Auxiliary vehicle-mounted millimeter wave radar detection method and device based on intelligent reflecting surface wide beam forming, and medium

Abstract

The invention discloses an auxiliary vehicle-mounted millimeter-wave radar detection method and device based on intelligent reflecting surface wide beam forming and a medium, and the method comprises the steps: S1, building a system model for auxiliary vehicle-mounted millimeter-wave radar detection based on intelligent reflecting surface wide beam forming, and enabling millimeter-wave radar antennas and intelligent reflecting surfaces to be uniform planar arrays, meanwhile, a detection area is given; s2, constructing a channel model and an intelligent reflector beam forming optimization problem; s3, according to the given detection area, calculating the span of the detection area on the spatial frequency; s4, calculating the number of sub-arrays required by beam forming, the beam direction of the sub-arrays and the common phase based on the spatial frequency span of the detection area obtained in the step S2; and S5, according to the parameters obtained in the step S3, calculating the wide beam reflection phase shift of the intelligent reflection surface for realizing auxiliary detection. According to the method, the potential target detection performance of the vehicle-mounted millimeter wave radar in a shielding scene can be remarkably improved, and the signal real-time processing complexity is reduced.

Description

Technical Field

[0001] The present invention relates to the field of automotive millimeter-wave radar detection technology, and in particular to a method, device and medium for assisting vehicle-mounted millimeter-wave radar detection based on intelligent reflection surface wide beam forming. Background Art

[0002] With the rapid development of intelligent car assisted driving technology, on-board millimeter-wave radar has become an indispensable sensor in vehicle perception systems due to its all-weather working ability and strong anti-interference performance. However, in actual road scenes, when the target detected by the radar is blocked by objects such as road corners, buildings, and large vehicles, the detection performance of the radar will be significantly reduced. This obstruction will not only weaken the intensity of the target echo signal received by the radar, but may also cause the multipath effect of the signal, making target detection more difficult. Especially in complex environments such as urban roads and intersections, the obstruction problem is more common, which seriously affects the safety and reliability of the assisted driving system and the driving process.

[0003] At present, the industry mainly adopts the following technical solutions to improve radar detection performance in occlusion scenarios: First, enhance signal penetration capability by increasing radar transmit power and optimizing receiving sensitivity, but this method is easily limited by power consumption and may violate relevant regulatory requirements; Second, use advanced signal processing algorithms such as adaptive threshold detection and Doppler compensation to improve the detection rate of weak targets, but the algorithm performance is still difficult to guarantee under severe occlusion conditions; Third, use a multi-radar collaborative perception strategy to expand the perception range by increasing the number of radar installations and optimizing the layout, but this solution not only significantly increases the system cost, but also brings technical difficulties such as sensor calibration and data fusion; Fourth, combine data from other sensors such as vision and lidar for multi-modal fusion, but the reliability of this solution under severe weather conditions still needs to be improved.

[0004] In summary, existing radar detection technologies mostly rely on radar’s own algorithm optimization and multi-sensor fusion methods, which can improve its detection performance under occlusion conditions. However, the technology is complex and costly, and there are obvious shortcomings. Therefore, it is considered to introduce external equipment and adopt appropriate algorithms to improve the radar detection performance in this scenario. Summary of the invention

[0005] In order to solve at least one of the technical problems existing in the prior art to a certain extent, the purpose of the present invention is to provide a method, device and medium for assisting vehicle-mounted millimeter-wave radar detection based on intelligent reflective surface wide beamforming. By designing a suitable intelligent reflective surface reflection coefficient to perform wide beamforming on the radar detection wave, it is possible to detect potential targets in a given detection area that is blocked by objects (i.e., the formed line-of-sight detection blind area), which has the advantages of being simple and easy to operate, strong real-time performance, and significant detection effect.

[0006] The first technical solution adopted by the present invention is as follows:

[0007] A method for detecting potential targets when the direct detection signal of a vehicle-mounted millimeter-wave radar is blocked by an object, which is applied to the detection of potential targets when the direct detection signal of a vehicle-mounted radar is blocked by an object. The method includes a vehicle-mounted millimeter-wave radar with M antennas, an intelligent reflecting surface with N passive reflecting units, and an intelligent reflecting surface controller. The controller adjusts the reflection coefficients of the passive reflecting units of the intelligent reflecting surface and stores some preset parameters. The method specifically includes the following steps:

[0008] S1. Establish a system model for detecting a vehicle-mounted millimeter-wave radar assisted by wide-beam shaping of an intelligent reflecting surface, where both the millimeter-wave radar antenna and the intelligent reflecting surface are uniform planar arrays, and a detection area is given at the same time;

[0009] S2. Construct a channel model and an intelligent reflecting surface beamforming optimization problem;

[0010] S3. Calculate the span of the detection area in spatial frequency according to the given detection area;

[0011] S4. Based on the spatial frequency span of the detection area obtained in step S2, calculate the number of subarrays required for beamforming, the beam directions of the subarrays, and the common phase;

[0012] S5. Calculate the wide-beam reflection phase shift for the intelligent reflecting surface to achieve assisted detection according to the parameters obtained in step S3.

[0013] Further, step S1 includes:

[0014] The system model includes an intelligent reflecting surface installed at a position with a height of H0 (such as a utility pole, traffic light, etc.) and having N = N x ×N y passive reflecting units, a moving intelligent vehicle carrying a vehicle-mounted millimeter-wave radar with M = M x ×M y radar antennas, the height of the radar is H1, and the detection area where the line-of-sight detection of the radar is blocked

[0015] Taking the ground as the xoy plane and the vertical projection of the lower left corner unit of the intelligent reflecting surface on it as the origin, a three-dimensional Cartesian coordinate system is established. Then M x and M y respectively represent the radar antennas distributed along the x-axis and y-axis, N x and N y respectively represent the passive reflecting units distributed along the x-axis and y-axis, and the spacing between the antennas and between the passive reflecting units is d e; The reference coordinates of the lower left corner of the intelligent reflecting surface, the coordinates of the millimeter-wave radar at time t, and the center coordinates of the detection area are n = [0, 0, H0] T , p0 = [0, y0, 0] T ; L x and L y respectively represent the length and width of the detection area , then any point in the detection area is expressed as p = [p x , p y , 0] T , and Therefore, the distances from the radar to the intelligent reflecting surface and from the intelligent reflecting surface to any point in the detection area are expressed as: and d T = ||p - n||, the superscript (·) T is defined as the transpose operation, and ||·|| is defined as the Euclidean norm; the initial reflection coefficient of the intelligent reflecting surface is set as Θ [t] = diag(θ [t] ), and 1 ≤ n x ≤ N x , 1 ≤ n y ≤ N y ;

[0016] For the relationship between the Angle of Arrival (AoA) and the Angle of Departure (AoD) in the system, let β R (r [t] , n) and α R (r [t] , n] respectively represent the zenith AoA and the azimuth AoA between the radar and the intelligent reflecting surface; the zenith AoD and the azimuth AoD from the intelligent reflecting surface to any point in the detection area are represented by β T (p, n) and α T (p, n) respectively.

[0017] Furthermore, the step S2 includes:

[0018] Based on the system model obtained in step S1, the real-time spatial frequencies along the x-axis and y-axis at the radar antenna plane are expressed as:

[0019] Ψ R (r [t] , n) = sin(β R (r [t] , n))cos(α R (r [t], n))

[0020] Ω R (r [t] , n) = sin(β R (r [t] , n))sin(α R (r [t] , n))

[0021] Then the transmit array response vector of the radar is expressed as:

[0022]

[0023] where λ is the radar detection wavelength and ||a R (r [t] , n)|| 2 = M, the one-dimensional steering vector e(φ, N) = [1, e -jπφ , …, e -jπ(N-1)φ T , denotes the Kronecker product; the real-time spatial frequencies along the x-axis and y-axis at the intelligent reflecting surface are expressed as:

[0024]

[0025] Then the receive array response vector of the intelligent reflecting surface is expressed as:

[0026]

[0027] Based on this, the direct detection channels from the radar to the intelligent reflecting surface and from the intelligent reflecting surface to any point within the detection area are respectively expressed as:

[0028]

[0029] where is the Doppler frequency generated by the radar when the moving speed is ν, and are the complex path gains of the link, c0 is the channel power gain when the reference distance is 1 meter and the superscript (·) H is defined as the operation of taking the conjugate transpose;

[0030] Assume the signal transmitted by the radar is A represents the amplitude of the signal, f c represents the carrier frequency of the signal, l represents the linear frequency modulation vector, φ0 represents the initial phase, then the power of the radar is: P = A 2 / 2;

[0031] Meanwhile, the total response matrix of potential targets is​ Denote the radar cross section of the potential target, then the target reflection signal received at the radar is:

[0032]

[0033] where is additive white Gaussian noise with zero mean and variance at time t; after the radar performs Doppler compensation through its internal processor and eliminates the self-reflection part of the IRS, the received signal-to-noise ratio of the radar is expressed as:

[0034]

[0035] where Based on this, the intelligent reflecting surface beamforming problem is equivalent to solving the following optimization problem:

[0036]

[0037] Furthermore, the step S3 includes:

[0038] According to the channel model established in S2 and the calculated parameters, the minimum and maximum spatial frequency deviations along the x-axis related to the detection area are:

[0039]

[0040]

[0041] Then the spatial span of the detection area along the x-axis is:

[0042] Δ span，x (n)=Δ max，x (n)-Δ min，x (n)

[0043] The spatial span of the detection area along the y-axis is:

[0044]

[0045] Furthermore, the step S4 includes:

[0046] Calculate the number of sub-arrays along the x-axis and y-axis to achieve wide beamforming:

[0047]

[0048] where κ ∈ {x, y}, Denote rounding up; thus, further calculate the sub-array beam directions along the x-axis and y-axis and the common phase, which are respectively:

[0049]

[0050] where is the number of passive reflection units included in each sub-array, and there is

[0051] Furthermore, the step S5 includes:

[0052] According to the parameters obtained in step S4, first calculate the phase shifts of the passive reflection units of the intelligent reflecting surface along the x-axis and y-axis respectively:

[0053]

[0054] where Then, the phase shift of the nth passive reflection unit is obtained by the following formula:

[0055]

[0056] Thus, the solution to the optimization problem is completed, that is, the wide-beam shaping design of the intelligent reflecting surface is completed.

[0057] The second technical solution adopted by the present invention is:

[0058] An electronic device, the electronic device includes a processor and a memory, and at least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement a method for assisting vehicle-mounted millimeter-wave radar detection based on wide-beam shaping of an intelligent reflecting surface as described above.

[0059] The third technical solution adopted by the present invention is:

[0060] A computer-readable storage medium, at least one instruction, at least one program, a code set or an instruction set is stored in the storage medium, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement a method for assisting vehicle-mounted millimeter-wave radar detection based on wide-beam shaping of an intelligent reflecting surface as described above.

[0061] The fourth technical solution adopted by the present invention is:

[0062] A computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to enable the computer device to execute the above-mentioned method.

[0063] The present invention has the following advantages and effects compared with the prior art:

[0064] 1) A method for intelligent reflecting surface wide-beam shaping-assisted vehicle-mounted millimeter-wave radar detection proposed by the present invention, compared with traditional technologies, this method avoids the problems of high cost and high energy consumption brought by traditional sensor fusion and other solutions, greatly reduces the cost and energy consumption, and significantly improves the detection effect of potential targets by the vehicle-mounted radar in occluded scenarios.

[0065] 2) A method for intelligent reflecting surface wide-beam shaping-assisted vehicle-mounted millimeter-wave radar detection proposed by the present invention does not require additional power transmission overhead. Only by presetting the detection area and obtaining the relative position between the vehicle and the intelligent reflecting surface can the corresponding reflection coefficient of the intelligent reflecting surface be calculated. Compared with existing methods, this method avoids the disadvantages of increasing the number of sensors and large energy consumption, thereby improving the detection effect of blind area targets.

[0066] 3) A method for intelligent reflecting surface wide-beam shaping-assisted vehicle-mounted millimeter-wave radar detection proposed by the present invention is a closed-form solution and does not require iterative calculation, greatly reducing the computational complexity, being able to better meet the real-time processing requirements under vehicle motion conditions, and having lower requirements for hardware performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following introduces the related technical solution drawings in the embodiments of the present invention or the prior art. It should be understood that the drawings introduced below are only for conveniently and clearly expressing some embodiments of the technical solutions in the present invention. For those skilled in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0068] Figure 1 is a system model diagram of the method for intelligent reflecting surface wide-beam shaping-assisted vehicle-mounted millimeter-wave radar detection in the embodiment of the present invention;

[0069] Figure 2 is a flowchart of a method for intelligent reflecting surface wide-beam shaping-assisted vehicle-mounted millimeter-wave radar detection according to the present invention;

[0070] Figure 3 is a performance comparison simulation diagram in Embodiment 1 of the present invention;

[0071] Figure 4 It is another performance comparison simulation diagram in Embodiment 1 of the present invention. Detailed implementation manners

[0072] The embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention and should not be construed as limiting the present invention. For the step numbers in the following embodiments, they are only set for the convenience of description and illustration, and no limitation is imposed on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0073] In the description of the present invention, it should be understood that with regard to the orientation description, such as the orientation or positional relationship indicated by up, down, front, back, left, right, etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as limiting the present invention.

[0074] In the description of the present invention, the meaning of several is one or more, the meaning of multiple is two or more, greater than, less than, exceeding, etc. are understood as not including the present number, and above, below, within, etc. are understood as including the present number. If there is a description of first and second, it is only for the purpose of distinguishing technical features and should not be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence relationship of the indicated technical features.

[0075] In the description of the present invention, unless otherwise clearly defined, words such as setting, installing, connecting, etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above words in the present invention in combination with the specific content of the technical solution.

[0076] See Figure 1 , Figure 1 is a model diagram of an intelligent reflecting surface wide-beam shaping assisted vehicle-mounted millimeter-wave radar detection system in all embodiments of the present invention. The assisted detection system includes an intelligent reflecting surface installed at a position with a height of H0 (such as a utility pole, traffic light, etc.) and having N = N x ×N y passive reflection units, a moving intelligent vehicle equipped with a vehicle-mounted millimeter-wave radar with M = M x ×M y radar antennas (height H1) and a detection area where the radar line-of-sight detection is blocked

[0077] To illustrate the technical advancement of the method of the present invention, on the MATLAB platform, the method of wide-beam shaping assisted vehicle-mounted millimeter-wave radar detection based on intelligent reflecting surface proposed by the present invention and other reflection phase shift optimization designs are compared in different embodiments for the radar receiving signal-to-noise ratio of the system. Among them, other designs include: 1) One-dimensional beamforming: Only perform beam phase shift design on one dimension of the intelligent reflecting surface, and keep the same phase shift for the other dimension; 2) Discrete Fourier Transform (DFT) codebook search method: The reflection phase shift of the intelligent reflecting surface is searched in the codebook based on the discrete Fourier transform to maximize the radar receiving signal-to-noise ratio; To better understand the above technical solutions, the following will combine the accompanying drawings of the specification and specific implementation manners to describe in more detail a method of wide-beam shaping assisted vehicle-mounted millimeter-wave radar detection based on intelligent reflecting surface disclosed in this embodiment.

[0078] Embodiment 1

[0079] As Figure 1 shown, the embodiment of the present invention is based on a wide-beam shaping assisted vehicle-mounted millimeter-wave radar detection system using an intelligent reflecting surface, and its specific system design is as follows:

[0080] Unless otherwise specified, in this embodiment, it is assumed that the installation heights of the intelligent reflecting surface and the radar on the moving vehicle are H0 = 16.5 meters and H1 = 1.5 meters respectively, the radar deploys M = 4×4 = 16 transmit / receive antennas and the coordinates of the radar are r [t] =[30, 8, 1.5] T , the reference coordinates of the intelligent reflecting surface are n = [0, 0, 16.5] T and there are N = 20×20 = 400 passive reflection units, the length and width of the detection area are L x = 10 meters, L y = 50 meters and p0 = [0, 25, 0] T , there is a single target in the detection area and its radar cross section is 0 dBsm. At the same time, it is assumed that the millimeter-wave radar operates at a frequency of 77 GHz, and the element interval of the intelligent reflecting surface is set to d e = λ / 10. For each independent link, the reference path gain at 1 meter is c0 = -20 dB, and the transmit power of the radar is set to P = 30 dBm.

[0081] The following will combine Figure 2 , and specifically describe a method of wide-beam shaping assisted vehicle-mounted millimeter-wave radar detection disclosed in the embodiment, including the following steps:

[0082] S1. Establish a system model for intelligent reflecting surface wide-beam shaping assisted vehicle-mounted millimeter-wave radar detection, where both the millimeter-wave radar antenna and the intelligent reflecting surface are uniform planar arrays, and a detection area is given;

[0083] S2. Construct a channel model and an intelligent reflecting surface beamforming optimization problem;

[0084] S3. Calculate the span of the detection area in spatial frequency according to the given detection area;

[0085] S4. Based on the spatial frequency span of the detection area obtained in step S2, calculate the number of sub-arrays required for beamforming, the beam directions of the sub-arrays, and the common phase;

[0086] S5. Calculate the wide-beam reflection phase shift for the intelligent reflecting surface to achieve assisted detection according to the parameters obtained in step S3.

[0087] In this embodiment, step S1 is specifically implemented as follows:

[0088] In this embodiment, the system includes an intelligent reflecting surface with N = N x ×N y passive reflection units installed at a position with a height of H0 (such as a utility pole, traffic light, etc.), and a moving intelligent vehicle equipped with a vehicle-mounted millimeter-wave radar with M = M x ×M y radar antennas (the height is H1) and a detection area where the radar line-of-sight detection is blocked Taking the ground as the xoy plane and the vertical projection of the lower left corner unit of the intelligent reflecting surface on it as the origin, a three-dimensional Cartesian coordinate system is established. Then M x (N x ) and M y (N y ) respectively represent the radar antennas (passive reflection units) distributed along the x-axis and y-axis, and the spacing between the antennas (passive reflection units) is d e . From the above parameters, the reference coordinates of the lower left corner of the intelligent reflecting surface, the coordinates of the millimeter-wave radar at time t, and the center coordinates of the detection area A are n = [0, 0, H0] T , P0 = [0, y0, 0] T . According to the length L and width L x of the detection area y , any point in the detection area can be expressed as p = [p x , p y , 0] T , and Therefore, the distances from the radar to the intelligent reflecting surface and from the intelligent reflecting surface to any point within the detection area are expressed as and d T = ||p - n||, the superscript (·) T is defined as the transpose operation, and ||·|| is defined as the Euclidean norm. Set the initial reflection coefficient of the intelligent reflecting surface as Θ [t] = diag(θ [t] ), and 1 ≤ n x ≤ N x ,1 ≤ n y ≤ N y ,and this reflection coefficient is updated as the remaining steps of this method are completed.

[0089] In addition, for the relationship between the Angle of Arrival (AoA) and the Angle of Departure (AoD) in the system, let β R (r [t] , n) and α R (r [t] , n) represent the zenith AoA and azimuth AoA between the radar and the intelligent reflecting surface respectively. Similarly, the zenith AoD and azimuth AoD from the intelligent reflecting surface to any point within the detection area are represented by β T (p, n) and α T (p, n) respectively.

[0090] In this embodiment, step S2 is specifically implemented as follows:

[0091] Based on the system model obtained in step S1, the real-time spatial frequencies along the x-axis and y-axis at the radar antenna plane are expressed as:

[0092] Ψ R (r [t] , n) = sin(β R (r [t] , n))cos(α R (r [t] , n))

[0093] Ω R (r [t] , n) = sin(β R (r [t] , n))sin(α R (r [t] , n))

[0094] Then the transmit array response vector of the radar is expressed as:

[0095]

[0096] Wherein, λ is the radar detection wavelength and there is ||a R (r [t] , n)|| 2 = M, the one-dimensional steering vector e(φ, N) = [1, e -jπφ , …, e -jπ(N-1)φ T , denotes the Kronecker product. Similarly, the real-time spatial frequencies along the x-axis and y-axis at the intelligent reflecting surface are expressed as:

[0097]

[0098] Then the received array response vector of the intelligent reflecting surface is expressed as:

[0099]

[0100] Based on this, the direct detection channels from the radar to the intelligent reflecting surface and from the intelligent reflecting surface to any point within the detection area can be respectively expressed as:

[0101]

[0102] where is the Doppler frequency generated by the radar when the moving speed is v, and are the complex path gains of the link, c0 is the channel power gain when the reference distance is 1 meter and the superscript (·) H is defined as the operation of taking the Hamiltonian transpose. Assume the signal transmitted by the radar is:

[0103]

[0104] where, A represents the amplitude of the signal, f c represents the carrier frequency of the signal, l represents the chirp vector, φ0 represents the initial phase, then the power of the radar is P = A 2 / 2. At the same time, the total response matrix of the potential target is represents the radar cross section of the potential target. Then the target reflection signal received at the radar is:

[0105]

[0106] where is the additive Gaussian white noise with zero mean and variance at time t. After the radar performs Doppler compensation through its internal processor and eliminates the self-reflection part of the IRS, the received signal-to-noise ratio of the radar can be expressed as:

[0107] ​

[0108] Among them Based on this, the intelligent reflecting surface beamforming problem can be equivalently transformed into solving the following optimization problem:

[0109]

[0110]

[0111] In this embodiment, step S3 is specifically implemented as follows:

[0112] According to the channel model established in step S2 and the calculated parameters, the minimum and maximum spatial frequency deviations along the x-axis related to the detection area are:

[0113]

[0114] Then the spatial span of the detection area along the x-axis is:

[0115] Δ span，x (n)=Δ max，x (n)-Δ min，x (n)

[0116] Similarly, the spatial span of the detection area along the y-axis is:

[0117]

[0118] In this embodiment, step S4 is specifically implemented as follows:

[0119] Calculate the number of sub-arrays along the x-axis and y-axis for realizing wide beamforming:

[0120]

[0121] where κ ∈ {x, y}, denotes rounding up. From this, the sub-array beam directions and the common phase along the x-axis and y-axis can be further calculated, which are respectively:

[0122]

[0123] where is the number of passive reflection units included in each sub-array, and there is

[0124] In this embodiment, step S5 is specifically implemented as follows:

[0125] From the parameters obtained in step S4, first calculate the phase shifts of the passive reflection units of the intelligent reflecting surface along the x-axis and y-axis respectively:

[0126]

[0127] wherein the phase shift of the nth passive reflection unit can be obtained by the following formula:

[0128]

[0129] Thus, the solution to the aforementioned optimization problem is completed, that is, the wide-beam shaping design of the intelligent reflecting surface is completed.

[0130] As Figure 3 shown, Figure 3 the relationship between the number of different reflection units in the intelligent reflecting surface-assisted vehicle-mounted millimeter-wave radar detection system and the worst received signal-to-noise ratio (SNR) of the radar is plotted. In the method of the embodiment of the present invention, when the number of reflection units is the same, the worst received SNR of the radar is significantly higher than that of the discrete Fourier transform codebook method and the one-dimensional beamforming method. In addition, in terms of the change in the worst received SNR of the radar, the gap between the method in this embodiment and the other two methods gradually increases with the increase in the number of passive units, which verifies the effectiveness of the method for the vehicle-mounted millimeter-wave radar detection system based on the wide-beam shaping of the intelligent reflecting surface proposed in the present invention in improving the detection of the radar blind area.

[0131] As Figure 4 shown, Figure 4 the relationship between different radar transmission powers and the worst received SNR of the radar in the intelligent reflecting surface-assisted vehicle-mounted millimeter-wave radar detection system is plotted. It can be found that as the power of the vehicle-mounted millimeter-wave radar increases, the worst received SNR of all methods will increase with it, which is expected because a stronger detection beam can be formed after a larger detection power passes through the intelligent reflecting surface. However, the method of the embodiment of the present invention has the best performance, which is attributed to the fact that this method can make the radar detection signal cover the detection area as evenly as possible. In particular, when the radar transmission power increases in this embodiment, the worst received SNR of the method in this embodiment has an average increase of 34.64% and 128.66% compared with the discrete Fourier transform codebook method and the one-dimensional beamforming method, respectively.

[0132] In summary, the method for the vehicle-mounted millimeter-wave radar detection based on the wide-beam shaping of the intelligent reflecting surface proposed in the present invention can significantly improve the target detection effect of the vehicle-mounted millimeter-wave radar in the line-of-sight detection blind area, thereby greatly improving the reliability and safety of intelligent assisted driving.

[0133] Embodiment 2

[0134] An embodiment of the present invention further provides an electronic device, which includes a processor and a memory. At least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement as Figure 2 a vehicle-mounted millimeter-wave radar detection method assisted by intelligent reflecting surface wide-beam shaping as shown.

[0135] It can be understood that the memory may include a random access memory (RAM), or may also include a read-only memory (ROM). Optionally, the memory includes a non-transitory computer-readable storage medium. The memory can be used to store instructions, programs, codes, code sets or instruction sets. The memory may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing an operating system, instructions for at least one function, instructions for implementing the above method embodiments, etc.; the data storage area may store data created according to the use of the server, etc.

[0136] The processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts within the entire server, and by running or executing instructions, programs, code sets or instruction sets stored in the memory, and calling data stored in the memory, it executes various functions of the server and processes data. Optionally, the processor may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor may integrate one or a combination of several of a central processing unit (CPU) and a modem, etc. Among them, the CPU mainly processes the operating system and application programs, etc.; the modem is used to process wireless communication. It can be understood that the above modem may not be integrated into the processor and may be implemented separately by a single chip.

[0137] Since this electronic device is the electronic device corresponding to a vehicle-mounted millimeter-wave radar detection method assisted by intelligent reflecting surface wide-beam shaping in an embodiment of the present invention, and the principle of solving problems by this electronic device is similar to that of this method, the implementation of this electronic device can refer to the implementation process of the above method embodiment, and the repeated parts will not be described again.

[0138] Example 3

[0139] The embodiment of the present invention also provides a computer-readable storage medium, in which at least one instruction, at least one program, a code set or an instruction set is stored, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement as Figure 2 a vehicle-mounted millimeter-wave radar detection method assisted by intelligent reflecting surface wide-beam shaping as shown.

[0140] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and this program can be stored in a computer-readable storage medium. The storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electrically-erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc memories, a magnetic disc memory, a tape memory, or any other computer-readable medium capable of carrying or storing data.

[0141] Since this storage medium is the storage medium corresponding to the vehicle-mounted millimeter-wave radar detection method assisted by intelligent reflecting surface wide-beam shaping in the embodiment of the present invention, and the principle of solving problems by this storage medium is similar to that of this method, the implementation of this storage medium can refer to the implementation process of the above method embodiment, and the repeated parts will not be described again.

[0142] Example 4

[0143] In some possible embodiments, aspects of the method of the embodiments of the present invention can also be implemented in the form of a program product, which includes program code. When the program product runs on a computer device, the program code is used to cause the computer device to execute the steps of a method for assisting vehicle-mounted millimeter-wave radar detection based on intelligent reflecting surface wide-beam shaping according to various exemplary embodiments of the present application described above in this specification. Among them, the executable computer program code or "code" for executing each embodiment can be written in high-level programming languages such as C, C++, C#, Smalltalk, Java, JavaScript, VisualBasic, structured query language (e.g., Transact-SQL), Perl, or in various other programming languages.

[0144] It should be understood that each part of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple 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, any one or a combination of the following technologies well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0145] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection 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 can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0146] The above embodiments are only for illustrating the technical concept and characteristics of the present invention, and their purpose is to enable those of ordinary skill in the art to understand the content of the present invention and implement it accordingly, and cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the essence of the content of the present invention should be covered by the protection scope of the present invention.

Claims

1. A vehicle-mounted millimeter-wave radar detection method based on intelligent reflective surface wide beamforming assistance, characterized in that: The following steps are involved: S1. Establish a system model of intelligent reflective surface wide beamforming assisted vehicle-mounted millimeter-wave radar detection, where both the millimeter-wave radar antenna and the intelligent reflective surface are uniform planar arrays, and the detection area is given; S2, construct channel model and intelligent reflection surface beamforming optimization problem; S3, according to the given detection area, calculating its span in spatial frequency; S4, based on the spatial frequency span of the detection area obtained in step S2, calculating the number of subarrays required for beamforming, the subarray beam direction and the common phase; S5. Calculate the wide-beam reflection phase shift of the intelligent reflection surface to achieve auxiliary detection based on the parameters obtained in step S3.

2. The method for detecting vehicle-mounted millimeter-wave radar based on intelligent reflective surface wide beam forming as claimed in claim 1, characterized in that: The step S1 comprises: The system model includes a node installed at a height of H0 and with N = N x ×N y A smart reflective surface with M=M passive reflective units, a moving smart car equipped with a x ×M y The vehicle-mounted millimeter-wave radar with a radar antenna, the radar height is H1, and the detection area where the radar line of sight detection is blocked A three-dimensional Cartesian coordinate system is established with the ground as the xoy plane and the vertical projection of the lower left corner unit of the smart reflective surface on it as the origin, then M x and M y Respectively represent the radar antennas distributed along the x-axis and y-axis, N x and N y represent the passive reflection units distributed along the x-axis and y-axis respectively, and the spacing between the antennas and the passive reflection units is d e ; Reference coordinates of the lower left corner of the intelligent reflective surface, coordinates of the millimeter-wave radar at time t, and detection area The center coordinates are n = [0, 0, H0] T , p0=[0,y0,0] T ; L x and L y Respectively represent the detection area The length and width of the detection area, any point in the detection area is expressed as p = [p x , p y ,0] T ,and Therefore, from the radar to the smart reflective surface and from the smart reflective surface to the detection area The distance to any point in is expressed as: and d T =‖pn‖, superscript (·) T is defined as taking the transpose operation, ‖·‖ is defined as taking the Euclidean norm; the initial reflection coefficient of the smart reflective surface is set to Θ [t] =diag(θ [t] ),and For the relationship between the arrival angle and departure angle in the system, let β R (r [t] , n) and α R (r [t] , n) represent the zenith AoA and azimuth AoA between the radar and the smart reflector; the smart reflector to the detection area The zenith AoD and azimuth AoD of any point in the T (p, n) and α T (p, n) represent respectively.

3. The method for detecting vehicle-mounted millimeter-wave radar based on intelligent reflective surface wide beam forming as claimed in claim 2, characterized in that: The step S2 comprises: Based on the system model obtained in step S1, the real-time spatial frequency along the x-axis and the y-axis at the radar antenna plane is expressed as: P R (r [t] ,n)=sin(β R (r [t] ,n))cos(α R (r [t] ,n)) Oh R (r [t] ,n)=sin(β R (r [t] ,n))sin(a R (r [t] ,n)) Then the radar's transmit array response vector is expressed as: in, λ is the radar detection wavelength and ||a R (r [t] , n)|| 2 =M, one-dimensional steering vector e(φ,N)=[1,e -jπφ ,…,e -jπ(N-1)φ ] T , represents the Kronecker product; the real-time spatial frequency along the x-axis and the y-axis at the smart reflection surface is expressed as: Then the receiving array response vector of the smart reflector is expressed as: Based on this, from radar to smart reflective surface and from smart reflective surface to detection area The direct detection channel of any point in is expressed as: in is the Doppler frequency generated by the radar when the moving speed is v, and is the complex path gain of the link, c0 is the channel power gain at a reference distance of 1 meter and Superscript (·) H Defined as taking the Hamiltonian transpose operation; Assume that the signal sent by the radar is A represents the amplitude of the signal, f c represents the carrier frequency of the signal, l represents the linear frequency modulation vector, φ0 represents the initial phase, then the power of the radar is: P = A 2 / 2; At the same time, the total response matrix of the potential target is represents the radar cross-section of the potential target, then the target reflection signal received at the radar is: in The mean at time t is zero and the variance is Additive Gaussian white noise; after the radar performs Doppler compensation through its own internal processor and eliminates the IRS self-reflection part, the radar's receiving signal-to-noise ratio is expressed as: in Based on this, the smart reflector beamforming problem is equivalent to solving the following optimization problem:

4. The method for detecting vehicle-mounted millimeter-wave radar based on intelligent reflective surface wide beam forming as claimed in claim 3, characterized in that: The step S3 comprises: According to the channel model established by S2 and the calculated parameters, the detection area The associated minimum and maximum spatial frequency deviations along the x-axis are: The detection area The spatial span along the x-axis is: D span，x (n)=Δ max，x (n)-D min，x (n) Detection area The spatial span along the y-axis is:

5. The method for detecting vehicle-mounted millimeter-wave radar based on intelligent reflective surface wide beam forming as claimed in claim 4, characterized in that: The step S4 comprises: Calculate the number of subarrays along the x-axis and y-axis to achieve wide beamforming: where κ∈{x,y}, Indicates rounding up; the subarray beam direction and common phase along the x-axis and y-axis are further calculated, which are: in is the number of passive reflector elements contained in each sub-array, and 6. The method for detecting vehicle-mounted millimeter-wave radar based on intelligent reflective surface wide beam forming as claimed in claim 1, characterized in that: The step S5 comprises: According to the parameters obtained in step S4, the phase shifts of the passive reflection units of the smart reflection surface along the x-axis and the y-axis are calculated respectively: in Then the phase shift of the nth passive reflector unit is obtained by the following formula: At this point, the solution to the optimization problem is completed, that is, the wide beamforming design of the smart reflector is completed.

7. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the method according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that: The storage medium stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the method according to any one of claims 1 to 6.

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