High-Resolution Beamforming Method for MIMO Arrays Based on Single-Bit Transmission

Abstract

The present invention provides a high-resolution beamforming method for MIMO arrays based on single-bit transmission, which relates to the technical field of array signal processing. This method models the single-bit array signal for a narrowband LFM waveform with random phase. By considering the multi-channel time-delay characteristics, the quantized high-order frequency-domain characteristics, and the high-order spatial frequency characteristics, a unified spatio-temporal-frequency-domain model is constructed to analyze the harmonic mechanism and the spatial dispersion effect, thus improving the single-bit quantization theory. Subsequently, on the basis of the traditional SIMO mode, single-bit quantization is further considered for the transmitting end of the array to obtain decorrelated array transmission signals, and high-precision quantization and matched filtering are adopted for each channel at the receiving end. Thus, the design of the MIMO array signal processing framework based on single-bit transmission is completed. The present invention realizes low-power and high-precision digital beamforming through single-bit quantization and transmission processing of MIMO array signals.

Description

Technical Field

[0001] The present invention relates to the technical field of array signal processing, and particularly to a high-resolution beamforming method for a MIMO (Multiple Input Multiple Output) array based on single-bit transmission. Background Art

[0002] With the rapid development of the intelligent transportation industry, autonomous vehicles need to perceive the surrounding environment and road conditions in real time. Vehicle-mounted millimeter-wave radars have to undertake different tasks such as "warning" and "gazing" in a dynamic environment. They not only need to perform a wide range of scans on specific distances in a specific area to detect potential obstacles or threats, but also need to continuously track the detected targets. The former requires a wide beam coverage range, and the latter requires a high beam resolution. This requires millimeter-wave array radars to have sufficient beam resources and reasonable allocation to assist autonomous driving decision-making and thus improve driving safety. However, with the continuous improvement of the autonomous driving level, the detection requirements and the difficulty of perception tasks are constantly increasing, followed by the growth of hardware costs and the computing power challenges of massive data. The future vehicle-mounted millimeter-wave radar solutions for the whole vehicle will surely not be at the cost of infinitely increasing the number of radars and the hardware resources of a single radar.

[0003] The existing beamforming technology based on single-bit transmission simplifies the hardware complexity significantly by quantifying the signal to one bit and only retaining the positive and negative sign information. The core of its technical solution lies in using a single-bit quantizer and a switched power amplifier to replace the traditional high-precision digital-to-analog converter and linear power amplifier, optimizing the beam pointing through precise control of the signal phase, and combining algorithms to compensate for the signal loss introduced by quantization. This technology has obvious advantages in hardware implementation, including reducing the manufacturing cost, data storage and transmission overhead, and significantly improving the energy efficiency of the system. It is applicable to scenarios such as low-power Internet of Things, satellite communication, and low-cost radars. However, due to the loss of the amplitude information of the signal, the signal quality of the system has decreased significantly, and the quantization noise has led to insufficient beam gain and sidelobe suppression performance. In addition, single-bit signals are extremely sensitive to the noise environment, and the performance degrades severely in low signal-to-noise ratio scenarios. Nevertheless, the beamforming technology based on single-bit transmission has great potential in low-power and resource-constrained scenarios, and still needs further improvement in terms of high resolution, dynamic adaptability, and signal processing efficiency. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to re-analyze the impact of single-bit quantization on array signals and propose a MIMO array high-resolution beamforming method based on single-bit transmission, aiming to reduce the software and hardware costs of the vehicle-mounted radar system and improve data processing efficiency under the premise of not sacrificing the vehicle-mounted radar perception capability (detection performance for long-distance targets or weak targets and scanning capability and resolution within a certain angle range) as much as possible through single-bit quantization technology.

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

[0006] Based on the above purpose, in a first aspect, the present invention provides a MIMO array high-resolution beamforming method based on single-bit transmission, comprising the following steps:

[0007] Step 1: Construct a single-bit array signal time-frequency-space domain model, model the single-bit array signal for the narrowband LFM waveform with random phase, build a unified time-space-frequency domain model, and analyze the harmonic mechanism and spatial dispersion effect; use the inverse sine theorem to construct the correlation function after signal quantization, and perform Fourier series expansion, consider the covariance matrix of the array signal, and expand the signal model from single channel to multi-channel;

[0008] Step 2: Construct a MIMO array signal processing framework based on single-bit transmission, use single-bit quantization on the array's transmitter, and use high-precision quantization and matched filtering on each channel at the receiver. Weighted synthesize the matched filtering results of the N×M channels to complete the construction of the MIMO array signal processing framework based on single-bit transmission.

[0009] As a further solution of the present invention, before using the inverse sine theorem to construct the correlation function after signal quantization, the energy density of the original signal model is set to The uniform noise has a spectrum range of ; According to the Wiener-Khinchin theorem, the correlation function of the signal before single-bit quantization is:

[0010]

[0011] In the formula, represents the center frequency of the RF receiver, represents half of the total bandwidth of the received signal, Stands for time delay, which is used to describe the time delay between two signals; Represents a frequency of The phase change of the sinusoidal signal depends on the time delay ;

[0012] With the help of the inverse sine theorem, the correlation function of the quantized signal is:

[0013]

[0014] In the formula, when tends to 0, the minimum period , and the one-bit correlation is represented by Fourier series expansion.

[0015] As a further solution of the present invention, when tends to 0, is an even-period triangular wave, and the Fourier series expansion of the real part of the quantized signal is:

[0016]

[0017] Among them, is the DC component of the signal, representing the average value of the signal in one period; is the Fourier cosine coefficient, representing the amplitude of the th-order cosine component in the signal; is the Fourier sine coefficient, representing the amplitude of the th-order component in the signal;

[0018]

[0019] The DC component is 0, is an even function, and for all , is all 0.

[0020] As a further solution of the present invention, when tends to 0, is an odd-period triangular wave, and the Fourier series expansion of the imaginary part of the quantized signal is:

[0021]

[0022] Among them, is the DC component of the signal, representing the average value of the signal in one period; is the Fourier cosine coefficient, representing the amplitude of the th-order cosine component in the signal; is the Fourier sine coefficient, representing the amplitude of the th-order component in the signal;

[0023]

[0024] The DC component is 0, is an odd function, and for all , is all 0.

[0025] As a further aspect of the present invention, when expanding the signal model from a single channel to multiple channels, consider a linear array composed of array elements, each element having a digital channel; wherein, if only a stationary process signal propagating in one space is incident on the array, when the receiving bandwidth approaches 0, the covariance matrix of the unquantized array signal is expressed as:

[0026]

[0027] wherein, is the power, is the array response vector of the signal incident from ;

[0028] is a matrix of rank one, the correlation between the element and the element is:

[0029]

[0030] wherein, represents the time delay between the element and the element. After quantization using one bit, the covariance matrix between the element and the element represents the spatial correlation between the element and the element and is interpreted as the time correlation at the element:

[0031]

[0032] wherein, represents the quantized signal received by the th channel, represents the conjugate complex form of the signal received by the th channel and is adjusted for time delay.

[0033] As a further aspect of the present invention, substituting the correlation function after signal quantization into the covariance matrix formula, the arcsine law is used to expand the array signal to form a one-dimensional covariance matrix:

[0034]

[0035] The operator acts on each element itself, as well as the real and imaginary parts of each element;

[0036] When approaching 0, substituting into the Fourier series expansion formula of the real part of the quantized signal and the Fourier series expansion formula of the imaginary part of the quantized signal, we get The array element and The spatial correlation function between array elements is:[[]]END]]

[0037]

[0038] And substituting into And The formula of, we get:

[0039]

[0040] By comparing with The array element and The correlation between array elements, the form of the single-bit covariance matrix is similarly expressed as the covariance matrix of the unquantized array signal:[[]]END]]

[0041]

[0042] Where,[[]]END]] Represents the power of the th-order signal,[[]]END]] Represents the th-order covariance matrix of the signal.[[]]END]]

[0043] As a further solution of the present invention, the single-bit covariance matrix is expressed as the sum of an infinite number of covariance matrices, and the th-order covariance matrix is:[[]]END]]

[0044]

[0045] The th-order signal power The expression is:[[]]END]]

[0046]

[0047] And the th-order steering vector of the signal is:[[]]END]]

[0048]

[0049] The spurious direction vector is:[[]]END]]

[0050]

[0051] A signal propagating in space appears as an infinite number of sub-signals, the sub-signals include the attenuated signal and the signal in the spurious direction, and the correlation matrix corresponding to the single-bit quantized signal is accumulated from multiple random signals, making is a full-rank matrix.

[0052] As a further aspect of the present invention, when weighted combining the beam from the matched filtering results of N×M channels, for N receiving channels, the received signals are processed by high-precision quantization, and M times of matched filtering are performed in parallel. Each filter corresponds to the signal of a single-bit transmitting channel; the weighted combines the beam.

[0053] As a further aspect of the present invention, a point spread function is introduced to weighted combine the beam from the matched filtering results of N×M channels. By adjusting the weights , so that the beam is in the direction of , scan within the interval, and the obtained gain curve ; is a full-rank matrix, substituting the direction into the SNR gain formula on it to obtain:

[0054]

[0055] where is determined by the phase difference between the signals of each channel of the array before single-bit quantization of transmission; is the power of the order signal; is the direction of any target; is the direction parameter that determines the weighted vector after matched filtering, and the directions of the transmitting and receiving beams can be adjusted again;

[0056] Among them, the SNR gain on the direction is expressed as:

[0057]

[0058] In the formula, is the correlation matrix of the array transmitting signals, is the steering vector of the transmitting array, is the steering vector of the receiving array, is the incoming direction of any target signal, N is the actual number of array elements of the receiving array, is the pointing direction of the beam, and the pointing direction of the beam is changed by adjusting the weighted of the filter output.

[0059] Compared with the prior art, a high-resolution beamforming method for a MIMO array based on single-bit transmission proposed by the present invention has the following beneficial effects:

[0060] The high-resolution beamforming method of the present invention mainly can be divided into two steps: First, for the narrowband LFM (Linear Frequency Modulation) waveform with random phase, the single-bit array signal is modeled. By considering the multi-channel time-delay characteristics, the quantized high-order frequency-domain characteristics, and the high-order spatial frequency characteristics, a unified spatio-temporal frequency-domain model is constructed to analyze the harmonic mechanism and the spatial dispersion effect, and the single-bit quantization theory is improved. Subsequently, on the basis of the traditional SIMO (Single Input Multiple Output) mode, single-bit quantization is further considered for the transmitting end of the array to obtain decorrelated array transmission signals, and high-precision quantization and matched filtering are adopted for each channel at the receiving end. Thus, the design of the MIMO array signal processing framework based on single-bit transmission is completed.

[0061] The present invention realizes low-power and high-precision digital beamforming through single-bit quantization and transmission processing of MIMO array signals. First, single-bit quantization significantly reduces the complexity and power consumption of analog-to-digital converters, meeting the energy efficiency requirements of intelligent driving platforms. Second, by processing the fundamental wave signal and harmonic signals in different frequency bands, not only harmonic interference is effectively avoided, but also the narrow beam characteristics of harmonics are utilized to improve the spatial resolution and achieve multi-beam high-precision beamforming. In addition, by exploring the characteristics of the wide beam coverage of the fundamental wave and the high beam resolution of harmonics, a feasible solution is provided for various task requirements such as "early warning" and "gazing" of vehicle-mounted millimeter-wave radars in intelligent driving scenarios.

[0062] These aspects or other aspects of the present application will be more clearly understood in the following description of the embodiments. It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the following will briefly introduce the drawings required for the description of the exemplary embodiments or related technologies. The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0064] Figure 1 is a flowchart of a high-resolution beamforming method for a MIMO array based on single-bit transmission according to an embodiment of the present invention.

[0065] Figure 2 is a diagram of the angular dispersion effect in a high-resolution beamforming method for a MIMO array based on single-bit transmission according to an embodiment of the present invention.

[0066] Figure 3 The figure is a comparison diagram of eigenvalues ​​of array signal correlation matrices before and after quantization in a MIMO array high-resolution beamforming method based on single-bit transmission according to an embodiment of the present invention.

[0067] Figure 4 The present invention is a block diagram of a MIMO array signal processing based on single-bit transmission in a MIMO array high-resolution beamforming method based on single-bit transmission in an embodiment of the present invention.

[0068] Figure 5 The figure is a transmission factor diagram in PSF in a comparison of conventional SIMO, orthogonal MIMO and the single-bit transmission MIMO mode proposed in the present invention in a MIMO array high-resolution beamforming method based on single-bit transmission in an embodiment of the present invention.

[0069] Figure 6 The figure is a PSF diagram for comparison of conventional SIMO, orthogonal MIMO and the single-bit transmission MIMO mode proposed in the present invention in a MIMO array high-resolution beamforming method based on single-bit transmission according to an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0071] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0072] In order to re-analyze the impact of single-bit quantization on array signals, the present invention proposes a MIMO array high-resolution beamforming method based on single-bit transmission, aiming to reduce the software and hardware costs of the vehicle-mounted radar system and improve data processing efficiency under the premise of not sacrificing the vehicle-mounted radar perception capability (detection performance for long-distance targets or weak targets and scanning capability and resolution within a certain angle range) as much as possible through single-bit quantization technology.

[0073] The present invention proposes a high-resolution beamforming method for MIMO arrays based on single-bit transmission, which can be mainly divided into two steps: First, for a narrowband LFM waveform with random phase, a single-bit array signal model is established. By considering the multi-channel time-delay characteristics, the quantized high-order frequency-domain characteristics, and the high-order spatial frequency characteristics, a unified spatio-temporal-frequency-domain model is constructed to analyze the harmonic mechanism and the spatial dispersion effect, and the single-bit quantization theory is improved. Subsequently, on the basis of the traditional SIMO mode, single-bit quantization is further considered for the transmitting end of the array to obtain decorrelated array transmission signals, and high-precision quantization and matched filtering are adopted for each channel at the receiving end. Thus, the design of the MIMO array signal processing framework based on single-bit transmission is completed.

[0074] See Figure 1 As shown, an embodiment of the present invention provides a high-resolution beamforming method for MIMO arrays based on single-bit transmission, and the method includes the following steps:

[0075] Step S10: Construct a time-frequency-spatial-domain model of the single-bit array signal.

[0076] Establish a single-bit array signal model for a narrowband LFM waveform with random phase, construct a unified spatio-temporal-frequency-domain model, analyze the harmonic mechanism and the spatial dispersion effect; use the arc sine theorem to construct the correlation function after signal quantization, and perform Fourier series expansion. Considering the covariance matrix of the array signal, the signal model is extended from a single channel to multiple channels.

[0077] Step S20: Construct an MIMO array signal processing framework based on single-bit transmission.

[0078] Adopt single-bit quantization for the transmitting end of the array, and adopt high-precision quantization and matched filtering for each channel at the receiving end. Weight and synthesize the beam from the matched filtering results of N×M channels to complete the construction of the MIMO array signal processing framework based on single-bit transmission.

[0079] In this embodiment, in step S10, when constructing the time-frequency-spatial-domain model of the single-bit array signal, it is assumed that the energy density of the original signal model is uniform noise, and the frequency spectrum range is ; According to the Wiener-Khinchin theorem, the correlation function before single-bit quantization of the signal is:

[0080]

[0081] In the formula, represents the center frequency of the RF receiver, represents half of the total bandwidth of the received signal, represents the time delay, which is used to describe the time delay between two signals; represents a frequency of The phase change of the sine signal depends on the time delay .

[0082] With the help of the arc sine theorem, the correlation function after signal quantization is as follows:

[0083]

[0084] In the formula, when tends to 0, the minimum period , and the one-bit correlation is represented by the Fourier series expansion.

[0085] When tends to 0, is an even-period triangular wave, and the Fourier series expansion of the real part of the quantized signal is:

[0086]

[0087] Among them, is the DC component of the signal, representing the average value of the signal in one period; is the Fourier cosine coefficient, representing the amplitude of the th-order cosine component in the signal; is the Fourier sine coefficient, representing the amplitude of the th-order component in the signal; represents the order of the cosine component of the signal.

[0088]

[0089] The DC component is 0, is an even function, and for all , is 0; represents the change amount of the phase of the incident signal.

[0090] Similarly, when tends to 0, is an odd-period triangular wave, and the Fourier series expansion of the imaginary part of the quantized signal is:

[0091]

[0092] Among them, is the DC component of the signal, representing the average value of the signal in one period; is the Fourier cosine coefficient, representing the amplitude of the th-order cosine component in the signal; is the Fourier sine coefficient, representing the amplitude of the th-order component in the signal; represents the imaginary part of the signal.

[0093]

[0094] DC component is 0, is an odd function, and for all , is 0; represents the minimum period of the signal.

[0095] Next, the signal model is extended from a single channel to multiple channels. When extending the signal model from a single channel to multiple channels, consider a linear array composed of array elements, and each array element has a digital channel; among them, if only a stationary process signal propagating in one space is incident on the array, when the receiving bandwidth tends to 0, the covariance matrix of the unquantized array signal is expressed as:

[0096]

[0097] where, represents the conjugate transpose operation on the vector, represents the incident direction of the signal, is the power, is from the array response vector of the signal incident; represents the conjugate transpose operation on the array response vector of the signal incident from the array.

[0098] is a matrix of rank one, the correlation between the array element and the

[0099]

[0100] where, represents the time delay between the array element and the array element. After using one-bit quantization, the covariance matrix between the array element and the array element represents the spatial correlation between the array element and is interpreted as

[0101]

[0102] where, represents the The quantized signal received by a channel represents the conjugate complex form of the signal received by the channel, and performs time delay adjustment; represents the time delay between array elements.

[0103] Substitute Equation (2) into Equation (9), that is: substitute the correlation function of the quantized signal into the covariance matrix formula, and expand the array signal of the arc sine law to form a one-dimensional covariance matrix:

[0104]

[0105] The operator on the matrix acts on each element itself, as well as the real and imaginary parts of each element;

[0106] When approaching 0, substitute Equation (3) and Equation (5), that is: substitute the Fourier series expansion formula of the real part of the quantized signal and the Fourier series expansion formula of the imaginary part of the quantized signal, to obtain the spatial correlation function between array elements is:

[0107]

[0108] Substitute Equation (4) and Equation (6), that is, substitute and formulas, to obtain:

[0109]

[0110] By comparing Equation (12) with Equation (8), and comparing the correlation between array elements, the form of the single-bit covariance matrix is similar to the covariance matrix of the unquantized array signal in Equation (7) and is expressed as:

[0111]

[0112] where represents the power of the order signal, represents the steering vector of the th signal component after quantization, represents the conjugate transpose of the transmit steering vector represents the covariance matrix of the

[0113] order signal.

[0113] The above formula (13) shows that the single-bit covariance matrix is expressed as the sum of an infinite number of covariance matrices. The -th order covariance matrix is:

[0114]

[0115] The -th order signal power expression is:

[0116]

[0117] And the -th order steering vector of the signal is:

[0118]

[0119] The spurious direction vector is:

[0120]

[0121] In the formula, represents the order of the signal component.

[0122] A signal propagating in space appears as an infinite number of sub-signals. The sub-signals include attenuated signals and signals in spurious directions. The correlation matrix corresponding to the signal after single-bit quantization is accumulated from multiple random signals, making a full-rank matrix.

[0123] Intuitively, formula (13) means that a signal propagating in space appears as an infinite number of sub-signals, which include attenuated signals and signals in spurious directions. This phenomenon is mainly caused by the angular spread due to single-bit quantization, as shown in Figure 2 . In addition, the correlation matrix corresponding to the signal after single-bit quantization is accumulated from multiple random signals, making a full-rank matrix, as shown in Figure 3 .

[0124] In step S20 of this embodiment, when constructing a signal processing framework for a MIMO array based on single-bit transmission, the single-bit transmission MIMO array refers to, based on the M channels of a traditional broadband phased array, the transmitted signal only carrying time / phase differences, generating a high-frequency modulation signal in the digital domain, using a high-speed comparator to replace a high-precision digital-to-analog converter, and outputting a single-bit signal. Therefore, the amplitude of the radio frequency signal transmitted by each channel only contains single-bit information, and the signal waveform tends to be an irregular square wave; for the N receiving channels, the received signal undergoes high-precision quantization processing, and M times of matched filtering are performed in parallel, with each filter corresponding to the signal of a single-bit transmission channel. Finally, the matched filtering results of the N×M channels are weighted. The combined beam has the overall structure as Figure 4 shown. Among them, T represents the transmitting element, R represents the receiving element, T / R represents the element shared by receiving and transmitting, and the two empty circles represent virtual elements; represents the initial phase, , , represent the phase offsets after single-bit quantization, represents conjugate processing.

[0125] In Figure 4 's working mode, the hardware advantage of the array is that at the transmitting end, a comparator is used to replace the high-precision DAC, which can improve the speed of signal digital-to-analog conversion and reduce the complex image spurs generated during the analog-to-digital conversion process. At the receiving end, single-bit matched filtering is performed on the high-precision quantized signal, and the multiplication and addition operations of the high-precision signal and the single-bit signal consume less computing resources.

[0126] Figure 4 Although the array and its signal processing method shown are similar to a MIMO array in shape, the core objective is to evaluate whether this array can obtain higher angle measurement accuracy compared to a phased array. Therefore, analyze the target angle resolution performance of the array shown in the figure from the perspective of beam synthesis. Reviewing conventional MIMO beam synthesis, for the weighted output of the matched filtering of the N×M channels , the SNR gain in the direction is expressed as:

[0127]

[0128] In the formula, the gain in this direction is jointly determined by the transmitting and receiving gains, is the correlation matrix of the array transmitted signal, is the steering vector of the transmitting array, is the steering vector of the receiving array, is the direction of arrival of any target signal, is the actual number of elements of the receiving array, is the pointing of the beam, and by adjusting the weighted output of the filtering to change the beam pointing direction; represents the transpose of the correlation matrix of the array transmitted signals, represents the steering vector in the transmission direction, which is the conjugate transpose operation on the steering vector.

[0129] To describe the angle resolution ability of the MIMO beam, in this embodiment, the point spread function (PSF, point spread function) is introduced. In formula (18), by adjusting the weights , when the beam points at , it scans within the interval, and the obtained gain curve is the PSF; this curve can reflect the gain characteristics of the beam with respect to the target direction variation, and at the same time reflect the beam's ability to resolve the target angle. Obviously, the leading factor in formula (18) is closely related to the transmitted signal, and its form depends on the array covariance matrix of the transmitted signal. Taking the traditional phased array as an example, is a rank-one matrix, where represents the direction delay vector of the transmitting array. For the matching of the target direction, substituting it into formula (18) can further simplify the expression to:

[0130]

[0131] In the formula, represents the number of elements of the transmitted signal array, represents the number of elements of the received signal array.

[0132] Taking the ideal MIMO array as an example again, if a set of complete orthogonal signal waveforms is transmitted, is a full-rank identity matrix. Substituting it into formula (18) can be simplified to:

[0133]

[0134] Comparing formula (19) and (20), it can be found that the receiving factor of the gain is the same as that of the traditional SIMO array; the transmitting factor of the phased array gain is a constant and is not affected by ; while in the ideal case, the transmitting factor of the gain of the MIMO array will vary with It changes with the change of [[ID=]], which makes the MIMO array superior to the phased array in terms of the target angular resolution. In other words, under the same transceiver array structure, the main influencing factor of the PSF is the covariance matrix of the array transmitted signals .

[0135] Next is the discussion on the transmission factor of the single-bit transmission MIMO array proposed by the present invention. As can be seen from Equation (13), is a full-rank matrix, and substituting it into Formula (18) can be simplified to:[[]]

[0136]

[0137] where is determined by the phase difference between the signals of each channel of the array before single-bit transmission quantization is the power of the -order signal; is the direction of any target; is the direction parameter that determines the weighted vector after matched filtering, and the transmission and reception beam directions can be adjusted again; represents the transmission steering vector of the th signal component in the direction after quantization, represents the carrier frequency of the transmitted signal, represents the conjugate transpose of the transmission steering vector of the th signal component after quantization.[[]]

[0138] As Figure 5 shown, the MIMO array based on single-bit transmission performs better than the traditional phased array in terms of the point spread function (PSF). That is to say, the MIMO array with single-bit transmission is superior to the general phased array in terms of the angular measurement accuracy. This is because the correlation matrix corresponding to the transmitted signals of the single-bit array is accumulated by multiple random signals, making a full-rank matrix. From another perspective, the transmission of the array can be regarded as a combination of multiple uncorrelated signals. This is different from the architecture of the traditional MIMO array where each channel transmits orthogonal signals respectively. In the latter, each channel transmits the sum signal of the fundamental wave and each harmonic wave, and there is a time delay relationship between each channel, so that the synthesized beam of the transmitted signals at each harmonic frequency points to different directions. In addition, for a high-speed moving target, a wide transmission beam and a narrow reception beam are used to achieve high spatial resolution tracking while performing wide-area search. As Figure 6As shown, the high-gain wide emission beam of the dashed line covers 6°, while multiple harmonic reception beams of the solid line are formed simultaneously, with each beam covering 2.4°. Among them, the angle covered by each beam (6° or 2.4°) can be obtained by performing a sine-value-angle transformation on the normalized emission direction covered in the figure.

[0139] In the steps of constructing the time-frequency-spatial domain model of the single-bit array signal, the present invention analyzes the characteristics of the single-bit covariance matrix. The covariance matrix after single-bit quantization can be expressed as the sum of infinitely many rank-one matrices, thereby revealing the spatial dispersion phenomenon caused by quantization. The influence of single-bit quantization on the signal can also be studied by analyzing the signal model. The processing of the signal by single-bit quantization will generate harmonic components. The direction angles and frequencies of the harmonics have a coupling relationship with the original signal, which means that the signal originally incident from the direction After quantization, it will be regarded as incident from the false direction at the harmonic frequency. This also reveals the angle dispersion effect caused by quantization.

[0140] The present invention realizes low-power and high-precision digital beamforming through single-bit quantization and transmission processing of MIMO array signals. First, single-bit quantization significantly reduces the complexity and power consumption of analog-to-digital converters, meeting the energy efficiency requirements of intelligent driving platforms. Second, by processing the fundamental wave signal and harmonic signals in different frequency bands, not only harmonic interference is effectively avoided, but also the narrow beam characteristics of the harmonics are utilized to improve the spatial resolution and achieve multi-beam high-precision beamforming. In addition, by exploring the characteristics of the wide beam coverage of the fundamental wave and the high beam resolution of the harmonics, a feasible solution is provided for various task requirements such as "warning" and "gazing" of vehicle-mounted millimeter-wave radars in intelligent driving scenarios.

[0141] It should be noted that the above-mentioned drawings are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present invention, rather than for restrictive purposes. It is easy to understand that the processes shown in the above-mentioned drawings do not indicate or limit the time sequence of these processes. Additionally, it is also easy to understand that these processes can be executed synchronously or asynchronously in, for example, multiple modules.

[0142] It should be understood that although the above is described in a certain order, these steps are not necessarily executed in the above order successively. Unless there is a clear indication in the present invention, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, a part of the steps in this embodiment may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0143] The above are exemplary embodiments disclosed by the present invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments disclosed by the present invention as defined by the claims. The functions, steps, and / or actions of the method claims according to the disclosed embodiments herein do not need to be executed in any specific order. In addition, although the elements disclosed by the embodiments of the present invention can be described or claimed in an individual form, unless clearly limited to the singular, they can also be understood as plural.

[0144] It should be understood that, unless the context clearly supports an exception, the singular form "a" in the present invention is also intended to include the plural form. It should also be understood that the "and / or" used in the present invention refers to any and all possible combinations including one or more of the associated listed items. The serial numbers of the disclosed embodiments of the present invention above are only for description and do not represent the superiority or inferiority of the embodiments.

[0145] Those of ordinary skill in the art should understand that: the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope of the embodiments disclosed by the present invention (including the claims) is limited to these examples; under the concept of the embodiments of the present invention, the technical features between the above embodiments or different embodiments can also be combined, and there are many other variations in different aspects of the above embodiments of the present invention, which are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention shall be included in the protection scope of the embodiments of the present invention.

Claims

1. A MIMO array high-resolution beamforming method based on single-bit transmission, characterized in that: The method comprises the following steps: Step 1: Construct a single-bit array signal time-frequency-space domain model, model the single-bit array signal for the narrowband LFM waveform with random phase, build a unified time-space-frequency domain model, and analyze the harmonic mechanism and spatial dispersion effect; use the inverse sine theorem to construct the correlation function after signal quantization, and perform Fourier series expansion, consider the covariance matrix of the array signal, and expand the signal model from single channel to multi-channel; Step 2: Construct a MIMO array signal processing framework based on single-bit transmission, use single-bit quantization on the array transmitter, and use high-precision quantization and matched filtering on each channel at the receiving end. Weighted synthesize beams for the matched filtering results of N×M channels to complete the construction of the MIMO array signal processing framework based on single-bit transmission; the energy density of the original signal model is set to The uniform noise has a spectrum range of ; According to the Wiener-Khinchin theorem, the correlation function of the signal before single-bit quantization is: In the formula, represents the center frequency of the RF receiver, represents half of the total bandwidth of the received signal, Stands for time delay, which is used to describe the time delay between two signals; Represents a frequency of The phase change of the sinusoidal signal depends on the time delay ; With the help of the inverse sine theorem, the correlation function of the quantized signal is: In the formula, when When it approaches 0, the minimum period , a one-bit correlation is represented by Fourier series expansion.

2. The MIMO array high-resolution beamforming method based on single-bit transmission according to claim 1, characterized in that: when Approaching 0, is an even-cycle triangular wave. The Fourier series expansion of the real part of the quantized signal is: in, It is the DC component of the signal, which represents the average value of the signal in one cycle; is the Fourier cosine coefficient, which represents the The magnitude of the cosine component of order; is the Fourier sine coefficient, which represents the The magnitude of the order component; Represents the order of the cosine component of the signal; DC component is 0, is an even function, for all , All are 0; Represents the change in the phase of the incident signal.

3. The MIMO array high-resolution beamforming method based on single-bit transmission as claimed in claim 2, characterized in that: when Approaching 0, is an odd-cycle triangular wave, and the Fourier series expansion of the imaginary part of the quantized signal is: in, It is the DC component of the signal, which represents the average value of the signal in one cycle; is the Fourier cosine coefficient, which represents the The magnitude of the cosine component of order; is the Fourier sine coefficient, which represents the The magnitude of the order component; represents the imaginary part of the signal; DC component is 0, is an odd function, for all , All are 0; Indicates the minimum period of a signal.

4. The MIMO array high-resolution beamforming method based on single-bit transmission as claimed in claim 3, characterized in that: When extending the signal model from single channel to multi-channel, consider a A linear array of array elements, each of which has a digital channel; if only a stationary process signal propagating in space is incident on the array, when the receiving bandwidth is When it approaches 0, the covariance matrix of the unquantized array signal is expressed as: in, It means to do conjugate transpose of the vector. represents the incident direction of the signal, is power, is from the array response vector of the incident signal; Expressing The incident signal array response vector is subjected to conjugate transposition processing; is a rank-one matrix, Array element and The correlation between array elements is: in, express Array element and The time delay between array elements is quantized by one bit. Array element and Covariance matrix between array elements express Array element and The spatial correlation between array elements is explained as Time correlation at the array element: in, Indicates The quantized signal received by each channel is Indicates The conjugate complex form of the signal received by each channel is adjusted for time delay; express Array element and Time delay between array elements.

5. The MIMO array high-resolution beamforming method based on single-bit transmission as claimed in claim 4, characterized in that: Substitute the correlation function of the quantized signal into the covariance matrix Formula, the inverse sine law expands the array signal to form a one-dimensional covariance matrix: Operators on matrices Acts on each element itself, as well as on the real and imaginary parts of each element; When it is close to 0, substitute the Fourier series expansion formula of the real part of the quantized signal and the Fourier series expansion formula of the imaginary part of the quantized signal, and we get Array element and The spatial correlation function between array elements is: And substitute and The formula is: Through Array element and The correlation between array elements is compared. The form of the single-bit covariance matrix is ​​similar to the covariance matrix of the unquantized array signal: in, Indicates The power of the order signal, After quantization, The steering vector of the signal components, Represents the launch steering vector The conjugate transpose of Indicates The covariance matrix of the .

6. The MIMO array high-resolution beamforming method based on single-bit transmission as claimed in claim 5, characterized in that: The single-bit covariance matrix is ​​represented as the sum of an infinite number of covariance matrices, The order covariance matrix is: No. Order signal power The expression is: And the signal The order guide vector is: The false direction vector is: In the formula, Expressed as the order of signal components, a signal propagating in space appears as an infinite number of sub-signals, which include attenuated signals and signals in false directions. The correlation matrix corresponding to the single-bit quantized signal is Multiple random signals Added together, is a full rank matrix.

7. The MIMO array high-resolution beamforming method based on single-bit transmission according to claim 6, characterized in that: When the matched filtering results of N×M channels are weighted to synthesize beams, for N receiving channels, the received signals are processed by high-precision quantization and matched filtering is performed M times in parallel, with each filter corresponding to the signal of a single-bit transmitting channel; Weighting of the matched filtering results of N×M channels Synthetic beam.

8. The MIMO array high-resolution beamforming method based on single-bit transmission according to claim 7, characterized in that: The point spread function is introduced to weight the matched filtering results of N×M channels to synthesize the beam. , so that the beam is pointed In the case of Scanning within the range, the gain curve obtained ; is a full rank matrix, substituting the direction The SNR gain formula is: in It is determined by the phase difference between the signals of each channel of the array before transmitting single-bit quantization; yes The power of the order signal; It is the direction of any goal; After matched filtering, the weighted vector is determined Direction parameters, adjust the transmit and receive beam directions again After quantization, The signal components in The launch steering vector in the direction, Indicates the carrier frequency of the transmitted signal, After quantization, The conjugate transpose of the transmit steering vector for each signal component.

9. The MIMO array high-resolution beamforming method based on single-bit transmission as claimed in claim 8, characterized in that: direction The SNR gain on is expressed as: In the formula, is the correlation matrix of the array transmit signal, is the steering vector of the transmitting array, is the steering vector of the receiving array, is the direction of any target signal, N is the actual number of array elements in the receiving array, To direct the beam, adjust the filter output weight To change the direction of the beam; represents the transpose of the correlation matrix of the array transmit signal, Indicated in The steering vector in the launch direction, The steering vector Perform conjugate transpose.

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