antenna theory, high-resolution and high-degree-of-freedom (DOF) direction-of-arrival (DOA) estimation requires the support of a large-aperture array, but it has become increasingly difficult to significantly improve the degree of freedom of the system only by optimizing the array structure, and it is difficult to balance the design difficulty of the platform and the overall cost control by adopting an array with a larger physical size. Therefore, in order to further improve the degree of freedom (DOF) based on array structure design, synthetic aperture (SA) technology has been widely applied in array signal processing in recent years. Combining a physical array with synthetic aperture technology can increase the length of the continuous virtual array element part through the movement of the array, improving the DOF and DOA estimation accuracy. At the same time, in order to improve the concealment, mobility, flexibility, and cost control advantages of the reconnaissance and positioning system of the unmanned platform, it has become the best choice to carry out relevant research on the formation design of small-sized arrays, moving aperture synthesis, and subsequent high-precision DOA estimation relying on small UAV platforms.

[0003] Virtual formation is a new research hotspot in the field of array signal processing in recent years. Compared with traditional physical formations, virtual formations expand the aperture of the original array or increase the number of array elements by processing the received signal data through a specific array structure model, mathematical methods, or performing virtual transformation on the array. Classical virtual formations include interpolated virtual arrays and conjugate virtual arrays. The interpolated virtual array increases the effective aperture of the array by inserting virtual array elements between physical arrays. The advantages are improving spatial resolution and being simple and easy to implement, but it will cause problems such as inaccurate signal estimation, shallow nulls, and noise amplification. The conjugate virtual array generates a virtual array by combining the signal of the actual array with its conjugate signal, and its aperture is larger than that of the actual array. The advantages are improving resolution and increasing the degree of freedom, but it will cause the problem of noise amplification. The antenna model of the interpolated virtual array is as Figure 1 shown, and the number of expanded array elements is and both the interpolated virtual array and the conjugate virtual array are not applicable to moving platforms. Utilizing the conjugate symmetry of the data received by the array antenna, we get as Figure 2The conjugate virtual array shown. Summary of the Invention

[0004] In view of the above problems, the present invention proposes a method for designing an antenna array for a moving unmanned platform.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for designing an antenna array for a moving unmanned platform, comprising:

[0007] After performing phase correction processing on the signals collected by the antenna array (moving array) of the moving unmanned platform at each time period, the signals are phase-shifted according to the horizontal movement and the vertical movement into the same reference time period to obtain an extended passive synthetic virtual array, and the signals after phase shifting are equivalent to the signal data of the synthetic virtual array in this reference time period.

[0008] Further, both the horizontal movement and the vertical movement are uniform linear motions.

[0009] Further, during the movement, the signals remain coherent, and the phase difference compensated to the time t + τ is exp(j2πfτ);

[0010] When performing phase shifting according to the horizontal movement, the received signal model of the virtual array is:

[0011]

[0012] Wherein, is the received signal vector of the virtual array at the time t + τ when performing phase shifting according to the horizontal movement, x(t + τ) represents the received signal vector of the physical moving array at the time t + τ, ε(t + τ) is the additive zero-mean white noise at the time t + τ,

[0013] where v is the movement speed, λ is the wavelength, θ q is the incident angle, s(t) represents the signal vector at the time t, s1(t), s2(t),..., s Q (t) are Q far-field uncorrelated narrowband signals received at the time t, d2 is the distance from the second array element to the origin, d L is the distance from the Lth array element to the origin.

[0014] Further, when performing phase shifting according to the horizontal movement, the aperture H E of the extended passive synthetic array is expressed as:

[0015] H E = vT total + H d

[0016] Among them, H d represents the aperture of the physical array, v is the moving speed, and T total represents the time difference between the front edge of the first sampling pulse and the front edge of the last sampling pulse of the array.

[0017] Furthermore, when performing phase shifting according to longitudinal movement, the received signal model of the virtual array is:

[0018]

[0019] In the formula,

[0020] A syn = [a syn (μ1,γ1,α),…,a syn (μ K ,γ K ,α)]

[0021]

[0022] p k = μ k cos(α)+γ k sin(α)

[0023]

[0024] Among them, x syn (t) represents the received signal vector of the virtual array at time t when performing phase shifting according to longitudinal movement, s(t) represents the signal vector at time t, A syn is the synchronization direction matrix, n syn (t) is the synchronization noise vector at time t, M represents the number of array elements, TCP represents the time coherence period, τ represents time, n is a non-negative integer, 0 ≤ n ≤ N, s1(t),…,s K (t) is the kth incident signal at time t, k = 1,…,K, α is the angle between the positive x-axis and the moving direction, 0° < α < 180°, v is the moving speed, n(t) is a white Gaussian additive noise vector with a mean of zero and a variance of σ 2 , a x (μ k ) is the array manifold, is the carrier frequency with the electromagnetic wave propagation speed c, λ is the wavelength, d xm is the abscissa of the array element, m = 1,…,M, the moving distance within time τ, d Nτ = Nd, d = vτ.

[0025] Furthermore, when the motion array is a uniform linear array, TCP ula =(M - 1)τ ula , where TCP ula represents the time coherence period corresponding to the uniform linear array, and τ ula represents time.

[0026] Furthermore, the method further includes performing beamforming on the lateral motion virtual array in the following manner:

[0027] Construct the joint sampling data s of the signal at two moments t + T l and t + T l+1 ; γl

[0028] Calculate the covariance matrix R of the joint sampling data s at moments t + T l and t + T l+1 ; γl γl

[0029] Using the generalized eigenvalue decomposition method, calculate the eigenvalue diagonal matrix and the eigenvector matrix of R γl to obtain the noise subspace U oN ;

[0030] Construct the MUSIC cost function P MUSIC , and estimate the incident angles θ of a total of K pairs of radiation sources at moment t + T oN based on U l ;

[0031] Traverse and optimize the search for θ to obtain the incident angle θ of the k-th pair of radiation sources k .

[0032] Furthermore, the method further includes performing beamforming on the longitudinal motion virtual array in the following manner:

[0033] Calculate the covariance matrix of x syn (t)

[0034] Perform eigenvalue decomposition on to obtain the noise subspace

[0035] Based on construct the spectral function Y(μ, γ, α);

[0036] After two-dimensional traversal search, the two-dimensional DOA estimate is obtained as where and ​​​They are respectively the azimuth angle and elevation angle of the estimated k-th radiation source.

[0037] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0038] The virtual array constructed by the present invention is divided into horizontal and vertical directions, and is respectively virtually extended into a longer linear array and planar array. The passive synthetic virtual array constructed horizontally by the present invention effectively expands the array aperture, and the synthetic time can be adjusted according to needs, and the layout of the synthetic array can be flexibly designed. The present invention realizes two-dimensional virtual aperture and virtual planar array through vertical expansion, and has universality in the motion direction.

[0039] The virtual linear array expanded through multiple motions and samplings by the present invention can accurately perform DOA estimation. The virtual planar array expanded through multiple motions and samplings by the present invention can accurately perform two-dimensional DOA estimation, and the degree of freedom is significantly improved compared with that of a common linear array. Through the expansion of virtual array elements, the degree of freedom of the original array is increased by an integer multiple, and the DOA estimation accuracy is also significantly improved with the increase of the number of array elements (physical array elements + virtual array elements). Description of the Drawings

[0040] Figure 1 It is a schematic diagram of the interpolation virtual array expansion;

[0041] Figure 2 It is a schematic diagram of the conjugate virtual array expansion;

[0042] Figure 3 It is a schematic diagram of the moving linear array and incident signal provided by the embodiment of the present invention;

[0043] Figure 4 It is a schematic diagram of the horizontal moving virtual array element expansion provided by the embodiment of the present invention;

[0044] Figure 5 It is a schematic diagram of the vertical moving virtual array element expansion provided by the embodiment of the present invention;

[0045] Figure 6 It is a synthesis diagram of the two-dimensional virtual aperture and virtual planar array provided by the embodiment of the present invention;

[0046] Figure 7 It is a schematic diagram of the vertical movement of the uniform linear array provided by the embodiment of the present invention (vertical view);

[0047] Figure 8 It is the DOA estimation of the horizontal moving array provided by the embodiment of the present invention (multiple times);

[0048] Figure 9 It is a table of DOA estimation values of the horizontal moving array provided by the embodiment of the present invention;

[0049] Figure 10The two-dimensional DOA estimation of the longitudinally moving virtual planar array provided by the embodiments of the present invention at different times t (t = 1, 2, 3, 4);

[0050] Figure 11 The two-dimensional DOA estimation value table of the longitudinally moving virtual planar array provided by the embodiments of the present invention (t = 4). Specific embodiments

[0051] The following further explains the present invention in conjunction with the accompanying drawings and specific embodiments:

[0052] With the wide application of unmanned aerial vehicles (UAVs), people have tried to apply virtual array antenna technology on UAV platforms, and the design of moving virtual spatio-temporal arrays has emerged accordingly. The emergence of the design of moving virtual spatio-temporal arrays has also provided new ideas for the optimization of virtual array antenna technology. Compared with classical virtual array synthesis, array motion technology is used to increase the virtual effective aperture of the array and has attracted increasing interest.

[0053] The present invention provides a method for designing an antenna array for a moving unmanned platform, which involves the design of a moving virtual spatio-temporal array (virtual array). The following focuses on the analysis of the design of the moving virtual spatio-temporal array, and its essence is the passive synthesis processing of the moving array. The corresponding process is as follows: After performing phase correction processing on the signals collected in each time period of the moving array, the phases are shifted to the same reference time period. Then, the signals after phase shift can be equivalently regarded as the signal data of the virtual array after passive synthesis in this reference time period. Generally speaking, the phase difference between two signals in adjacent time periods is 2πf0T. When performing passive synthesis processing of the array by this method of phase shift, it is necessary to determine the phase difference between the signals in each adjacent time period, and then perform phase shift in each adjacent time period to achieve the alignment of the phase differences. The motion is divided into horizontal and longitudinal motions according to the motion direction.

[0054] The following first introduces the basic principle of the design of the horizontally moving virtual spatio-temporal array:

[0055] As Figure 3 shown, assume there is a co-prime array with M array elements moving at a constant speed v, and Q far-field uncorrelated narrowband signals are received, which are respectively s q (t), t = T s , 2T s ,..., L s T s , T s and L s respectively represent the sampling interval and the number of snapshots, and the incident angle corresponding to each signal is θ q , then the received signal model at time t is

[0056]

[0057] where is additive white Gaussian noise with zero mean, d2 is the distance from the second element to the origin, and d L is the distance from the L-th element to the origin. The first element is located at the origin. Then the received signal at time t + τ can be further expressed as

[0058]

[0059] where,

[0060]

[0061] For narrowband incident signals, the envelope changes slowly. Therefore, the received signal model at time t + τ can be further written as

[0062] x(t + τ) = exp(j2πfτ)Bs(t) + ε(t + τ) (3)

[0063] If the relationship between the motion speed and the half-wavelength is defined as vτ = d = λ / 2, then the steering vector at time t + τ can be written as

[0064]

[0065] Assume that the signal remains coherent during the motion. At this time, the phase difference compensated for time t + τ is exp(j2πfτ), and the synthesized received signal vector can be obtained as

[0066]

[0067] where

[0068] After combining the received signal models at two times, we can obtain

[0069]

[0070] After compensating the phase difference for the received data of the physical array, the extended passive synthetic array can be obtained. One advantage of the passive synthesis algorithm is that the array extension is not limited by element overlap and is more flexible. The aperture H of the extended synthetic array E can be expressed as:

[0071] H E = vT total + H d (7)

[0072] where H d is the aperture of the physical array, and T totalDenotes the time it takes for the array to receive data from the first segment to the last segment, that is, the time difference between the leading edge of the first sampling pulse and the leading edge of the last sampling pulse. Taking the linear array {0, 1, 2, 3}m as an example, moving uniformly in a certain direction, the extended virtual array elements {4, 5, 6, 7, 8, 9, 10, 11}m can be obtained. The basic physical array and the virtual extended array are as Figure 4 .

[0073] It can be seen that the passive synthetic array effectively expands the array aperture, and by adjusting the synthesis time as needed, the layout of the synthesized array can be flexibly designed.

[0074] Previously, by making the array move uniformly in a straight line in the transverse direction, the generalization method of the linear array transverse movement was explored. Based on the synthetic aperture technology, by making the array move uniformly in a straight line in the longitudinal direction, the formation process of the two-dimensional virtual array aperture is mathematically explained below, and the synthetic signal model of the virtual array is derived. The basic principle of the virtual space-time array pattern design for longitudinal movement is continued to be introduced below.

[0075] Figure 5 Shows a schematic diagram of the longitudinal movement of the linear array. Consider the initial array as a linear array with M array elements, and the abscissa of the array element is d xm , where m = 1, …, …, and the first array element is the reference point, that is, d x1 = 0. Without loss of generality, make the linear array located on the positive x-axis move along an arbitrary direction at a constant speed v. Denote the angle (offset angle) between the positive x-axis and the movement direction as α. Due to symmetry, the angle α can be limited to 0° < α < 180°.

[0076] Assume that K far-field narrowband signals with the same wavelength λ are incident on the array, and the k-th incident signal is expressed as s k (t), k = 1, …, K. Introduce the parameters and where θ k ∈[0°, 180°] and are the k-th azimuth angle and elevation angle respectively. The output of the linear array at time t is expressed as

[0077]

[0078] where is the carrier frequency with the electromagnetic wave propagation speed c, p k is written as p k = μ k cos(α) + γ k sin(α). n(t) is a white Gaussian additive noise vector with a mean of zero and a variance of σ 2 . The array manifold a x(μ k ) is represented as

[0079]

[0080] The output of the array at time t can be transformed to:

[0081] x(t) = As(t) + n(t) (10)

[0082] where the direction matrix is and the signal vector is

[0083]

[0084] At time t + nτ, where n is a non - negative integer, the received signal of the array becomes

[0085]

[0086] where the new direction matrix A n =[a n (μ1,γ1,α),…,a n (μ K ,γ K ,α)].

[0087] where

[0088] For narrow - band signals holds. Thus, Equation (11) can be rewritten as

[0089] x(t + nτ)=exp(j2πf0nτ)A n s(t)+n(t + nτ) (12)

[0090] By using the phase - correction factor exp(j2πf0nτ), the synchronized signal can be obtained.

[0091]

[0092] where

[0093] The time - coherence period (TCP) is introduced to determine the total motion time, and it is assumed that the distance traveled within time τ is d. In addition, it is assumed that the waveform and position of the source remain unchanged during the period of array motion.

[0094] Denote and 0 ≤ n ≤ N, the combined received signal using synthetic - aperture processing is given by

[0095]

[0096] By substituting (10) and (13) into (14), we have

[0097]

[0098] where the synchronization direction matrix is and the synchronization noise vector becomes Specifically, A syn can be further written as:

[0099] A syn = [a syn (μ1,γ1,α),…,a syn (μ K ,γ K ,α)] (16)

[0100] where and

[0101]

[0102] Under synthetic aperture processing, two-dimensional virtual apertures and virtual plane arrays are realized and are universal in the motion direction. To illustrate the above method more clearly, a flowchart is provided as Figure 6 shown.

[0103] Based on the above analysis, for a uniform linear array (ULA), the synthetic aperture processing method is elaborated in detail, further clarifying the universality of the method. The initial array is set as an array with M array elements, and the spacing d between its array elements (units) is half a wavelength Therefore, the corresponding abscissas of the array elements are As Figure 7 shown, the antenna is controlled to move along the motion direction by a distance of half a wavelength per time τ ula Then, the time τ ula is calculated as Meanwhile, TCP is restricted to TCP ula = (M - 1)τ ula , so the parameter n is determined as Therefore, the synthetic signal is formed as:

[0104]

[0105] where the synchronization direction matrix is and the synchronized noise vector becomes Specifically, A syn,ula can be further written as

[0106] A syn,ula = [a syn,ila (μ1,γ1,α),…,a syn,ula (μK , γ K , α)] (18)

[0107] wherein

[0108] wherein

[0109] and

[0110] In summary, the motion virtual space-time array is divided into horizontal and vertical directions and is virtually expanded respectively.

[0111] Under the support of the above array motion synthesis principle, the current research on the design of the motion virtual space-time array mainly starts from the perspectives of array element expansion array structure, integer multiple and half-wavelength motion, multi-level non-uniform motion sampling method design, etc., aiming to obtain a larger synthetic aperture. Moreover, the existing motion virtual space-time array and motion sampling method design only target one-dimensional linear arrays or single array element groups. Although the aperture can be improved by motion for the array, high resolution still requires a large physical aperture array to achieve. For example, for an array carried by a single moving platform, a large aperture array has extremely high requirements for the carrying platform. For a signal source with a frequency of 1 GHz, its half-wavelength is 0.15 m. If a uniform linear array (ULA) composed of four array elements is used, its aperture is 0.6 m, which is also larger than the size of a general small unmanned aerial vehicle. In addition, one of the necessary conditions for synthetic aperture processing is that the time required to form the synthetic array must be less than the minimum coherence time of the signal (temporal signal coherence period, TCP). In the field of underwater acoustic positioning, due to the numerical characteristics of the signal wavelength and conventional detection frequencies, it is reasonable to make assumptions about signal coherence (or coherence). However, for the electromagnetic radiation source signals in the actual reconnaissance and positioning scenarios, this coherence requirement is extremely strict.

[0112] To solve the above problems, the design and corresponding verification of the motion sampling method for the motion virtual space-time array with a small aperture will be carried out below, which is more suitable for the DOA estimation scenario with a small unmanned aerial vehicle as the moving platform. Accordingly, aiming at the synthesis of a large aperture motion virtual space-time array with a limited number of motions, and taking the physical size, load and power of the moving platform as constraints, a motion virtual space-time array with high degrees of freedom and the corresponding motion sampling method will be designed and the DOA estimation accuracy will be verified.

[0113] The specific steps of the beamforming algorithm for the horizontal motion virtual space-time array are as follows:

[0114] (1) Construct the joint sampling data s of the signal at two moments t + T l and t + T l+1 γl ​is:

[0115]

[0116] Combined steering vector A γl is:

[0117] A γl =[A l ; A l+1 (20)

[0118] (2) Calculate t + T l and the covariance matrix of the combined sampling data at time t + T l+1 :

[0119]

[0120] where the signal covariance matrix is expressed as

[0121] R S,γl = E{s l (t)s l (t) H} = diag{pw1, pw2,..., pw K}, pw K represents the power of the Kth signal, and the noise covariance matrix is expressed as R N,γl = E{n γl (t)n γl (t) H} = σ 2 I γl , σ 2 represents the power of the noise.

[0122] (3) Using the method of generalized eigenvalue decomposition (Eigen Value Decomposition, EVD), calculate the eigenvalue diagonal matrix and eigenvector matrix of R γl to obtain the noise subspace U oN ; it should be noted that the data received by the array is of finite length. Therefore, in practice, the covariance matrix is calculated by the maximum likelihood estimation method using the finite-length received data, that is:

[0123]

[0124] where D is the number of snapshots. Therefore, the calculated noise subspace is U oN .

[0125] (4) Construct the MUSIC cost function P MUSIC , and estimate the incident angles θ of a total of K pairs of radiation sources at time t + T l as follows:

[0126]

[0127] (5) Traverse and optimize the search for θ to obtain the k-th pair of angles θ k , that is:

[0128]

[0129] This algorithm is applicable to the case of multiple independent radiation sources or coherent radiation sources, and can process multiple radiation sources with similar frequencies simultaneously. The simulation conditions are as follows: The array located on the x-axis is a uniform linear array with 4 physical array elements and an element spacing of λ / 2, moving at a constant speed of v = 4 element spacings / s. Consider that there are K far-field narrowband uncorrelated signal sources incident on the array. The corresponding angle search range is [-90, 90]°, and the step size is 0.1. According to the above analysis, the synthetic time interval of the moving array is 1 s, and the synthesis is performed 3 times. The estimation results are as Figure 8 shown, where K = 7, specifically see Figure 9 . In addition, the noise is additive white Gaussian noise, and the SNR and the number of snapshots are set to 8 dB and F = 800 respectively.

[0130] From Figure 9 , it can be seen that with the movement of the array and multiple samplings, the number of signals that can be estimated increases significantly. It can be concluded that through the virtual linear array expanded by multiple movements and samplings, the DOA can be accurately estimated. The improvement compared to the ordinary four-element linear array that can only estimate three signal degrees of freedom is obvious.

[0131] The transverse movement virtual spatio-temporal array beamforming was discussed previously. Considering the movement direction of the UAV, the longitudinal movement virtual spatio-temporal array beamforming is discussed below. In this section, the MUSIC method is also used for two-dimensional DOA estimation. First, calculate the covariance matrix of the synthetic signal,

[0132]

[0133] The covariance matrix is expressed as Perform eigenvalue decomposition (EVD) on it to obtain the noise subspace Without loss of generality, the same notation is also used for other matrices and vectors.

[0134] Define the spectral function Y(μ, γ, α) as follows:

[0135]

[0136] After two-dimensional traversal search, the estimation of the two-dimensional DOA is

[0137] The brief process is as follows:

[0138] Input: Synthesized received signal x syn (t), the number M of array elements, and the number K of sources.

[0139] Output: DOA estimation k = 1, ..., K.

[0140] 1: Calculate the covariance matrix For Perform eigenvalue decomposition to obtain the noise subspace

[0141] 2: Construct the spectral function Y(μ, γ, α).

[0142] 3: Calculate the 2D DOA estimation through the spectral function.

[0143] 4: Return

[0144] The following gives the estimation results corresponding to the virtual planar array formed by the longitudinal movement of the array to verify the ability of the proposed method to achieve 2D DOA estimation. The simulation conditions are as follows: The array located on the x-axis is a uniform linear array with 4 physical array elements and an element spacing of λ / 2, moving at a constant speed of v = 1 element spacing / s. Consider K far-field narrowband uncorrelated signal sources incident on the array. The corresponding azimuth and elevation angle search ranges are [-90, 90]°, and the step size is 0.1. According to the above analysis, the movement time is 4 s and the aperture synthesis is performed 4 times. The bias angle α is selected as α = 30°. The estimation results are as Figure 10 shown, where K = 6, and the specific estimated angles are as follows Figure 11 . In addition, the noise is additive white Gaussian noise, and the SNR and the number of snapshots are set to 8 dB and F = 800, respectively.

[0145] The simulation results show that a four-element linear array can be used for 2D DOA estimation of six signals. Therefore, it can be concluded that the virtual planar array extended through multiple movements and samplings can accurately perform 2D DOA estimation, and the degree of freedom is significantly improved compared with that of a common linear array.

[0146] Through the above extension of virtual array elements, the degree of freedom of the original array form is increased by an integer multiple, and the DOA estimation accuracy is also significantly improved with the increase in the number of array elements (physical array elements + virtual array elements).

[0147] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A method for designing an antenna array of a mobile unmanned platform, characterized in that Including: After performing phase correction processing on the signals collected by the antenna array of the moving unmanned platform at each time period, the signals are phase-shifted to the same reference time period according to the lateral movement and longitudinal movement, obtaining an extended passive synthetic virtual array, and the signals after phase-shifting are equivalent to the signal data of the synthetic virtual array in this reference time period.

2. The antenna array design method of a mobile unmanned platform according to claim 1, wherein Both the lateral movement and the longitudinal movement are uniform linear motions.

3. A method for designing an antenna array of a mobile unmanned platform according to claim 1, characterized in that, During the movement, the signals maintain coherence, and the phase difference compensated to the time t + τ is exp(j2πfτ); When performing phase-shifting according to the lateral movement, the received signal model of the virtual array is: Among them, is the received signal vector of the virtual array at time t + τ when phase shifting is performed according to the lateral movement, and x(t + τ) represents the received signal vector of the physical movement array at time t + τ. ε(t + τ) is the additive zero-mean white noise at time t + τ. where v is the moving speed, λ is the wavelength, and θ q is the incident angle, s(t) represents the signal vector at time t, and s1(t), s2(t), …, s Q (t) are Q far-field uncorrelated narrowband signals received at time t, d2 is the distance from the second array element to the origin, and d L is the distance from the Lth array element to the origin.

4. A method for designing an antenna array of a moving unmanned platform according to claim 1, characterized in that When performing phase shifting according to the lateral movement, the aperture H of the expanded passive synthesis array E is expressed as: H E = vT total + H d where H d represents the aperture of the physical array, v is the moving speed, and T total represents the time difference between the front edge of the first sampling pulse and the front edge of the last sampling pulse of the array.

5. A method for designing an antenna array of a mobile unmanned platform according to claim 1, characterized in that, When performing phase-shifting according to the longitudinal movement, the received signal model of the virtual array is: In the formula, A syn = [a syn (μ1,γ1,α),…,a syn (μ K ,γ K ,α)] p k = μ k cos(α) + γ j sin(α) where x syn (t) represents the received signal vector of the virtual array at time t during phase shifting according to longitudinal movement, s(t) represents the signal vector at time t, A syn is the synchronization direction matrix, n syn (t) is the synchronization noise vector at time t, M represents the number of array elements, TCP represents the time coherence period, τ represents time, n is a non - negative integer, 0 ≤ n ≤ N, s1(t), …, s K (t) is the k - th incident signal at time t, k = 1, ..., K, α is the angle between the positive x - axis and the movement direction, 0° < α < 180°, v is the movement speed, n(t) is a white Gaussian additive noise vector with zero mean and variance σ 2 , a x (μ k ) is the array manifold, is the carrier frequency with the electromagnetic wave propagation speed c, λ is the wavelength, d xm is the abscissa of the array element, m = 1, ..., M, the movement distance within time τ, d Nτ = Nd, d = vτ.

6. The antenna array design method of a mobile unmanned platform according to claim 5, characterized in that, When the motion array is a uniform linear array, TCP ula =(M - 1)τ ula , where TCP ula represents the time coherence period corresponding to the uniform linear array, and τ ula represents time.

7. A method for designing an antenna array of a moving unmanned platform according to claim 1, characterized in that This method further includes performing beamforming on the virtual array of the lateral movement in the following manner: Structure t+T l and t+T l+1 Joint sampling data s of the signal at two moments γl ; Calculate t+T l and t+T l+1 Jointly sample the data s γl at the moments of t+T to obtain the covariance matrix R γl ; Using the generalized eigenvalue decomposition method, calculate R γl The eigenvalue diagonal matrix and the eigenvector matrix, and obtain the noise subspace U oN ; Construct the MUSIC cost function P MUSIC , based on U oN Estimate the incident angles θ of a total of K pairs of radiation sources at time t + T l ; Traverse the optimized search θ to obtain the incident angle θ of the k-th pair of radiation sources k .

8. The antenna array design method for a moving unmanned platform according to claim 5, characterized in that This method further includes performing beamforming on the virtual array of the longitudinal movement in the following manner: Calculate x syn Covariance matrix of (t) Perform eigenvalue decomposition to obtain the noise subspace Based on Construct the spectral function Y(μ,γ,α); After two-dimensional traversal search, the estimated two-dimensional DOA is where and are the azimuth angle and elevation angle of the k-th estimated radiation source, respectively.

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