MIMO (Multiple Input Multiple Output) array high-resolution beam forming method based on single-bit transmission

Abstract

The invention provides an MIMO (multiple input multiple output) array high-resolution beam forming method based on single-bit transmission, relates to the technical field of array signal processing, and aims at narrow-band LFM (linear frequency modulation) waveforms of random phases to model single-bit array signals of the narrow-band LFM waveforms. By considering the multi-channel time delay characteristic, the quantized high-order frequency domain characteristic and the high-order spatial frequency characteristic, a unified space-time frequency domain model is constructed to analyze the harmonic mechanism and the spatial dispersion effect, and the single-bit quantization theory is perfected. And then, on the basis of a traditional SIMO mode, further considering that single-bit quantization is adopted for a transmitting end of the array so as to obtain a decorrelated array transmitting signal, and adopting high-precision quantization and matched filtering at each channel of a receiving end, so that the design of the MIMO array signal processing framework based on single-bit transmission is completed. According to the invention, low-power-consumption and high-precision digital beam forming is realized through single-bit quantization and emission processing of MIMO array signals.

Description

Technical Field

[0001] The present invention relates to the technical field of array signal processing, and in particular to a MIMO (Multiple Input Multiple Output) array high-resolution beamforming method 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. In order to simultaneously undertake different tasks such as "early warning" and "staring" in a dynamic environment, on-board millimeter-wave radars not only need to perform large-scale scanning of specific distances in specific areas to detect potential obstacles or threats, but also need to continuously track the discovered targets. The former requires a wide beam coverage range, and the latter requires high beam resolution. This requires that millimeter-wave array radars should have sufficient beam resources and allocate them reasonably to assist in autonomous driving decisions, thereby improving driving safety. However, with the continuous improvement of the level of autonomous driving, the difficulty of detection requirements and perception tasks continues to increase, which is accompanied by the increase in hardware costs and the computing power challenges of massive data. The future vehicle-mounted millimeter-wave radar solution must not be at the expense of unlimited growth in the number of radars and the hardware resources of a single radar.

[0003] The existing single-bit transmission beamforming technology greatly simplifies the hardware complexity by quantizing the signal into one bit and retaining only the positive and negative sign information. The core of its technical solution is to use a single-bit quantizer and a switching power amplifier instead of the traditional high-precision digital-to-analog converter and linear power amplifier, and achieve beam pointing optimization by accurately controlling the signal phase, and combine algorithms to compensate for the signal loss introduced by quantization. This technology has obvious advantages in hardware implementation, including reducing manufacturing costs, data storage and transmission overhead, and significantly improving the energy efficiency of the system. It is suitable for scenarios such as low-power Internet of Things, satellite communications, and low-cost radars. However, due to the loss of signal amplitude information, the signal quality of the system is significantly reduced, and the quantization noise leads to insufficient beam gain and sidelobe suppression performance. In addition, single-bit signals are extremely sensitive to noise environments, and performance degrades severely in low signal-to-noise ratio scenarios. Despite this, beamforming technology based on single-bit transmission has great potential in low-power and resource-constrained scenarios, and it 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: 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: 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'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.

[0006] 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:

[0007] 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:

[0008] In the formula, when When it approaches 0, the minimum period , a one-bit correlation is represented by Fourier series expansion.

[0009] As a further embodiment of the present invention, when Approaching 0, is an even-cycle triangular wave. The Fourier series expansion of the real part of the quantized signal is:

[0010] 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;

[0011] DC component is 0, is an even function, for all , All are 0.

[0012] As a further embodiment of the present invention, when Approaching 0, is an odd-cycle triangular wave, and the Fourier series expansion of the imaginary part of the quantized signal is:

[0013] 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;

[0014] DC component is 0, is an odd function, for all , All are 0.

[0015] As a further solution of the present invention, when the signal model is extended from a single channel to multiple channels, 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:

[0016] in, is power, is from the array response vector of the incident signal; is a rank one matrix, Array element and The correlation between array elements is:

[0017] 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:

[0018] 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.

[0019] As a further solution of the present invention, the correlation function after signal quantization is substituted into the covariance matrix Formula, the inverse sine law expands the array signal to form a one-dimensional covariance matrix:

[0020] 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:

[0021] And substitute and The formula is:

[0022] 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:

[0023] in, Indicates The power of the order signal, Indicates The covariance matrix of the α-order signal.

[0024] As a further solution of the present invention, the single-bit covariance matrix is ​​represented as the sum of an infinite number of covariance matrices. The order covariance matrix is:

[0025] No. Order signal power The expression is:

[0026] And the signal The order guide vector is:

[0027] The false direction vector is:

[0028] A signal propagating in space is represented by 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.

[0029] As a further solution of the present invention, when weighting the matched filtering results of N×M channels 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, each filter corresponding to a signal of a single-bit transmitting channel; the matched filtering results of N×M channels are weighted Synthetic beam.

[0030] As a further solution of the present invention, a 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 In the case of Scanning within the interval, the gain curve obtained ; is a full rank matrix, substituting the direction The SNR gain formula is:

[0031] 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 can adjust the transmit and receive beam directions again; Among them, the direction The SNR gain on is expressed as:

[0032] In the formula, 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 any target signal, N is the actual number of elements in the receiving array, To direct the beam, adjust the filter output weight to change the direction of the beam.

[0033] Compared with the prior art, the MIMO array high-resolution beamforming method based on single-bit transmission proposed in the present invention has the following beneficial effects: The high-resolution beamforming method of the present invention can be mainly divided into two steps: First, for the narrowband LFM (Linear Frequency Modulation) waveform with random phase, its single-bit array signal is modeled. By considering the multi-channel delay characteristics, the high-order frequency domain characteristics after quantization, and the high-order spatial frequency characteristics, a unified time-space frequency domain model is constructed to analyze the harmonic mechanism and spatial dispersion effect, and improve the single-bit quantization theory. Subsequently, on the basis of the traditional SIMO (Single Input Multiple Output) mode, further consideration is given to using single-bit quantization on the transmitting end of the array to obtain a decorrelated array transmission signal, and high-precision quantization and matched filtering are used on each channel of the receiving end, thereby completing the design of the MIMO array signal processing framework based on single-bit transmission.

[0034] 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. Secondly, by processing fundamental signals 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 spatial resolution and realize multi-beam high-precision beamforming. In addition, by exploring the characteristics of wide beam coverage of the fundamental wave and high beam resolution of the harmonic wave, a feasible solution is provided for the various task requirements of vehicle-mounted millimeter-wave radars such as "early warning" and "staring" in intelligent driving scenarios.

[0035] These and other aspects of the present application will be more concise and understandable 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

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the following briefly introduces the drawings required for use in the exemplary embodiments or related technical descriptions. The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation to the present invention. In the drawings: Figure 1 The present invention is a flowchart of a MIMO array high-resolution beamforming method based on single-bit transmission according to an embodiment of the present invention.

[0037] Figure 2 This is a diagram of angular dispersion effect in a MIMO array high-resolution beamforming method based on single-bit transmission according to an embodiment of the present invention.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] Figure 6The 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

[0042] 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.

[0043] 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.

[0044] 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.

[0045] The present invention proposes a high-resolution beamforming method for a MIMO array based on single-bit transmission, which can be mainly divided into two steps: first, for a narrowband LFM waveform with a random phase, a single-bit array signal is modeled. By considering the multi-channel delay characteristics, the high-order frequency domain characteristics after quantization, and the high-order spatial frequency characteristics, a unified time-space frequency domain model is constructed to analyze the harmonic mechanism and spatial dispersion effect, and improve 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 a decorrelated array transmission signal, and high-precision quantization and matched filtering are used for each channel at the receiving end, thereby completing the design of the MIMO array signal processing framework based on single-bit transmission.

[0046] See also Figure 1 As shown, an embodiment of the present invention provides a MIMO array high-resolution beamforming method based on single-bit transmission, the method comprising the following steps: Step S10: construct a single-bit array signal time-frequency-space domain model.

[0047] The single-bit array signal is modeled for the narrow-band LFM waveform with random phase, and a unified space-time frequency domain model is constructed to analyze the harmonic mechanism and spatial dispersion effect. The inverse sine theorem is used to construct the correlation function of the signal after quantization, and Fourier series expansion is performed. The covariance matrix of the array signal is considered to expand the signal model from single channel to multi-channel.

[0048] Step S20: construct a MIMO array signal processing framework based on single-bit transmission.

[0049] Single-bit quantization is used on the transmitting end of the array, and high-precision quantization and matched filtering are used on each channel of the receiving end. The matched filtering results of N×M channels are weighted to synthesize beams, completing the construction of the MIMO array signal processing framework based on single-bit transmission.

[0050] In this embodiment, in step S10, when constructing the single-bit array signal time-frequency-space domain model, it is assumed that 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:

[0051] 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 .

[0052] With the help of the inverse sine theorem, the correlation function of the quantized signal is:

[0053] In the formula, when When it approaches 0, the minimum period , a one-bit correlation is represented by Fourier series expansion.

[0054] when When it approaches 0, is an even-cycle triangular wave. The Fourier series expansion of the real part of the quantized signal is:

[0055] 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 order cosine component; is the Fourier sine coefficient, which represents the The magnitude of the order component; Indicates the order of the cosine component of the signal.

[0056]

[0057] DC component is 0, is an even function, for all , All are 0; Represents the change in the phase of the incident signal.

[0058] Similarly, when When it approaches 0, is an odd-cycle triangular wave, and the Fourier series expansion of the imaginary part of the quantized signal is:

[0059] in, 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 order cosine component; is the Fourier sine coefficient, which represents the The magnitude of the order component; Represents the imaginary part of the signal.

[0060]

[0061] DC component is 0, is an odd function, for all , All are 0; Indicates the minimum period of a signal.

[0062] Next, the signal model is expanded from single channel to multi-channel. When the signal model is expanded 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:

[0063] in, It means to do conjugate transpose of the vector. represents the incident direction of the signal, is the power, is from the array response vector of the incident signal; Expressing The incident signal array response vector is conjugate transposed.

[0064] is a rank one matrix, Array element and The correlation between array elements is:

[0065] 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:

[0066] 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.

[0067] Substitute formula (2) into formula (9), that is: Substitute the correlation function after signal quantization into the covariance matrix Formula, the inverse sine law expands the array signal to form a one-dimensional covariance matrix:

[0068] 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 into formula (3) and formula (5), that is, substitute 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, and we get Array element and The spatial correlation function between array elements is:

[0069] Substitute into formula (4) and formula (6), that is, substitute and The formula is:

[0070] By comparing formula (12) with formula (8), Array element and For correlation comparison between array elements, the form of the single-bit covariance matrix is ​​similar to the covariance matrix of the unquantized array signal in formula (7) and is expressed as:

[0071] 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 α-order signal.

[0072] The above formula (13) shows that the single-bit covariance matrix is ​​expressed as the sum of infinite covariance matrices, The order covariance matrix is:

[0073] No. Order signal power The expression is:

[0074] And the signal The order guide vector is:

[0075] The false direction vector is:

[0076] In the formula, Expressed as the order of the signal component.

[0077] A signal propagating in space is represented by 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.

[0078] From an intuitive point of view, formula (13) is: A signal propagating in space will appear as an infinite number of sub-signals, which include attenuated signals and signals in false directions. This phenomenon is mainly caused by the angular dispersion caused by single-bit quantization, see Figure 2 In addition, the correlation matrix corresponding to the single-bit quantized signal is Multiple random signals Added together, is a full rank matrix, see Figure 3 shown.

[0079] In step S20 of the present embodiment, when constructing a MIMO array signal processing framework based on single-bit transmission, the single-bit transmission MIMO array refers to a transmission signal based on the M channels of the traditional wideband phased array, with only time / phase difference, generating a high-frequency modulation signal in the digital domain, and using a high-speed comparator instead of a high-precision digital-to-analog converter to output a single-bit signal. Therefore, the amplitude of the RF signal transmitted by each channel contains only single-bit information, and the signal waveform tends to be an irregular square wave; for the N receiving channels, the received signal is processed with high-precision quantization, and M matching filters 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 overall structure of the synthetic beam is as follows: Figure 4 As shown. Among them, T represents the transmitting array element, R represents the receiving array element, T / R represents the common array element for receiving and transmitting, and two empty circles represent virtual array elements; represents the initial phase, , , represents the phase offset after single-bit quantization, Indicates conjugation treatment.

[0080] exist Figure 4 In the working mode, the hardware advantage of the array is that the transmitter uses a comparator instead of a high-precision DAC, which can increase the speed of the signal digital-to-analog conversion and reduce the complex image spurs generated during the analog-to-digital conversion process. The receiver performs single-bit matched filtering on the quantized high-precision signal, and the multiplication and addition operations of the high-precision signal and the single-bit signal consume less computing resources.

[0081] Figure 4 Although the array and its signal processing are similar to MIMO arrays, the core goal is to evaluate whether the array can achieve higher angle measurement accuracy than phased arrays. Therefore, the target angle resolution performance of the array shown in the figure is analyzed from the perspective of beamforming. Looking back at conventional MIMO beamforming, the matched filter output weights for N×M channels are ,direction The SNR gain on is expressed as:

[0082] The gain in this direction is determined by the transmit and receive 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 any target signal, is the actual number of 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.

[0083] In order to describe the angular resolution capability of the MIMO beam, this embodiment introduces a point spread function (PSF). In formula (18), by adjusting the weight , so that the beam is pointed in the In the case of Scanning within the interval, the gain curve obtained , which is PSF; this curve can reflect the direction of the beam following the target The changing gain characteristics also reflect the beam's ability to resolve the target angle. Obviously, the first factor of 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 directional delay vector of the transmitting array. For the matching of the target direction, substituting it into formula (18) can further simplify the expression to:

[0084] In the formula, Indicates the number of transmitting signal array elements, Indicates the number of received signal array elements.

[0085] Taking the ideal MIMO array as an example, if a set of completely orthogonal signal waveforms is transmitted, is a full-rank identity matrix. Substituting into formula (18) can be simplified to:

[0086] Comparing formulas (19) and (20), we can find that the gain The receiving factor is consistent with the traditional SIMO array; the phased array gain The emission factor is a constant and is not affected by In an ideal situation, the gain of the MIMO array is The emission factor will vary with This makes the MIMO array better than the phased array in terms of target angle resolution. In other words, under the same transceiver array structure, the main factor affecting PSF is the covariance matrix of the array transmission signal. .

[0087] Next is a discussion of the single-bit transmission MIMO array transmission factor proposed in the present invention. From equation (13), we can see that: is a full rank matrix, which can be simplified into formula (18):

[0088] in 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 can 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.

[0089] like Figure 5 As shown in Figure 1, the MIMO array based on single-bit transmission performs better than the traditional phased array in terms of point spread function (PSF). In other words, the MIMO array based on single-bit transmission is better than the general phased array in terms of angle measurement accuracy. This is because the correlation matrix corresponding to the transmission signal of the single-bit array Multiple random signals Added together, is a full-rank matrix. From another perspective, the transmission of the array can be seen as a combination of multiple unrelated signals. This is different from the architecture of the traditional MIMO array, in which each channel transmits an orthogonal signal. Each channel of the latter transmits the sum signal of the fundamental wave and each harmonic. There is a time delay relationship between the channels, so that the beam synthesized by the transmission signal at each harmonic frequency points in different directions. In addition, for high-speed moving targets, wide transmit beams and narrow receive beams are used to achieve high spatial resolution tracking while searching over a wide area. Figure 6 As shown, the dotted high-gain wide transmit beam covers 6°, while multiple harmonic receive beams of the solid line are formed simultaneously, each beam covering 2.4°, wherein the angle covered by each beam (6° or 2.4°) can be obtained by performing a sine value-angle transformation on the normalized transmit direction covered in the figure.

[0090] In the step of constructing the single-bit array signal time-frequency-spatial domain model, 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 an infinite number of matrices with rank one, 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 produce harmonic components. The directional angle and frequency of the harmonics are coupled with the original signal, which means that the original direction The incident signal, after quantization, is seen as a function of the harmonic frequencies. The false direction of incidence also reveals the angular dispersion effect caused by quantization.

[0091] 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. Secondly, by processing fundamental signals 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 spatial resolution and realize multi-beam high-precision beamforming. In addition, by exploring the characteristics of wide beam coverage of the fundamental wave and high beam resolution of the harmonic wave, a feasible solution is provided for the various task requirements of vehicle-mounted millimeter-wave radars such as "early warning" and "staring" in intelligent driving scenarios.

[0092] It should be noted that the above figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0093] It should be understood that, although described in a certain order, these steps are not necessarily performed in sequence in the above order. Unless there is clear explanation in the present invention, the execution of these steps does not have strict order restriction, and these steps can be performed in other orders. Moreover, a part of the steps of the present embodiment may include a plurality of steps or a plurality of stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a part of the steps or stages in other steps or other steps.

[0094] The above are exemplary embodiments disclosed in the present invention, but it should be noted that various changes and modifications may be made without departing from the scope disclosed in the embodiments of the present invention as defined in the claims. The functions, steps and / or actions of the method claims according to the disclosed embodiments described herein do not need to be performed in any particular order. In addition, although the elements disclosed in the embodiments of the present invention may be described or required in individual form, they may also be understood as multiple unless explicitly limited to the singular.

[0095] It should be understood that, as used in the present invention, the singular form "a" or "an" is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used in the present invention, "and / or" refers to any and all possible combinations of one or more items listed in association. The serial numbers of the embodiments disclosed in the above embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments.

[0096] A person skilled 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 disclosure of the embodiments of the present invention (including the claims) is limited to these examples; under the concept of the embodiments of the present invention, the technical features in the above embodiments or different embodiments can also be combined, and there are many other changes in different aspects of the above embodiments of the present invention, which are not provided in detail for the sake of simplicity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present invention should 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'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.

2. The MIMO array high-resolution beamforming method based on single-bit transmission according to claim 1, characterized in that: 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: 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.

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 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.

4. The MIMO array high-resolution beamforming method based on single-bit transmission as claimed in claim 3, 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.

5. The MIMO array high-resolution beamforming method based on single-bit transmission as claimed in claim 4, 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.

6. The MIMO array high-resolution beamforming method based on single-bit transmission as claimed in claim 5, 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 α-order signal.

7. The MIMO array high-resolution beamforming method based on single-bit transmission according to claim 6, 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.

8. The MIMO array high-resolution beamforming method based on single-bit transmission according to claim 7, 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.

9. The MIMO array high-resolution beamforming method based on single-bit transmission according to claim 8, 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 can be used to adjust the transmit and receive beam directions 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.

10. The MIMO array high-resolution beamforming method based on single-bit transmission according to claim 9, 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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