Multi-target sensing method and device

Abstract

The invention provides a multi-target sensing method and device, and the method comprises the steps: transmitting an OFDM signal to an intelligent metasurface through a transmitting antenna, transmitting the OFDM signal to a multi-target position through the intelligent metasurface, reflecting the OFDM signal to a receiving antenna, enabling the OFDM signal to comprise a first set number of time frames, and enabling each time frame to comprise a second set number of OFDM symbols, the intelligent metasurface is provided with a fourth set number of transmission array elements, and the transmission array elements are used for controlling and outputting the input OFDM symbols into beam signals through beam forming, and obtaining OFDM reflection signals reflected to a receiving antenna. Performing joint processing on beam signals contained in each time frame of the OFDM transmitting signal to obtain a target parameter vector estimated value of each subcarrier of the corresponding frame so as to obtain a time delay unit vector, performing coherent accumulation on the time delay unit vector to obtain a time delay spectrum, the time delay spectrum comprising a fifth set number of discrete values, judging whether each time delay unit has a target or not based on each discrete value; and for the time delay unit with the target, calculating the distance and the angle of the target.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication and perception, and in particular to a multi-target perception method and device. Background Art

[0002] Smart metasurfaces can intelligently reshape the wireless signal propagation environment and are regarded as an innovative technology for the next generation of mobile communication systems. Specifically, smart metasurfaces are digitally controllable metasurfaces composed of a large number of low-cost reflective or transmissive array elements, which can reconstruct the wireless transmission environment by actively adjusting the amplitude and phase of the incident signal. At present, smart metasurfaces have been widely studied for use in the fields of communication and perception. In the field of communication, through active and passive combined beamforming, smart metasurfaces can greatly improve the signal-to-noise ratio, transmission rate and spectrum efficiency of the system, and achieve high-speed communication. In the field of perception, smart metasurfaces can enhance the intensity of target echo signals, thereby improving the target detection probability and target parameter estimation accuracy. At the same time, deploying smart metasurfaces between base stations and users or between base stations and targets can overcome the problem of obstacles blocking wireless signal transmission, especially in high-frequency bands with severe path loss, and realize non-line-of-sight communication and perception. Since both communication and perception are to extract information of interest from wireless signals in a noisy environment, communication and perception are expected to share hardware resources and wireless resources, that is, communication and perception integration. Deploying smart metasurfaces in a communication and perception integrated system can bring gains to both communication and perception.

[0003] At present, the intelligent metasurface assisted perception methods only consider using the signal-to-noise ratio gain provided by the intelligent metasurface in the spatial domain to improve the target detection probability and parameter estimation accuracy, or using the spatial degrees of freedom provided by the intelligent metasurface to improve the angle estimation capability. However, these methods do not utilize the beamforming gain of the intelligent metasurface in the time domain, and do not fully explore the gain of the intelligent metasurface on perception performance, especially in terms of resolution. Summary of the invention

[0004] The present invention aims to solve one of the technical problems in the related art at least to a certain extent.

[0005] To this end, the first objective of the present invention is to propose a multi-target perception method to improve the perception accuracy and perception resolution of multiple targets.

[0006] The second objective of the present invention is to provide a multi-target perception device.

[0007] To achieve the above object, the first aspect of the present invention proposes a multi-target perception method, comprising:

[0008] An OFDM signal is transmitted to the smart metasurface by using a transmitting antenna, and the OFDM signal is transmitted by the smart metasurface to multiple targets and then reflected by each target to a receiving antenna, wherein the OFDM signal includes a first set number of time frames, each time frame includes a second set number of OFDM symbols, each OFDM symbol includes a third set number of subcarriers, and the smart metasurface is configured with a fourth set number of transmission array elements, and the transmission array elements are used to control the input OFDM symbols to be output into beam signals through beamforming;

[0009] Obtain an OFDM reflected signal reflected to a receiving antenna, perform joint processing on a beam signal contained in each time frame of the OFDM transmit signal to obtain a target parameter vector estimate of each subcarrier of the corresponding frame, obtain a delay unit vector based on the target parameter vector estimate, perform coherent accumulation on the delay unit vector to obtain a delay spectrum, wherein the delay spectrum includes a fifth set number of discrete values, each discrete value corresponds to a delay unit, determine whether there is a target in each delay unit based on each discrete value, and calculate the distance of the target for the delay unit where the target exists;

[0010] For the time delay units with targets, the angle of each target is calculated by using the subspace method based on the time delay unit vector.

[0011] In the method of the first aspect of the present invention, the second set number is equal to the fourth set number, and the space-time beamforming codebook of each transmission array element of the smart metasurface is an orthogonal codebook.

[0012] In the method of the first aspect of the present invention, the beam signal contained in each time frame of the OFDM transmission signal is jointly processed to obtain the target parameter vector estimation value of each subcarrier of the corresponding frame, including: defining a target parameter vector, the target parameter vector is equal to the transpose of the smart metasurface-target-receiving antenna channel matrix; based on the target parameter vector, the form of the beam signal contained in each time frame is converted to obtain the required beam signal; based on the required beam signal, the least squares method is used for joint processing to obtain the target parameter vector estimation value of each subcarrier of the corresponding frame.

[0013] In the method of the first aspect of the present invention, obtaining the delay unit vector based on the target parameter vector estimate includes: obtaining the delay unit vector based on the target parameter vector estimate using an inverse discrete Fourier transform method.

[0014] In the method of the first aspect of the present invention, the discrete value corresponding to the i-th delay unit satisfies:

[0015]

[0016] In the formula, g iis the discrete value corresponding to the i-th delay unit, is the azimuth, γ D is the pitch angle, T is the first setting number, N is the third setting number, L is the fourth setting number, is the transpose of the array response vector of the smart metasurface, g i (t) is the delay unit vector corresponding to the t-th time frame and the i-th delay unit.

[0017] In the method of the first aspect of the present invention, judging whether each delay unit has a target based on each discrete value includes: judging whether each delay unit has a target based on each discrete value using a binary hypothesis testing method.

[0018] In the method of the first aspect of the present invention, the distance of the target is calculated for the delay unit where the target exists, including: determining the delay unit index where the target exists, and calculating the distance of the target in the delay unit based on the delay unit index, the speed of light, a third set number and the subcarrier spacing.

[0019] In the method of the first aspect of the present invention, the angle of each target is calculated based on the delay unit vector using a subspace method for the delay unit with a target, including: for any delay unit with a target, preprocessing the delay unit vector of the delay unit using a forward and backward spatial smoothing technique to obtain a covariance matrix after spatial smoothing; obtaining the angle spectrum of the target in the delay unit based on the covariance matrix after spatial smoothing to obtain the angle of the target in the delay unit, and then obtaining the angle of the target in all delay units with targets.

[0020] In the method of the first aspect of the present invention, the angle spectrum of the target in the delay unit is obtained based on the covariance matrix after spatial smoothing, including: performing eigenvalue decomposition on the covariance matrix after spatial smoothing of the delay unit; obtaining eigenvectors based on eigenvalues ​​and then obtaining the angle spectrum of the target in the delay unit.

[0021] To achieve the above-mentioned object, the second aspect of the present invention provides a multi-target sensing device, comprising a multi-target sensing unit and a computing unit;

[0022] The multi-target sensing unit includes a transmitting antenna, a smart metasurface and a receiving antenna; the transmitting antenna is used to transmit an OFDM signal to the smart metasurface, wherein the OFDM signal includes a first set number of time frames, each time frame includes a second set number of OFDM symbols, and each OFDM symbol includes a third set number of subcarriers; the smart metasurface is configured with a fourth set number of transmission array elements, and the transmission array elements are used to control the input OFDM symbols to be output into beam signals through beamforming; the OFDM signal is transmitted by the smart metasurface to multiple targets and then reflected by each target to the receiving antenna; the receiving antenna is used to receive the OFDM reflection signal reflected by each target;

[0023] The calculation unit is used to obtain the OFDM reflection signal reflected to the receiving antenna, jointly process the beam signal contained in each time frame of the OFDM transmission signal to obtain the target parameter vector estimation value of each subcarrier of the corresponding frame, obtain the delay unit vector based on the target parameter vector estimation value, coherently accumulate the delay unit vector to obtain the delay spectrum, the delay spectrum includes a fifth set number of discrete values, each discrete value corresponds to a delay unit, based on each discrete value, it is judged whether each delay unit has a target, and the distance of the target is calculated for the delay unit with the target; for the delay unit with the target, the angle of each target is calculated by using the subspace method based on the delay unit vector.

[0024] The multi-target perception method, system, electronic device and storage medium provided by the present invention transmit an OFDM signal to an intelligent metasurface by using a transmitting antenna, and the OFDM signal is transmitted by the intelligent metasurface to multiple targets and then reflected by each target to a receiving antenna, wherein the OFDM signal includes a first set number of time frames, each time frame includes a second set number of OFDM symbols, each OFDM symbol includes a third set number of subcarriers, and the intelligent metasurface is configured with a fourth set number of transmission array elements, which are used to control the input OFDM symbols to be output into beam signals through beamforming; obtaining the OFDM signals reflected to the receiving antenna; The OFDM reflected signal of the line is processed jointly for the beam signal contained in each time frame of the OFDM transmission signal to obtain the target parameter vector estimation value of each subcarrier of the corresponding frame, the delay unit vector is obtained based on the target parameter vector estimation value, the delay unit vector is coherently accumulated to obtain the delay spectrum, the delay spectrum includes the fifth set number of discrete values, each discrete value corresponds to a delay unit, and the target is judged based on each discrete value whether there is a target in each delay unit, and the distance of the target is calculated for the delay unit with the target; for the delay unit with the target, the angle of each target is calculated based on the delay unit vector using the subspace method. In this case, the OFDM signal is transmitted to the smart metasurface by the transmitting antenna, and the OFDM signal is transmitted to the multiple targets by the smart metasurface and then reflected to the receiving antenna by each target. Considering the beamforming gain of the smart metasurface in the time domain, the OFDM reflected signal is processed and calculated to obtain the distance and angle of the target, thereby improving the perception accuracy and perception resolution of the multiple targets.

[0025] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0027] Figure 1 A schematic diagram of a flow chart of a multi-target perception method provided by an embodiment of the present invention;

[0028] Figure 2 A model diagram of the intelligent metasurface-assisted multi-target perception method provided in an embodiment of the present invention;

[0029] Figure 3 A transmission protocol diagram of the intelligent metasurface assisted multi-target perception method provided by an embodiment of the present invention;

[0030] Figure 4 A performance comparison chart of the success rate of multi-target detection between multi-beam joint processing under space-time beamforming and single-beam processing under spatial domain beamforming provided by an embodiment of the present invention;

[0031] Figure 5 A comparison diagram of the range spectra of multi-beam joint processing under space-time beamforming and single-beam processing under spatial domain beamforming provided by an embodiment of the present invention;

[0032] Figure 6 An angular spectrum diagram of multi-beam joint processing under space-time beamforming provided by an embodiment of the present invention;

[0033] Figure 7 A block diagram of a multi-target perception device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0035] The following describes a multi-target perception method and device according to an embodiment of the present invention with reference to the accompanying drawings.

[0036] The embodiment of the present invention provides a multi-target perception method to improve the perception accuracy and perception resolution of multiple targets. The multi-target perception method proposed in the present invention is an intelligent metasurface-assisted multi-target perception method, which can be applied to a synaesthesia integration system. The synaesthesia integration system generally includes a synaesthesia integration transceiver equipped with a single transmitting antenna and a single receiving antenna and a transmissive intelligent metasurface.

[0037] Figure 1 A flowchart of a multi-target perception method provided by an embodiment of the present invention.

[0038] like Figure 1 As shown, the multi-target perception method includes the following steps:

[0039] Step S101, using a transmitting antenna to transmit an OFDM signal to the smart metasurface, the OFDM signal is transmitted by the smart metasurface to multiple targets and then reflected by each target to a receiving antenna.

[0040] In step S101, an OFDM (Orthogonal Frequency Division Multiplexing) signal sent by a transmitting antenna includes a first set number T of time frames, each time frame includes a second set number M of OFDM symbols, and each OFDM symbol includes a third set number N of subcarriers.

[0041] In step S101, the smart metasurface is configured with a fourth set number of transmission array elements, which are used to control the input OFDM symbols to be output into beam signals through beamforming. The second set number is equal to the fourth set number, and the space-time beamforming codebook of each transmission array element of the smart metasurface is an orthogonal codebook.

[0042] Specifically, step S101 of the embodiment of the present invention is a signal transmission stage, and the specific content of this stage is as follows:

[0043] Figure 2 This is a model diagram of the intelligent super surface assisted multi-target perception method provided by the embodiment of the present invention. Figure 2 As shown in the figure, in the signal transmission stage, the transmitting antenna transmits the OFDM signal to the smart metasurface, the OFDM signal is transmitted by the smart metasurface to multiple targets, and then reflected by each target to form an OFDM reflected signal, which is received by the receiving antenna. The entire signal transmission stage contains T time frames that can be coherently accumulated, and each time frame contains M OFDM symbols. The number of subcarriers in each OFDM symbol is N, that is, the number of subcarriers of the OFDM signal is N, and the subcarrier spacing is Δf.

[0044] The smart metasurface is configured with L transmission elements, L = L y ×L z .L y is the number of transmission array elements arranged in a row of the smart metasurface, L z The number of transmission array elements arranged in a row of the smart metasurface. Each transmission array element of the smart metasurface has a corresponding beamforming vector, and all beamforming parameters of the smart metasurface remain unchanged within an OFDM symbol time. The set of all M beamforming vectors used by the M OFDM symbols in each time frame is called the space-time beamforming vector of the smart metasurface, which can be expressed as ξ=[ξ1 T , ..., ξ m T , ..., ξ M T ] T , where ξ m is the smart metasurface beamforming vector corresponding to the mth OFDM symbol in any time frame, and m is 1, 2, …, M. ξ m T For m The transpose of . T Indicates transpose.

[0045] In the signal transmission stage, the number of OFDM symbols in each time frame satisfies M=L. M is the second set number (i.e., the number of OFDM symbols in each time frame), and L is the fourth set number (i.e., the number of transmission array elements included in the smart metasurface). The space-time beamforming codebook of each transmission array element of the smart metasurface is an orthogonal codebook, that is, any two smart metasurface beamforming vectors satisfy:

[0046]

[0047] In the formula, and They are the smart metasurface beamforming vectors corresponding to the m1th OFDM symbol and the m2th OFDM symbol in the same time frame respectively. for The conjugate transpose of .

[0048] In this embodiment, a discrete Fourier transform matrix or a Hadamard matrix can be used as a space-time beamforming codebook of the smart metasurface to optimize the perception performance of the method of the present invention.

[0049] a) Space-time beamforming codebook based on discrete Fourier transform matrix:

[0050] For the mth OFDM symbol in a time frame, m=(l1-l)L z +l2, the beamforming vector of the smart metasurface corresponding to the mth OFDM symbol can be expressed as:

[0051]

[0052] Among them, F Y and F Z The size is L y ×L y and L z ×L z The discrete Fourier transform matrix of Represents F Y The l1th column of Represents F Z The l2th column of . represents the Kronecker product. D，m Represents the smart metasurface beamforming vector corresponding to the mth OFDM symbol based on the discrete Fourier transform matrix.

[0053] b) Space-time beamforming codebook based on Hadamard matrix:

[0054] For the mth OFDM symbol in a certain time frame, the beamforming vector of the smart metasurface corresponding to the mth OFDM symbol can be expressed as:

[0055]

[0056] Among them, ξ H,m is the smart metasurface beamforming vector corresponding to the mth OFDM symbol based on the Hadamard matrix. had is a Hadamard matrix of size L×L, [H had ] m Represents H had The elements in the Hadamard matrix only contain +1 and -1, which can provide 1-bit discrete phase adjustment corresponding to π and -π. At the same time, since not all Hadamard matrices of arbitrary sizes exist, when using the Hadamard matrix as a space-time beamforming codebook, the size of the smart metasurface must meet the size of the Hadamard matrix.

[0057] In the signal transmission stage, the OFDM signal is transmitted through the intelligent metasurface to obtain a transmission signal. After the OFDM symbol in each time frame in the OFDM signal is transmitted through the intelligent metasurface, the corresponding beam signal (referred to as beam) of the corresponding time frame in the transmission signal is obtained. Since the transmission does not change the number of time frames and the number of subcarriers, the transmission signal includes a first set number T of time frames, and each time frame contains a second set number M of beam signals. All beams in each time frame are a space-time beamforming vector. Each beam signal includes N subcarriers.

[0058] In the signal transmission stage, the OFDM reflected signal is obtained by reflecting the transmitted signal at multiple targets. Since the reflection does not change the number of time frames and the number of subcarriers, the OFDM transmission signal includes a first set number T of time frames, each of which contains a second set number of beam signals. Each beam signal includes N subcarriers. Figure 3 Transmission protocol diagram of the intelligent metasurface assisted multi-target perception method provided in an embodiment of the present invention. Figure 3 The figure shows the transmission protocol diagram of the OFDM reflected signal. The OFDM transmission signal includes T time frames, namely time frame 1, ..., time frame T, each time frame includes M beams (respectively beam 1, ..., beam M), T time frames are a coherent processing interval, and the M beams of each time frame correspond to a space-time beamforming. Target detection and parameter estimation can be performed based on the OFDM reflected signal. Target detection and parameter estimation include delay domain target detection and distance estimation, as well as space-time domain angle estimation.

[0059] In the embodiment of the present invention, the received signal corresponding to the nth subcarrier of the mth OFDM symbol in the tth time frame (that is, the nth subcarrier in the tth time frame and the mth beam signal in the OFDM reflection signal) y n，m (t) can be expressed as:

[0060]

[0061] Among them, p t The transmit power on each subcarrier, G t and G r are the transmitting antenna gain and the receiving antenna gain respectively, h T2I，n For the transmitting antenna-smart metasurface channel matrix, is the smart metasurface-target-receiving antenna channel matrix, Θ m is the transmission coefficient matrix of the smart metasurface (Θ m is a diagonal matrix with diagonal elements ξ m ), x n，m (t) is the nth subcarrier of the mth OFDM symbol in the tth time frame of the OFDM signal, z n，m (t) is the noise corresponding to the nth subcarrier of the mth OFDM symbol in the tth time frame in the OFDM signal.

[0062] Step S102, obtaining the OFDM reflected signal reflected to the receiving antenna, jointly processing the beam signal contained in each time frame of the OFDM transmission signal to obtain the target parameter vector estimation value of each subcarrier of the corresponding frame, obtaining the delay unit vector based on the target parameter vector estimation value, coherently accumulating the delay unit vector to obtain the delay spectrum, the delay spectrum includes a fifth set number of discrete values, each discrete value corresponds to a delay unit, judging whether there is a target in each delay unit based on each discrete value, and calculating the distance of the target for the delay unit where the target exists;

[0063] In step S102, the beam signal contained in each time frame of the OFDM transmission signal is jointly processed to obtain the target parameter vector estimation value of each subcarrier of the corresponding frame, including: defining a target parameter vector, the target parameter vector is equal to the transpose of the smart metasurface-target-receiving antenna channel matrix; based on the target parameter vector, the form of the beam signal contained in each time frame is converted to obtain the required beam signal; based on the required beam signal, the least squares method is used for joint processing to obtain the target parameter vector estimation value of each subcarrier of the corresponding frame.

[0064] In step S102, a delay unit vector is obtained based on the target parameter vector estimate, including: obtaining the delay unit vector based on the target parameter vector estimate using an inverse discrete Fourier transform method.

[0065] In step S102, judging whether each delay unit has a target based on each discrete value includes: judging whether each delay unit has a target based on each discrete value using a binary hypothesis testing method.

[0066] In step S102, the distance of the target is calculated for the delay unit where the target exists, including: determining the delay unit index where the target exists, and calculating the distance of the target in the delay unit based on the delay unit index, the speed of light, the third set number and the subcarrier spacing.

[0067] Specifically, step S102 of the embodiment of the present invention is a delay domain target detection and distance estimation stage, and the specific content of this stage is as follows:

[0068] definition in, (·) T represents transpose;

[0069] Define the target parameter vector in, for The transposed matrix of

[0070] Then the received signal corresponding to the nth subcarrier of all OFDM symbols in the tth time frame (i.e., the nth subcarrier in all beam signals in the tth time frame of the OFDM reflection signal) is y n (t) can be expressed as:

[0071]

[0072] This expression is the desired signal form obtained after transformation based on the defined target parameter vector. To simplify the subsequent expressions, we also define Then the received signal y corresponding to the nth subcarrier of all OFDM symbols in the tth time frame is n (t) can be simplified as:

[0073] y n (t) = H n (t,ξ)d n +z n (t).

[0074] In each time frame, for y n (t) is jointly processed. Specifically, the least square method is used to jointly process the received signals in a time frame. Then the received signal y corresponding to the nth subcarrier of all OFDM symbols in the tth time frame is n The estimated value of the target parameter vector of (t) satisfies:

[0075]

[0076] In the formula, is the target parameter vector estimate of the nth subcarrier in the tth time frame (i.e., the received signal y corresponding to the nth subcarrier of all OFDM symbols in the tth time frame). n(t) target parameter vector estimate), H n The pseudo-inverse of (t, ξ). When M = L, it satisfies In addition, the target parameter vector estimate can also be estimated using atomic norm minimization (compressed sensing).

[0077] The delay unit vector is obtained based on the target parameter vector estimate. Specifically, the target parameter vector estimate is subjected to an inverse discrete Fourier transform to obtain the delay unit vector of the i-th delay unit:

[0078]

[0079] In the formula, g i (t) is the delay unit vector of the i-th delay unit in the t-th time frame, N is the third set number (i.e., the number of subcarriers), It is the estimated value of the target parameter vector of the nth subcarrier in the tth time frame. For T time frames, T corresponding delay unit vectors can be obtained, and the T corresponding delay unit vectors are coherently accumulated to obtain the delay spectrum finally used for target detection. The delay spectrum includes discrete values ​​of the fifth set number N0, and the fifth set number (that is, the number of discrete values ​​of the delay spectrum) N0 is equal to the number of subcarriers N. Each discrete value corresponds to a delay unit. For example, the i-th discrete value corresponds to the i-th delay unit. The discrete values ​​in the delay spectrum can be regarded as the detection statistics of the corresponding delay units. The detection statistics of the i-th delay unit (that is, the discrete value corresponding to the i-th delay unit) can be expressed as:

[0080]

[0081] In the formula, g i is the discrete value corresponding to the i-th delay unit, is the azimuth, γ D is the pitch angle, T is the first setting number, N is the third setting number, L is the fourth setting number, is the array response vector of the smart metasurface, is the transpose of the array response vector of the smart metasurface, g i (t) is the delay unit vector corresponding to the t-th time frame and the i-th delay unit. Each detection statistic is obtained by exhaustive search, where the azimuth angle and the elevation angle are in the interval Search on.

[0082] The i-th delay unit satisfies:

[0083]

[0084] In the formula, τ iis the i-th delay unit, i is the delay unit index, N is the third set number (ie, the number of subcarriers), and Δf is the subcarrier spacing.

[0085] A constant false alarm detector is used to detect whether there is a target on each delay unit. Specifically, a binary hypothesis test is used to detect whether there is a target in the i-th delay unit. The binary hypothesis test can be expressed as:

[0086]

[0087] In the formula, it is assumed that Indicates that there is a target in the i-th delay unit, assuming represents that there is no target in the i-th delay unit, and κ is the detection threshold. The detection threshold is set according to the false alarm rate. When the noise power at the receiving end is σ 2 , the false alarm rate is P FA , the detection threshold can be set as:

[0088]

[0089] in, is the noise power after least squares, β 2 is the path loss from the transmitting antenna to the smart metasurface. η(P FA ) is the detection threshold coefficient, and its value is determined by the false alarm rate. The mapping relationship between the two is obtained by numerical method.

[0090] Filter out the delay unit where the target is determined, determine the corresponding delay unit index, and calculate the distance of the target in the delay unit based on the delay unit index, light speed, the third set number and the subcarrier spacing. If the distance of the target in the i-th delay unit satisfies:

[0091]

[0092] Where c is the speed of light.

[0093] Step S103: For the time delay units with targets, the angle of each target is calculated by using the subspace method based on the time delay unit vector.

[0094] In step S103, for the delay units with targets, the angles of the targets are calculated based on the delay unit vectors by using the subspace method, including: for any delay unit with targets, the delay unit vectors of the delay unit are preprocessed by using the forward and backward spatial smoothing technology to obtain the covariance matrix after spatial smoothing; based on the covariance matrix after spatial smoothing, the angle spectrum of the targets in the delay unit is obtained to obtain the angles of the targets in the delay unit, and then the angles of the targets in all the delay units with targets are obtained. Wherein, the angle spectrum of the targets in the delay unit is obtained based on the covariance matrix after spatial smoothing, including: eigenvalue decomposition of the covariance matrix after spatial smoothing of the delay unit; based on the eigenvalues, the eigenvector is obtained to obtain the angle spectrum of the targets in the delay unit.

[0095] Specifically, step S103 of the embodiment of the present invention is a space-time domain angle estimation stage, and the specific content of this stage is as follows:

[0096] The time domain degrees of freedom provided by the intelligent metasurface space-time beamforming are used to make up for the lack of spatial domain degrees of freedom at the receiving end, and the angle of the target in the delay unit where the target exists is estimated. The delay unit vector of each time frame is obtained, and the corresponding delay unit vector under T time frames is T signal samples. Based on the T signal samples, the receiving end uses the subspace method to achieve super-resolution estimation of the angle of multiple targets.

[0097] Specifically, in the delay unit where the target exists, the angle of the target is obtained using the subspace method. First, if there is a target in the ith delay unit, the delay unit vector g of the iith delay unit in the tth time frame is smoothed using the forward and backward spatial smoothing technique. i (t) pre-processing. Pre-processing refers to g i (t) can be regarded as a received signal vector on a virtual receiving array. The virtual array has the same configuration as the smart metasurface. The virtual array is divided into J subarrays, each of which is equipped with L sub The received signal vector of the jth subarray in the tth time frame can be expressed as g i，j (t).g i，j The covariance matrix R of (t) i，j It can be approximated as:

[0098]

[0099] In the formula, g i，j The conjugate transpose of (t), is the covariance function.

[0100] Then the covariance matrix R after spatial smoothing is i It can be expressed as:

[0101]

[0102] In the formula, I v It is a commutative matrix, the elements on the anti-diagonal are 1, and the elements in other positions are all 0. For R i，j The conjugation of.

[0103] The covariance matrix R after spatial smoothing i Perform eigenvalue decomposition:

[0104] R i =UΣU H

[0105] Among them, U is a square matrix, U H is the conjugate transpose of U. and For R i The eigenvalues ​​of are arranged in descending order. Then the angle spectrum of the target in the i-th time delay unit can be expressed as:

[0106]

[0107] In the formula, is the angle spectrum of the target in the i-th time delay unit, is the transpose of the array response vector of the smart metasurface, is the azimuth angle, and γ is the elevation angle. For L sub -K i eigenvectors, corresponding to R i L sub -K i The smallest eigenvalue. i is the number of targets in the ith time delay unit. Finally, the angle of the target is obtained by searching for the peak of the angle spectrum.

[0108] In order to verify the effect of the method of the present invention, the following verification was performed.

[0109] The configuration is as follows: the intelligent metasurface adopts a transmissive intelligent metasurface. The number of intelligent metasurface array elements L = 8 × 8, the distance from the transmitting antenna to the intelligent metasurface is 0.1 meters, the number of targets is 3, the carrier frequency is 28 GHz, the subcarrier interval Δf = 240 kHz, the number of subcarriers N = 3333, the number of time frames T = 10, the transmission signal is random, and the modulation method is Quadrature Phase Shift Keying (QPSK).

[0110] Figure 4This is a performance comparison chart of the success rate of multi-target detection under multi-beam joint processing under space-time beamforming and single beam processing under spatial beamforming provided by an embodiment of the present invention. Figure 5 This is a comparison diagram of the range spectra of multi-beam joint processing under space-time beamforming and single beam processing under spatial domain beamforming provided by an embodiment of the present invention. Figure 6 Angular spectrum of multi-beam joint processing under space-time beamforming provided by an embodiment of the present invention.

[0111] In the simulation, the distances of the three targets are randomly and uniformly distributed on [30, 70] meters, and the angles are Randomly and uniformly distributed. Figure 4 The horizontal axis is the number of time frames T, and the vertical axis is the detection success rate. Figure 4 It can be seen from the figure that the detection success rate increases with the increase of T, because the coherent accumulation of multiple time frames can significantly improve the signal-to-noise ratio of the target echo signal (i.e., the reflected signal). In addition, single beam 1 and single beam 2 are designed for different false alarm rates P. FA The detection success rate curve obtained by single beam processing under spatial beamforming. Multi-beam 1 and multi-beam 2 are for different false alarm rates P FA The detection success rate curve obtained by multi-beam joint processing under the space-time beamforming of the present invention is shown in Figure 2 at different false alarm rates P. FA The multi-beam joint processing method under the proposed space-time beamforming can improve the success rate of multi-target detection in the delay domain, especially when the false alarm rate is small. This proves that the method of the present invention can significantly improve the multi-target detection performance.

[0112] Figure 5 The horizontal axis is the distance (meters), and the vertical axis is the normalized amplitude (dB). Figure 5 It can be seen that there are three obvious peaks in the distance spectrum, corresponding to the distances of the three targets. In addition, the peaks of the distance spectrum under the proposed multi-beam joint processing method under space-time beamforming are more obvious, proving that the method of the present invention can provide better performance in distance perception.

[0113] In the simulation, the two targets are located in the same range unit, with the pitch angle of 0 degrees and the azimuth angles of 0 degrees and 8 degrees respectively. Figure 6 The three coordinates are the elevation angle, azimuth angle and normalized amplitude (dB). Figure 6 It can be seen from the figure that there are two peaks in the angle spectrum, corresponding to the angles of the two targets. In addition, the target angle interval is 8 degrees, which is less than the beam width, proving that the method of the present invention can achieve super-resolution angle estimation.

[0114] Therefore, it is proved through verification that the intelligent metasurface-assisted multi-target perception method proposed in the present invention can realize multi-target detection and distance and angle estimation using OFDM signals. The proposed multi-beam joint processing method under space-time beamforming can significantly improve the detection success rate and distance estimation performance of multiple targets, and can also realize super-resolution estimation of multi-target angles.

[0115] In order to implement the above embodiment, the present invention also proposes a multi-target perception device.

[0116] Figure 7 A block diagram of a multi-target perception device provided in an embodiment of the present invention.

[0117] like Figure 7 As shown, the multi-target sensing device includes a multi-target sensing unit 11 and a computing unit 12, wherein:

[0118] The multi-target sensing unit 11 includes a transmitting antenna, a smart metasurface and a receiving antenna; the transmitting antenna is used to transmit an OFDM signal to the smart metasurface, wherein the OFDM signal includes a first set number of time frames, each time frame includes a second set number of OFDM symbols, and each OFDM symbol includes a third set number of subcarriers; the smart metasurface is configured with a fourth set number of transmission array elements, and the transmission array elements are used to control the input OFDM symbols to be output into beam signals through beamforming; the OFDM signal is transmitted from the smart metasurface to multiple targets and then reflected by each target to the receiving antenna; the receiving antenna is used to receive the OFDM reflection signal reflected by each target;

[0119] The calculation unit 12 is used to obtain the OFDM reflected signal reflected to the receiving antenna, jointly process the beam signal contained in each time frame of the OFDM transmission signal to obtain the target parameter vector estimation value of each subcarrier of the corresponding frame, obtain the delay unit vector based on the target parameter vector estimation value, coherently accumulate the delay unit vector to obtain the delay spectrum, the delay spectrum includes a fifth set number of discrete values, each discrete value corresponds to a delay unit, based on each discrete value, it is judged whether there is a target in each delay unit, and the distance of the target is calculated for the delay unit with the target; for the delay unit with the target, the subspace method is used to calculate the angle of each target based on the delay unit vector.

[0120] Furthermore, in a possible implementation of an embodiment of the present invention, in the multi-target perception unit 11, the second set number is equal to the fourth set number, and the space-time beamforming codebook of each transmission array element of the intelligent metasurface is an orthogonal codebook.

[0121] Furthermore, in a possible implementation of an embodiment of the present invention, in the calculation unit 12, the beam signal contained in each time frame of the OFDM transmission signal is jointly processed to obtain a target parameter vector estimate of each subcarrier of the corresponding frame, including: defining a target parameter vector, the target parameter vector is equal to the transpose of the smart metasurface-target-receiving antenna channel matrix; based on the target parameter vector, the form of the beam signal contained in each time frame is converted to obtain a desired beam signal; based on the desired beam signal, a least squares method is used for joint processing to obtain a target parameter vector estimate of each subcarrier of the corresponding frame.

[0122] Further, in a possible implementation manner of the embodiment of the present invention, in the calculation unit 12, obtaining the delay unit vector based on the target parameter vector estimate includes: using an inverse discrete Fourier transform method to obtain the delay unit vector based on the target parameter vector estimate.

[0123] Furthermore, in a possible implementation of the embodiment of the present invention, in the calculation unit 12, judging whether each delay unit has a target based on each discrete value includes: judging whether each delay unit has a target based on each discrete value using a binary hypothesis testing method.

[0124] Furthermore, in a possible implementation of an embodiment of the present invention, in the calculation unit 12, the distance of the target is calculated for the delay unit where the target exists, including: determining the delay unit index where the target exists, and calculating the distance of the target in the delay unit based on the delay unit index, the speed of light, a third set number and the subcarrier spacing.

[0125] Furthermore, in a possible implementation of an embodiment of the present invention, in the calculation unit 12, for the delay units where targets exist, a subspace method is used based on the delay unit vector to calculate the angle of each target, including: for any delay unit where targets exist, preprocessing the delay unit vector of the delay unit using a forward and backward spatial smoothing technique to obtain a covariance matrix after spatial smoothing; obtaining an angle spectrum of the target in the delay unit based on the covariance matrix after spatial smoothing to obtain the angle of the target in the delay unit, and then obtaining the angle of the target in all delay units where targets exist.

[0126] Furthermore, in a possible implementation method of an embodiment of the present invention, in the calculation unit 12, the angle spectrum of the target in the delay unit is obtained based on the covariance matrix after spatial smoothing, including: performing eigenvalue decomposition on the covariance matrix after spatial smoothing of the delay unit; obtaining eigenvectors based on the eigenvalues ​​and then obtaining the angle spectrum of the target in the delay unit.

[0127] It should be noted that the aforementioned explanation of the multi-target perception method embodiment is also applicable to the multi-target perception device of this embodiment and will not be repeated here.

[0128] In an embodiment of the present invention, an OFDM signal is transmitted to a smart metasurface by using a transmitting antenna, and the OFDM signal is transmitted by the smart metasurface to multiple targets and then reflected by each target to a receiving antenna, wherein the OFDM signal includes a first set number of time frames, each time frame includes a second set number of OFDM symbols, each OFDM symbol includes a third set number of subcarriers, and the smart metasurface is configured with a fourth set number of transmission array elements, and the transmission array elements are used to control the input OFDM symbols to output beam signals through beamforming; the OFDM reflection signal reflected to the receiving antenna is obtained, and the beam signal contained in each time frame of the OFDM transmission signal is jointly processed to obtain a target parameter vector estimate value of each subcarrier of the corresponding frame, a delay unit vector is obtained based on the target parameter vector estimate value, and the delay unit vector is coherently accumulated to obtain a delay spectrum, the delay spectrum includes a fifth set number of discrete values, each discrete value corresponds to a delay unit, and it is judged whether each delay unit has a target based on each discrete value, and the distance of the target is calculated for the delay unit with the target; for the delay unit with the target, the angle of each target is calculated based on the delay unit vector using a subspace method. In this case, the transmitting antenna is used to transmit the OFDM signal to the smart metasurface. The OFDM signal is transmitted by the smart metasurface to multiple targets and then reflected by each target to the receiving antenna. Considering the beamforming gain of the smart metasurface in the time domain, the OFDM reflected signal is processed and calculated to obtain the distance and angle of the target, thereby improving the perception accuracy and resolution of multiple targets.

[0129] The method proposed in the present invention uses OFDM signals to realize the perception function, jointly processes the received signals under multiple beams, and uses the gain of the space-time beamforming of the intelligent metasurface to improve the perception accuracy and perception resolution of multiple targets. Specifically, in the signal transmission stage, the transmitting antenna transmits the OFDM signal to the intelligent metasurface, and the OFDM signal is transmitted by the intelligent metasurface to the target, and then reaches the receiving antenna after being reflected by the target. The entire signal transmission stage includes T time frames that can be coherently accumulated, and each time frame includes M OFDM symbols. The beamforming of the intelligent metasurface remains unchanged within an OFDM symbol time and is mutually orthogonal on different symbols. In order to meet the time domain orthogonality of beamforming, a discrete Fourier transform matrix or a Hadamard matrix is ​​used as the space-time beamforming codebook of the intelligent metasurface. In the delay domain target detection and distance estimation stage, the delay spectrum finally used for target detection is obtained. The discrete values ​​in the delay spectrum can be regarded as the detection statistics of the corresponding delay unit. A constant false alarm detector is used to detect whether there is a target on each discrete delay unit, and the target distance is estimated at the same time. In the space-time domain angle estimation stage, the time-domain degrees of freedom provided by the space-time beamforming of the intelligent metasurface is used to compensate for the lack of space-domain degrees of freedom at the receiving end, and the target angle in the delay unit where the target exists is estimated. The results obtained by processing in T time frames are regarded as T signal samples. Based on the T signal samples, the subspace method is used to achieve super-resolution estimation of multi-target angles.

[0130] In order to implement the above embodiments, the present invention also proposes an electronic device, comprising: a processor, and a memory connected to the processor for communication; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the target detection and parameter estimation process of the above embodiments.

[0131] In order to implement the above embodiments, the present invention further proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0132] In order to implement the above embodiments, the present invention further proposes a computer program product, including a computer program, which implements the target detection and parameter estimation process provided by the above embodiments when executed by a processor.

[0133] In the description of the aforementioned embodiments, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0134] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0135] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0136] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0137] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0138] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0139] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0140] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A multi-target perception method, characterized in that: include: An OFDM signal is transmitted to the smart metasurface by using a transmitting antenna, and the OFDM signal is transmitted by the smart metasurface to multiple targets and then reflected by each target to a receiving antenna, wherein the OFDM signal includes a first set number of time frames, each time frame includes a second set number of OFDM symbols, each OFDM symbol includes a third set number of subcarriers, and the smart metasurface is configured with a fourth set number of transmission array elements, and the transmission array elements are used to control the input OFDM symbols to be output into beam signals through beamforming; Obtain an OFDM reflected signal reflected to a receiving antenna, perform joint processing on a beam signal contained in each time frame of the OFDM transmit signal to obtain a target parameter vector estimate of each subcarrier of the corresponding frame, obtain a delay unit vector based on the target parameter vector estimate, perform coherent accumulation on the delay unit vector to obtain a delay spectrum, wherein the delay spectrum includes a fifth set number of discrete values, each discrete value corresponds to a delay unit, determine whether there is a target in each delay unit based on each discrete value, and calculate the distance of the target for the delay unit where the target exists; For the time delay units with targets, the angle of each target is calculated by using the subspace method based on the time delay unit vector.

2. The multi-target perception method according to claim 1, characterized in that: The second set number is equal to the fourth set number, and the space-time beamforming codebook of each transmission array element of the smart metasurface is an orthogonal codebook.

3. The multi-target perception method according to claim 1, characterized in that: The jointly processing the beam signal contained in each time frame of the OFDM transmission signal to obtain the target parameter vector estimation value of each subcarrier of the corresponding frame includes: Defining a target parameter vector, wherein the target parameter vector is equal to the transpose of the smart metasurface-target-receiving antenna channel matrix; Based on the target parameter vector, the form of the beam signal contained in each time frame is transformed to obtain the required beam signal; Based on the desired beam signal, a least square method is used for joint processing to obtain an estimated value of a target parameter vector of each subcarrier of the corresponding frame.

4. The multi-target perception method according to claim 1, characterized in that: The obtaining of the delay unit vector based on the target parameter vector estimate value comprises: obtaining the delay unit vector based on the target parameter vector estimate value using an inverse discrete Fourier transform method.

5. The multi-target perception method according to claim 1, characterized in that: The discrete value corresponding to the i-th delay unit satisfies: In the formula, g i is the discrete value corresponding to the i-th delay unit, is the azimuth, γ D is the pitch angle, T is the first setting number, N is the third setting number, L is the fourth setting number, is the transpose of the array response vector of the smart metasurface, g i (t) is the delay unit vector corresponding to the t-th time frame and the i-th delay unit.

6. The multi-target perception method according to claim 1, characterized in that: Judging whether each delay unit has a target based on each discrete value includes: judging whether each delay unit has a target based on each discrete value using a binary hypothesis testing method.

7. The multi-target perception method according to claim 1, characterized in that: The distance of the target is calculated for the delay unit where the target exists, including: Determine the delay unit index where the target exists, and calculate the distance of the target in the delay unit based on the delay unit index, the speed of light, the third set number and the subcarrier spacing.

8. The multi-target perception method according to claim 1, characterized in that: The method of calculating the angle of each target by using a subspace method based on the delay unit vector for the delay unit having the target includes: For any time delay unit with a target, the time delay unit vector of the time delay unit is preprocessed by using forward and backward spatial smoothing technology to obtain a covariance matrix after spatial smoothing; The angle spectrum of the target in the time delay unit is obtained based on the covariance matrix after spatial smoothing to obtain the angle of the target in the time delay unit, and then the angle of the target in all the time delay units where the target exists is obtained.

9. The multi-target perception method according to claim 8, characterized in that: The step of obtaining the angle spectrum of the target in the time delay unit based on the spatially smoothed covariance matrix includes: Performing eigenvalue decomposition on the spatially smoothed covariance matrix of the time delay unit; The eigenvalues ​​are used to obtain eigenvectors and then the angle spectrum of the target in the time delay unit is obtained.

10. A multi-target sensing device, characterized in that: Including multi-target perception unit and calculation unit; The multi-target sensing unit includes a transmitting antenna, a smart metasurface and a receiving antenna; the transmitting antenna is used to transmit an OFDM signal to the smart metasurface, wherein the OFDM signal includes a first set number of time frames, each time frame includes a second set number of OFDM symbols, and each OFDM symbol includes a third set number of subcarriers; the smart metasurface is configured with a fourth set number of transmission array elements, and the transmission array elements are used to control the input OFDM symbols to be output into beam signals through beamforming; the OFDM signal is transmitted by the smart metasurface to multiple targets and then reflected by each target to the receiving antenna; the receiving antenna is used to receive the OFDM reflection signal reflected by each target; The calculation unit is used to obtain the OFDM reflection signal reflected to the receiving antenna, jointly process the beam signal contained in each time frame of the OFDM transmission signal to obtain the target parameter vector estimation value of each subcarrier of the corresponding frame, obtain the delay unit vector based on the target parameter vector estimation value, coherently accumulate the delay unit vector to obtain the delay spectrum, the delay spectrum includes a fifth set number of discrete values, each discrete value corresponds to a delay unit, based on each discrete value, it is judged whether each delay unit has a target, and the distance of the target is calculated for the delay unit with the target; for the delay unit with the target, the angle of each target is calculated by using the subspace method based on the delay unit vector.

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