Particle flow multi-parameter detection method based on MIMO-FMCW radar, medium and equipment

Abstract

The present application relates to the technical field of radar detection, and particularly relates to a particle flow multi-parameter detection method based on MIMO-FMCW radar, a medium and equipment, the particle flow multi-parameter detection method based on MIMO-FMCW radar comprises the following steps: S1, arranging a virtual channel array structure of × in a detection area, and obtaining a digital signal matrix of multiple frames of measurement data corresponding to the detection area by using the virtual channel array structure; S2, obtaining multiple parameters of the particle flow in the detection area based on the digital signal matrix.The present application synchronously obtains data in the time, frequency and spatial domain by using the MIMO-FMCW radar system, realizes the joint measurement of the multiple parameters of the particle flow, can extract the speed information by the Doppler effect of the FMCW signal, can form a virtual channel to extract the angle information, and simultaneously combines the signal amplitude to estimate the concentration, so that comprehensive particle flow movement characterization is realized.

Description

Technical Field

[0001] This invention relates to the field of radar detection technology, specifically to a method, medium, and device for multi-parameter detection of particle streams based on MIMO-FMCW radar. Background Technology

[0002] Flowing particulate systems are widely present in industrial processes such as chemical, energy, and environmental protection (e.g., fluidized beds, moving beds, rotary kilns). Real-time monitoring of multiple parameters of particle flow (including velocity field, spatial distribution, and concentration changes) is crucial for process control and optimization. However, because particles are typically dense and opaque, traditional optical imaging methods struggle to obtain flow information from within. While X-ray, millimeter-wave, and CT tomography techniques can achieve particle imaging, the equipment is expensive and sampling times are long, hindering online real-time monitoring. Another approach uses tracer particles (such as positron emission tomography (PEPT), radioactive tracer (RPT), and magnetic tracer (MPT), but these techniques either involve radioactive particles (posing safety hazards) or suffer from rapid signal attenuation and limited detection range, making it difficult to cover large-scale process systems.

[0003] In contrast, radar technology enables non-contact detection by emitting electromagnetic waves, is independent of visible light, and can penetrate dust and media. Frequency-modulated continuous wave (FMCW) radar can simultaneously provide target range and velocity information: it generates range-Doppler maps, allowing extraction of the target's radial velocity at a specific distance. Existing research has utilized FMCW radar to measure the velocity of fluids (such as simulated urine flow), directly obtaining flow velocity information by analyzing the range-Doppler maps. Furthermore, multiple-input multiple-output (MIMO) radar, through the formation of a virtual array using multiple transmitters and receivers, can significantly improve the angular resolution of targets. For example, configuring two transmitters and four receivers in a TDM-MIMO structure can synthesize eight virtual channels, thereby greatly improving the accuracy of azimuth estimation. In the field of particle flow measurement, recent research has attempted to apply radar technology in scenarios such as fluidized beds: work at Chalmers University shows that pulse Doppler radar up to 340 GHz can achieve high-precision simultaneous measurement of the velocity and concentration of solid particles in circulating fluidized beds, with spatial resolution far exceeding traditional methods. However, existing research is mostly limited to single parameter or specific frequency band measurements, and there is still a lack of a general scheme for multi-parameter joint real-time detection of flowing particles using MIMO-FMCW radar. Summary of the Invention

[0004] The purpose of this invention is to provide a method, medium, and device for multi-parameter detection of particle flow based on MIMO-FMCW radar, aiming to solve the problem that traditional measurement methods in the prior art are insufficient for characterizing particle flow dynamics. The specific technical solution is as follows:

[0005] This invention provides a multi-parameter detection method for particle streams based on MIMO-FMCW radar, comprising the following steps:

[0006] S1. Arrangement in the detection area × The virtual channel array structure is used to obtain a digital signal matrix of multiple frames of measurement data corresponding to the detection area, wherein: The number of transmitting antennas, This refers to the number of receiving antennas;

[0007] S2. Obtain multiple parameters of the particle flow in the detection area based on the digital signal matrix, where the multiple parameters include: velocity, distance, angle, and concentration; S2 specifically includes:

[0008] S2.1 Obtaining the range-Doppler spectrum: Performing two-dimensional FFT processing on the digital signal matrix based on the range domain and pulse domain to obtain the range-Doppler spectrum, where: the range-Doppler spectrum includes range information and velocity information;

[0009] S2.2, Estimating Angle Information and 3D Positioning: The angle information of the target particle is calculated based on the phase difference of the reflected echo signal of the target particle by each receiving antenna in the virtual channel array structure; and the angle information is combined with the range-Doppler spectrum to obtain the range-Doppler-angle 3D spectrum, where: the angle information includes azimuth and elevation angles;

[0010] S2.3 Estimating Concentration Distribution: Estimating the concentration information of the particle flow based on the distance-Doppler-angle three-dimensional spectrum.

[0011] Optionally, S1 includes:

[0012] S1.1 Configuring a MIMO-FMCW radar array: A transmitting antenna array and a receiving antenna array are arranged outside the detection area, and a virtual channel array structure is formed through MIMO processing. Transmission is performed using TDM mode, wherein: the virtual channel array structure includes... One virtual channel;

[0013] S1.2 Transmitting FMCW signals: The transmitting antenna array continuously transmits linear FMCW signals within a predetermined frequency range, wherein the signal transmission frequency changes linearly with time;

[0014] In S1.2, the linear frequency modulated signals of each virtual channel are transmitted alternately in time slots. Linear frequency modulation signal corresponding to each transmitting antenna The specific formula is as follows:

[0015] ;

[0016] in: It is the emission amplitude. It is the carrier frequency. Indicates the frequency modulation slope. Indicates the frequency modulation slope. It is the total signal bandwidth. It is a single frequency sweep cycle. Launch time; This is the number of the transmitting antenna. ; It is a complex number;

[0017] S1.3 Receiving echo signals, specifically including:

[0018] Under the scattering effect of the particle flow on the incident radar wave within the detection area, the receiving antenna array captures the reflected echo signal; where: the first The reflected echo signal corresponding to the receiving antenna The specific formula is as follows:

[0019] ;

[0020] in: It is the echo amplitude; It's the speed of light; For round-trip delay, , The target distance; The number of the receiving antenna. ;

[0021] The low-frequency baseband beat frequency signal is obtained by mixing the reflected echo signal with the local oscillator signal of the receiving antenna array, as shown in the following formula:

[0022] ;

[0023] in: It is the first The low-frequency baseband beat frequency signal of the channel; The conjugate of the local oscillator signal of the receiving antenna array; The amplitude of the beat frequency signal. Beat frequency ; This refers to the high-frequency portion;

[0024] The low-frequency baseband beat frequency signal is sampled by an analog-to-digital converter to form a digital signal matrix. The specific formula is as follows:

[0025] ;

[0026] in: Number the sampling points. It is the number of sampling points per pulse. , It is a single frequency sweep cycle. Sampling time, , For rate.

[0027] Optionally, S2.1 includes:

[0028] To obtain distance information, specifically:

[0029] ① For each pulse in the pulse domain, for the first pulse... Execution of the distance domain sequence of the channel Point-based two-dimensional FFT processing yields the first The complex amplitude and corresponding beat frequency of the distance element;

[0030] ② According to the first The distance between the target particle and the transmitting antenna is calculated by using the beat frequency of the distance unit and the frequency modulation slope of the transmitting antenna array. The specific calculation formula is as follows:

[0031] ;

[0032] in: For the first Distance information of the distance unit; The speed of light; For the first The corresponding beat frequency of the distance unit, ;

[0033] Obtain speed information, specifically:

[0034] ① Collect data for each distance unit. Each pulse is obtained ,in: Number the pulse. ;

[0035] ②, Regarding the first Execution of the distance domain sequence of the channel Point-based two-dimensional FFT processing yields the first Distance unit, first Doppler element complex amplitude and pulse repetition frequency ,in: , The frame time length;

[0036] ③ Calculate the velocity corresponding to each Doppler element based on the pulse repetition frequency and the carrier frequency of the transmitting antenna. The specific calculation formula is as follows:

[0037] ;

[0038] in: For Doppler frequency shift, .

[0039] Optionally, S2.2 includes:

[0040] S2.2.1, each Peak units are cascaded into vectors across all virtual channels. The power spectrum is obtained by performing FFT or beamforming along the virtual channel array structure index, where: It is the set of complex numbers;

[0041] S2.2.2, Search Make the power spectrum At its maximum, it can obtain azimuth angles. and pitch angle Angle information;

[0042] S2.2.3. Combine the angle information corresponding to different target particles with the range-Doppler spectrum to obtain the range-Doppler-angle three-dimensional spectrum.

[0043] Optionally, 2.3 includes:

[0044] S2.3.1 Construct voxels and calculate the volume of a single voxel. Specifically:

[0045] Construct a range-resolved unit based on the bandwidth of the FMCW signal. The specific formula is as follows:

[0046] ;

[0047] Angle resolution units are constructed based on the number of virtual channels in the azimuth and elevation directions. The specific formula is as follows:

[0048] ;

[0049] in: For azimuth resolution units; For pitch angle resolution; It is the wavelength; Antenna spacing, ; It refers to the number of virtual channels in terms of orientation. It is the number of virtual channels in the pitch direction;

[0050] Calculate the cross-sectional area corresponding to one angle resolution unit based on the angle resolution unit. ;

[0051] ;

[0052] in: Given a distance;

[0053] Based on the cross-sectional area corresponding to the distance resolution unit and the angle resolution unit Calculate the volume of a single voxel The specific formula is as follows:

[0054] ;

[0055] S2.3.2 Judgment: If the number of particles in the detection area is less than 30%, the particle concentration in a single voxel is calculated using the target counting method; otherwise, the particle concentration in a single voxel is calculated using the echo amplitude accumulation method.

[0056] Optionally, in section 2.3.2, the particle concentration within a single voxel is calculated using the echo amplitude accumulation method, specifically including:

[0057] ① Record the background noise power spectrum when there are no particles. and compared with the original power spectrum obtained during measurement. Differential power spectrum is obtained by performing a differential operation. ,in: These are the distance, azimuth, and elevation indices, respectively, and the specific formulas are as follows:

[0058] ;

[0059] ② For each voxel The cumulative power is obtained by averaging or summing the measurement results from multiple pulses or frames. The specific formula is as follows:

[0060] ;

[0061] in: For frame number, This is the number assigned to each frame of measurement results;

[0062] ③ The cumulative number of peak values ​​at the same voxel location collected in a reference container of known volume. The total number of particles was obtained from the reference container. Calibration determination coefficient The specific formula is as follows:

[0063] ;

[0064] ④ Based on cumulative power and the coefficient of determination estimation voxels Corresponding number of particles voxels are then obtained. Corresponding particle concentration The specific formula is as follows:

[0065] ;

[0066] .

[0067] Optionally, in S2.3.2, the particle concentration within a single voxel is calculated using the echo amplitude accumulation method, specifically including:

[0068] ① Perform constant false alarm rate detection on the distance-Doppler-angle three-dimensional spectrum and identify local peak points;

[0069] ② Statistical analysis of a voxel within each or multiple frames. Total number of peak values ​​detected in The average peak count is obtained by averaging the total peak count across multiple frames. ;

[0070] ③ In the reference container, the number of peak values ​​per unit voxel is also counted. and the known number of particles Perform linear fitting to obtain coefficients The specific formula is as follows:

[0071] ;

[0072] ④ Based on coefficients Calculate particle concentration The specific formula is as follows:

[0073] ;

[0074] in: This indicates the number of particles in the container.

[0075] Optionally, S1.1 further includes: superimposing a periodic magnetic field in the detection area to synchronously modulate the scattering cross section of the magnetic particles;

[0076] The process after S2.2 further includes: generating a particle velocity vector map, a flow velocity distribution map, and a spatial location information map based on the angle information, velocity information, and distance information, respectively; the process after S2.3 further includes: generating a concentration change curve based on the angle information and concentration information.

[0077] The present invention also provides a readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the particle flow multi-parameter detection method based on MIMO-FMCW radar as described above.

[0078] The present invention also provides an electronic device, comprising: at least one processor, at least one memory, and computer program instructions stored in the memory, wherein the computer program instructions are executed by the processor to perform the particle flow multi-parameter detection method based on MIMO-FMCW radar as described above.

[0079] The technical solution of this invention utilizes a MIMO-FMCW radar system to simultaneously acquire data in the time, frequency, and spatial domains, achieving multi-parameter joint measurement of particle flow. This invention can extract velocity information through the Doppler effect of the FMCW signal, extract angle information by forming a virtual channel using an antenna array, and simultaneously estimate concentration by combining signal amplitude, thus achieving comprehensive particle flow characterization.

[0080] In addition to the objectives, features, and advantages described above, the present invention has other objectives, features, and advantages. The invention will now be described in further detail with reference to the figures. Attached Figure Description

[0081] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0082] Figure 1 This is a schematic diagram of the trajectory of particles moving inside the pipe.

[0083] Figure Labels

[0084] 1. Particle flow, 2. MIMO-FMCW radar. Detailed Implementation

[0085] To make the objectives, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Several embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein.

[0086] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances. The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature.

[0087] In this invention, unless otherwise expressly specified and limited, "above" or "below" a second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of a second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" of a second feature includes the first feature being directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature. The terms "vertical," "horizontal," "left," "right," "above," "below," and similar expressions are for illustrative purposes only and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed or operated in a specific orientation, and therefore should not be construed as limiting the invention.

[0088] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, the present invention can be implemented in many different ways as defined and covered by the claims.

[0089] In one embodiment, a multi-parameter detection method for particle streams based on MIMO-FMCW radar includes the following steps:

[0090] S1. Arrangement in the detection area × The virtual channel array structure is used to obtain a digital signal matrix of multiple frames of measurement data corresponding to the detection area, wherein: The number of transmitting antennas, This refers to the number of receiving antennas;

[0091] S1 includes:

[0092] S1.1 Configuring MIMO-FMCW Radar 2 Array: A transmitting antenna array and a receiving antenna array are arranged outside the detection area, and a virtual channel array structure is formed through MIMO processing. Transmission is performed using TDM mode, wherein: the virtual channel array structure includes... A virtual channel; in this embodiment, a multi-transmitter, multi-receiver antenna array is arranged outside the detection area to form a virtual channel. × The virtual channel array structure obtains rich angle information; in time division multiplexing (TDM) mode, each transmit antenna is excited to transmit FMCW signals to achieve efficient coverage of multiple signals.

[0093] Configure an appropriate number of transmitting and receiving antennas based on the detection area size and resolution requirements. The antennas can be arranged linearly or in a planar array. For TDM-MIMO systems, the transmitters can be driven alternately in time slot sequence to avoid signal interference. A virtual channel array coordinate system is established by accurately measuring the geometric position of each antenna.

[0094] for Transmitting antenna and Receiving antenna, denoted as the first The location of the transmitting antenna is

[0095] ;

[0096] No. The receiving antenna location is: ;

[0097] in, and Represent the three-dimensional coordinates of the transmitting antenna and the receiving antenna, respectively;

[0098] Based on time-division multiplexing (TDM) and MIMO processing, it is possible to build A virtual channel.

[0099] No. Location of each virtual channel: ;

[0100] in, Indicates virtual channel The corresponding transmit-receive pair index; Indicates the first Virtual channel position (m).

[0101] In this embodiment, the method for increasing the radar cross section (RCS) of magnetic particles in the MIMO-FMCW radar 2 system aims to enhance the echo signal strength, thereby improving the detection probability and signal-to-noise ratio. This can be achieved by utilizing high-permeability materials (such as ferrite, etc.). This can increase the equivalent polarization intensity and scattering intensity to improve the RCS of the particles, and the same method of magnetic modulation can be used to achieve this purpose. S1.1 also includes: superimposing a periodic magnetic field in the detection area to synchronously modulate the scattering cross section of the magnetic particles; thereby generating a narrowband signal component that can be synchronously extracted in the MIMO-FMCW radar 2 echo, improving the signal-to-noise ratio.

[0102] periodic magnetic field The specific expression is as follows:

[0103] ;

[0104] in, It is the DC bias magnetic field strength. It is the amplitude of the alternating current modulated magnetic field. It is the modulation angular frequency. It is the modulation frequency.

[0105] Under the linear approximation, particle magnetization for:

[0106] ;

[0107] in, It is the bulk magnetic susceptibility.

[0108] Scattering cross section With magnetization The squared transformation is expressed as follows:

[0109] ;

[0110] Expanding the above equation while retaining DC and the first harmonic:

[0111] ;

[0112] in: ;

[0113] In the formula, It is the DC component of the scattering cross section ( ), It is the amplitude of the first modulation of the scattering cross section ( The echo power is obtained by simplifying the radar equations. :

[0114] ;

[0115] in: ;

[0116] In the formula, These are radar system constants (including transmit power, antenna gain, wavelength, etc.). It is the target distance (m). It is the DC component of the echo power (W). It is the echo power modulation amplitude (W).

[0117] Will and Multiply and then pass through a low-pass filter (LPF) to obtain:

[0118] ;

[0119] in, It is the amplitude of the demodulated output signal.

[0120] Therefore, stray components and noise are significantly suppressed after LPF, thereby improving the signal-to-noise ratio and achieving the goal of improving RCS.

[0121] S1.2 Transmitting FMCW signals: The transmitting antenna array continuously transmits linear FMCW signals within a predetermined frequency range, wherein the signal transmission frequency changes linearly with time; in this embodiment, the predetermined frequency range is 60GHz~340GHz; millimeter wave or terahertz bands (such as 77GHz, 340GHz, etc.) can be used.

[0122] In this embodiment, driven by the controller, the transmitter transmits a continuously rising or falling linear frequency modulated signal according to a preset bandwidth and modulation bandwidth. Commercial millimeter-wave / terahertz radar chips or modules can be used to ensure that the signal bandwidth meets the required range resolution. Each channel transmits alternately in time slots to avoid collisions.

[0123] In S1.2, the linear frequency modulated signals of each virtual channel are transmitted alternately in time slots. Linear frequency modulation signal corresponding to each transmitting antenna The specific formula is as follows:

[0124] ;

[0125] in: It is the emission amplitude. It is the carrier frequency. Indicates the frequency modulation slope. Indicates the frequency modulation slope. It is the total signal bandwidth. It is a single frequency sweep cycle. Launch time; This is the number of the transmitting antenna. ; It is a complex number;

[0126] S1.3 Receiving the echo signal: Particles in the particle stream scatter the incident radar wave, and the receiving array captures the reflected echo. The echo signal is mixed with the local oscillator signal to obtain a low-frequency baseband beat frequency signal, which is then sampled by an analog-to-digital converter to form a digital signal matrix. In this embodiment, the receiving antenna can capture the echo signal scattered by the particles and mix it with the local oscillator to obtain the baseband beat frequency signal. The baseband signal is bandpass filtered and sampled to form a discrete-time domain signal sampling sequence, and then quantized. Receiving the echo signal specifically includes:

[0127] Under the scattering effect of the particle flow 1 on the incident radar wave within the detection area, the receiving antenna array captures the reflected echo signal; where: the first The reflected echo signal corresponding to the receiving antenna The specific formula is as follows:

[0128] ;

[0129] in: It is the echo amplitude; It's the speed of light; For round-trip delay, , The target distance; The number of the receiving antenna. ;

[0130] The low-frequency baseband beat frequency signal is obtained by mixing the reflected echo signal with the local oscillator signal of the receiving antenna array, as shown in the following formula:

[0131] ;

[0132] in: It is the first The low-frequency baseband beat frequency signal of the channel; The conjugate of the local oscillator signal of the receiving antenna array; The amplitude of the beat frequency signal. Beat frequency ; This refers to the high-frequency portion;

[0133] The low-frequency baseband beat frequency signal is sampled by an analog-to-digital converter to form a digital signal matrix. The specific formula is as follows:

[0134] ;

[0135] in: Number the sampling points. It is the number of sampling points per pulse. , It is a single frequency sweep cycle. Sampling time, , For rate.

[0136] S2. Obtain multiple parameters of the particle flow in the detection area based on the digital signal matrix, where the multiple parameters include: velocity, distance, angle, and concentration; S2 specifically includes:

[0137] S2.1 Obtaining the range-Doppler spectrum: Performing two-dimensional FFT processing on the digital signal matrix based on the range domain and pulse domain to obtain the range-Doppler spectrum, where: the range-Doppler spectrum includes range information and velocity information;

[0138] In this embodiment, a two-dimensional Fast Fourier Transform (FFT) is performed on the acquired fast-time (range domain) and slow-time (pulse domain) signals to obtain a range-Doppler spectrum. In the spectrum, each range cell corresponds to a specific Doppler frequency shift, and the corresponding radial velocity can be calculated from the Doppler frequency shift value. The range component directly corresponds to the range information between the target and the MIMO-FMCW radar 2. In this way, particle velocity information can be extracted from different ranges, and different targets can be separated in the range-velocity two-dimensional domain, improving detection robustness. The two-dimensional FFT processing in this embodiment effectively separates targets with different range cells and different velocities, and the peak detection algorithm can be used to identify target signals in the range-Doppler spectrum.

[0139] S2.1 includes:

[0140] To obtain distance information, specifically:

[0141] ① For each pulse in the pulse domain, for the first pulse... Execution of the distance domain sequence of the channel Point-based two-dimensional FFT processing yields the first The complex amplitude and corresponding beat frequency of the distance element;

[0142] Specifically: for each pulse, the first... Fast time series (i.e., distance dimension) execution of the channel Point FFT:

[0143] ;

[0144] in, It is the first Distance element complex amplitude; corresponding beat frequency ;

[0145] ② According to the first The distance between the target particle and the transmitting antenna is calculated by using the beat frequency of the distance unit and the frequency modulation slope of the transmitting antenna array. The specific calculation formula is as follows:

[0146] ;

[0147] in: For the first Distance information of the distance unit; The speed of light; For the first The corresponding beat frequency of the distance unit, ;

[0148] Obtain speed information, specifically:

[0149] ① Collect data for each distance unit. Each pulse is obtained ,in: Number the pulse. ;

[0150] ②, Regarding the first Execution of the distance domain sequence of the channel Point-based two-dimensional FFT processing yields the first Distance unit, first Doppler element complex amplitude and pulse repetition frequency ,in: , The frame time length;

[0151] Specifically: Let each Unit collection One pulse, to obtain ,in Perform on slow time (i.e., velocity dimension). Point FFT:

[0152] ;

[0153] in, It is the first Distance, number Doppler element complex amplitude; pulse repetition frequency Doppler frequency shift ;

[0154] ③ Calculate the velocity corresponding to each Doppler element based on the pulse repetition frequency and the carrier frequency of the transmitting antenna. The specific calculation formula is as follows:

[0155] ;

[0156] in: For Doppler frequency shift, .

[0157] In two-dimensional spectrum The target peak value is obtained by detecting local peak values. ;

[0158] S2.2, Estimating Angle Information and 3D Positioning: The angle information of the target particle is calculated based on the phase difference of the reflected echo signal of the target particle by each receiving antenna in the virtual channel array structure; and the angle information is combined with the range-Doppler spectrum to obtain the range-Doppler-angle 3D spectrum, where: the angle information includes azimuth and elevation angles;

[0159] This embodiment addresses each detected target peak in the spectrum. Calculate the corresponding distance (determined by the relationship between FMCW beat frequency and propagation time) and radial velocity. (Calculated from Doppler frequency shift); Based on the MIMO virtual array structure, the azimuth angle of the target can be calculated through angle Fourier transform (or beamforming) using the phase difference between multiple receiving antennas. Combining the angle information with the range information allows for three-dimensional positioning of the target particle. Specifically:

[0160] For the Virtual antenna, number Corresponding position of the channel Target direction unit vector Array steering vector:

[0161] ;

[0162] in, and These represent the pitch angle (°) and azimuth angle (°), respectively. Each... Peak units on all virtual channels string into vector Perform FFT or beamforming along the virtual array index:

[0163] ;

[0164] search Make the power spectrum At its maximum, the azimuth angle can be obtained. and pitch angle The spectral peak corresponding to the maximum power spectrum. The corresponding 3D positioning results are as follows:

[0165] ;

[0166] S2.2 includes:

[0167] S2.2.1, each Peak units are cascaded into vectors across all virtual channels. The power spectrum is obtained by performing FFT or beamforming along the virtual channel array structure index, where: It is a set of complex numbers; the peak unit refers to the detected distance-velocity unit;

[0168] S2.2.2, Search Make the power spectrum At its maximum, it can obtain azimuth angles. and pitch angle Angle information;

[0169] S2.2.3. Combine the angle information corresponding to different target particles with the range-Doppler spectrum to obtain the range-Doppler-angle three-dimensional spectrum.

[0170] S2.3 Estimating Concentration Distribution: Estimating the concentration information of particle flow 1 based on the distance-Doppler-angle three-dimensional spectrum.

[0171] In this embodiment, after obtaining the target position and velocity, the number of all detected particles or the cumulative echo energy within a unit volume (or unit distance range) can be counted to estimate the particle concentration distribution. By analyzing the amplitude of the echo signal or the number of targets, the concentration distribution change of the particle swarm can be estimated. The echo amplitude is positively correlated with the particle number density, and the absolute concentration value can be obtained by referencing the container correction coefficient. For example, by counting the cumulative echo energy or the number of targets within a unit volume and combining it with known calibration data, the concentration field of particle flow 1 can be obtained.

[0172] 2.3 includes:

[0173] S2.3.1 Construct voxels and calculate the volume of a single voxel. Specifically:

[0174] Construct a range-resolved unit based on the bandwidth of the FMCW signal. The specific formula is as follows:

[0175] ;

[0176] Angle resolution units are constructed based on the number of virtual channels in the azimuth and elevation directions. The specific formula is as follows:

[0177] ;

[0178] in: For azimuth resolution units; For pitch angle resolution; It is the wavelength; Antenna spacing, ; It refers to the number of virtual channels in terms of orientation. It is the number of virtual channels in the pitch direction;

[0179] Calculate the cross-sectional area corresponding to one angle resolution unit based on the angle resolution unit. ;

[0180] ;

[0181] in: Given a distance;

[0182] Based on the cross-sectional area corresponding to the distance resolution unit and the angle resolution unit Calculate the volume of a single voxel The specific formula is as follows:

[0183] ;

[0184] S2.3.2 Judgment: If the number of particles in the detection area is less than 30%, the particle concentration in a single voxel is calculated using the target counting method; otherwise, the particle concentration in a single voxel is calculated using the echo amplitude accumulation method.

[0185] In section 2.3.2, the echo amplitude accumulation method is used to calculate the particle concentration within a single voxel, specifically including:

[0186] ① Record the background noise power spectrum when there are no particles. and compared with the original power spectrum obtained during measurement. Differential power spectrum is obtained by performing a differential operation. ,in: These are the distance, azimuth, and elevation indices, respectively, and the specific formulas are as follows:

[0187] ;

[0188] ② For each voxel The cumulative power is obtained by averaging or summing multiple pulse or frame measurement results, as shown in the following formula:

[0189] ;

[0190] in: For frame number, This is the number assigned to each frame of measurement results;

[0191] ③ The cumulative number of peak values ​​at the same voxel location collected in a reference container of known volume. The total number of particles was obtained from the reference container. Calibration determination coefficient The specific formula is as follows:

[0192] ;

[0193] ④ Based on cumulative power and the coefficient of determination estimation voxels Corresponding number of particles voxels are then obtained. Corresponding particle concentration The specific formula is as follows:

[0194] ;

[0195] .

[0196] In S2.3.2, the particle concentration within a single voxel is calculated using the echo amplitude accumulation method, specifically including:

[0197] ① Perform constant false alarm rate detection on the distance-Doppler-angle three-dimensional spectrum and identify local peak points, which are the maximum points;

[0198] ② Statistical analysis of a voxel within each or multiple frames. Total number of peak values ​​detected in The average peak count is obtained by averaging the total peak count across multiple frames. ;

[0199] ③ In the reference container, the number of peak values ​​per unit voxel is also counted. and the known number of particles Perform linear fitting to obtain coefficients The specific formula is as follows:

[0200] ;

[0201] ④ Based on coefficients Calculate particle concentration The specific formula is as follows:

[0202] ;

[0203] in: This indicates the number of particles in the container.

[0204] In this embodiment, after S2.2, the method further includes: generating a particle velocity vector map, a flow velocity distribution map, and a spatial location information map based on the angle information, velocity information, and distance information, respectively; after S2.3, the method further includes: generating a concentration change curve based on the angle information and concentration information. Combining the above processing results, multiple parameters of the particle flow 1 are obtained, including the particle velocity vector, flow velocity distribution map, concentration change curve, and spatial location information for each detection area, for subsequent display, control, or analysis.

[0205] like Figure 1 As shown, in one embodiment, it is applied to the detection of multiple parameters of particulate flow in a pipeline.

[0206] Furthermore, in another embodiment, taking fluidized bed reactor monitoring in the chemical industry as an example: In a combustion furnace or chemical reactor, catalyst or fuel particles move with the airflow, and real-time monitoring of particle velocity distribution and concentration changes is crucial for process optimization. Deploying a MIMO detection system using MIMO-FMCW radar 2 can non-invasively penetrate high-temperature flue gas clouds to measure the velocity and concentration fields of particle flow 1. For example, when the particle concentration increases, the received echo power increases; when some flow channels are blocked or unevenly distributed, the velocity field at the corresponding directional angle will show abnormal changes. Combining the above technical solutions, real-time three-dimensional imaging of particle movement within the fluidized bed can be achieved.

[0207] In another embodiment, it can also be applied in the biopharmaceutical field, such as in magnetic nanomedicine delivery systems, where the MIMO-FMCW radar 2 can be used to track the flow rate and distribution of drug particles in simulated tissues or reaction vessels in vitro, optimizing drug release parameters without the need for fluorescent or radiofrequency labeling. This is particularly important in scenarios such as cell culture and bioreactor monitoring.

[0208] Each step in this embodiment can be implemented using existing radar hardware platforms and digital signal processing technology.

[0209] The particle flow multi-parameter detection method based on MIMO-FMCW radar in this embodiment has the following advantages:

[0210] 1. Non-contact measurement: It uses electromagnetic waves for detection, which does not require direct contact with particulate media, is not limited by transparency, and can work in harsh environments such as dust and high temperature.

[0211] 2. Simultaneous acquisition of multiple parameters: Multiple motion parameters such as velocity, azimuth and concentration can be extracted simultaneously through a single continuous scan, avoiding the cumbersome process of switching measurement methods multiple times and providing comprehensive dynamic information of particle flow 1.

[0212] 3. High precision and high resolution: The MIMO virtual array significantly improves angular resolution. Combined with FMCW distance resolution and Doppler velocimetry, it can achieve centimeter-level positioning accuracy and precise measurement of fine particle flow velocity.

[0213] 4. Real-time online monitoring: The MIMO-FMCW radar 2 has a fast signal processing speed and can continuously output motion parameters in real time, meeting the online monitoring needs of industrial processes.

[0214] 5. Safe and reliable: It does not require the use of harmful radiation sources, making it safer and more environmentally friendly than methods that require radioactive tracers; the system hardware has high reliability and is easy to operate stably for a long time. ；

[0215] 6. Using high magnetic permeability materials (such as ferrite, Fe3O4) can improve the equivalent polarization intensity and increase the scattering intensity, thereby improving the RCS of the particles. 。

[0216] This embodiment also provides a readable storage medium storing computer program instructions, which, when executed by a processor, implement the particle flow multi-parameter detection method based on MIMO-FMCW radar as described above.

[0217] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0218] This embodiment also includes an electronic device, comprising: at least one processor, at least one memory, and computer program instructions stored in the memory, wherein the computer program instructions are executed by the processor to perform the particle flow multi-parameter detection method based on MIMO-FMCW radar as described above.

[0219] For example, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device.

[0220] The electronic device can be a mobile phone, desktop computer, laptop, handheld computer, cloud server, or other computing device. The electronic device may include, but is not limited to, processors and memory. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0221] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the electronic device, connecting all parts of the electronic device via various interfaces and lines.

[0222] The memory can be used to store the computer program and / or modules. The processor implements the computer program by running or executing the computer program and / or modules stored in the memory, and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area, wherein: the program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.); the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital card (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0223] Wherein: If the modules / units integrated in the electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a readable storage medium, and when the computer program is executed by a processor, it can implement the steps of the various method embodiments described above. Wherein: The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0224] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A multi-parameter detection method for particle streams based on MIMO-FMCW radar, characterized in that, Includes the following steps: S1. Arrangement in the detection area × The virtual channel array structure is used to obtain a digital signal matrix of multiple frames of measurement data corresponding to the detection area, wherein: The number of transmitting antennas, This refers to the number of receiving antennas; S2. Obtain multiple parameters of the particle flow in the detection area based on the digital signal matrix, where the multiple parameters include: velocity, distance, angle, and concentration; S2 specifically includes: S2.1 Obtaining the range-Doppler spectrum: Performing two-dimensional FFT processing on the digital signal matrix based on the range domain and pulse domain to obtain the range-Doppler spectrum, where: the range-Doppler spectrum includes range information and velocity information; S2.2, Estimating Angle Information and 3D Positioning: The angle information of the target particle is calculated based on the phase difference of the reflected echo signal of the target particle by each receiving antenna in the virtual channel array structure; and the angle information is combined with the range-Doppler spectrum to obtain the range-Doppler-angle 3D spectrum, where: the angle information includes azimuth and elevation angles; S2.3 Estimating Concentration Distribution: Estimating the concentration information of the particle flow based on the distance-Doppler-angle three-dimensional spectrum.

2. The multi-parameter detection method for particle streams based on MIMO-FMCW radar according to claim 1, characterized in that, S1 includes: S1.1 Configuring a MIMO-FMCW radar array: A transmitting antenna array and a receiving antenna array are arranged outside the detection area, and a virtual channel array structure is formed through MIMO processing. Transmission is performed using TDM mode, wherein: the virtual channel array structure includes... One virtual channel; S1.2 Transmitting FMCW signals: The transmitting antenna array continuously transmits linear FMCW signals within a predetermined frequency range, wherein the signal transmission frequency changes linearly with time; In S1.2, the linear frequency modulated signals of each virtual channel are transmitted alternately in time slots. Linear frequency modulation signal corresponding to each transmitting antenna The specific formula is as follows: ； in: It is the emission amplitude. It is the carrier frequency. Indicates the frequency modulation slope. Indicates the frequency modulation slope. It is the total signal bandwidth. It is a single frequency sweep cycle. Launch time; This is the number of the transmitting antenna. ; It is a complex number; S1.3 Receiving echo signals, specifically including: Under the scattering effect of the particle flow on the incident radar wave within the detection area, the receiving antenna array captures the reflected echo signal; where: the first The reflected echo signal corresponding to the receiving antenna The specific formula is as follows: ； in: It is the echo amplitude; It's the speed of light; For round-trip delay, , The target distance; The number of the receiving antenna. ; The low-frequency baseband beat frequency signal is obtained by mixing the reflected echo signal with the local oscillator signal of the receiving antenna array, as shown in the following formula: ； in: It is the first The low-frequency baseband beat frequency signal of the channel; The conjugate of the local oscillator signal of the receiving antenna array; The amplitude of the beat frequency signal. Beat frequency ; This refers to the high-frequency portion; The low-frequency baseband beat frequency signal is sampled by an analog-to-digital converter to form a digital signal matrix. The specific formula is as follows: ； in: Number the sampling points. It is the number of sampling points per pulse. , It is a single frequency sweep cycle. Sampling time, , For rate.

3. The multi-parameter detection method for particle streams based on MIMO-FMCW radar according to claim 2, characterized in that, S2.1 includes: To obtain distance information, specifically: ① For each pulse in the pulse domain, for the first pulse... Execution of the distance domain sequence of the channel Point-based two-dimensional FFT processing yields the first The complex amplitude and corresponding beat frequency of the distance element; ② According to the first The distance between the target particle and the transmitting antenna is calculated by using the beat frequency of the distance unit and the frequency modulation slope of the transmitting antenna array. The specific calculation formula is as follows: ； in: For the first Distance information of the distance unit; The speed of light; For the first The corresponding beat frequency of the distance unit, ; Obtain speed information, specifically: ① Collect data for each distance unit. Each pulse is obtained ,in: Number the pulse. ; ②, Regarding the first Execution of the distance domain sequence of the channel Point-based two-dimensional FFT processing yields the first Distance unit, first Doppler element complex amplitude and pulse repetition frequency ,in: , The frame time length; ③ Calculate the velocity corresponding to each Doppler element based on the pulse repetition frequency and the carrier frequency of the transmitting antenna. The specific calculation formula is as follows: ； in: For Doppler frequency shift, .

4. The multi-parameter detection method for particle streams based on MIMO-FMCW radar according to claim 3, characterized in that, S2.2 includes: S2.2.1, each Peak units are cascaded into vectors across all virtual channels. The power spectrum is obtained by performing FFT or beamforming along the virtual channel array structure index, where: It is the set of complex numbers; S2.2.2, Search Make the power spectrum At its maximum, it can obtain azimuth angles. and pitch angle Angle information; S2.2.

3. Combine the angle information corresponding to different target particles with the range-Doppler spectrum to obtain the range-Doppler-angle three-dimensional spectrum.

5. The multi-parameter detection method for particle streams based on MIMO-FMCW radar according to claim 4, characterized in that, 2.3 includes: S2.3.1 Construct voxels and calculate the volume of a single voxel. Specifically: Construct a range-resolved unit based on the bandwidth of the FMCW signal. The specific formula is as follows: ； Angle resolution units are constructed based on the number of virtual channels in the azimuth and elevation directions. The specific formula is as follows: ； in: For azimuth resolution units; For pitch angle resolution; It is the wavelength; Antenna spacing, ; It refers to the number of virtual channels in terms of orientation. It is the number of virtual channels in the pitch direction; Calculate the cross-sectional area corresponding to one angle resolution unit based on the angle resolution unit. ; ； in: Given a distance; Based on the cross-sectional area corresponding to the distance resolution unit and the angle resolution unit Calculate the volume of a single voxel The specific formula is as follows: ； S2.3.2 Judgment: If the number of particles in the detection area is less than 30%, the particle concentration in a single voxel is calculated using the target counting method; otherwise, the particle concentration in a single voxel is calculated using the echo amplitude accumulation method.

6. The multi-parameter detection method for particle streams based on MIMO-FMCW radar according to claim 5, characterized in that, In section 2.3.2, the echo amplitude accumulation method is used to calculate the particle concentration within a single voxel, specifically including: ① Record the background noise power spectrum when there are no particles. and compared with the original power spectrum obtained during measurement. Differential power spectrum is obtained by performing a differential operation. ,in: These are the distance, azimuth, and elevation indices, respectively, and the specific formulas are as follows: ； ② For each voxel The cumulative power is obtained by averaging or summing the measurement results from multiple pulses or frames. The specific formula is as follows: ； in: For frame number, This is the number assigned to each frame of measurement results; ③ The cumulative number of peak values ​​at the same voxel location collected in a reference container of known volume. The total number of particles was obtained from the reference container. Calibration determination coefficient The specific formula is as follows: ； ④ Based on cumulative power and the coefficient of determination estimation voxels Corresponding number of particles voxels are then obtained. Corresponding particle concentration The specific formula is as follows: ； 。 7. The multi-parameter detection method for particle streams based on MIMO-FMCW radar according to claim 6, characterized in that, In S2.3.2, the particle concentration within a single voxel is calculated using the echo amplitude accumulation method, specifically including: ① Perform constant false alarm rate detection on the distance-Doppler-angle three-dimensional spectrum and identify local peak points; ② Statistical analysis of a voxel within each or multiple frames. Total number of peak values ​​detected in The average peak count is obtained by averaging the total peak count across multiple frames. ; ③ In the reference container, the number of peak values ​​per unit voxel is also counted. and the known number of particles Perform linear fitting to obtain coefficients The specific formula is as follows: ； ④ Based on coefficients Calculate particle concentration The specific formula is as follows: ； in: This indicates the number of particles in the container.

8. The multi-parameter detection method for particle streams based on MIMO-FMCW radar according to any one of claims 1 to 7, characterized in that, S1.1 further includes: superimposing a periodic magnetic field in the detection area to synchronously modulate the scattering cross section of the magnetic particles; The process after S2.2 further includes: generating a particle velocity vector map, a flow velocity distribution map, and a spatial location information map based on the angle information, velocity information, and distance information, respectively; the process after S2.3 further includes: generating a concentration change curve based on the angle information and concentration information.

9. A readable storage medium, characterized in that, It stores computer program instructions, which, when executed by a processor, implement the particle flow multi-parameter detection method based on MIMO-FMCW radar as described in any one of claims 1 to 8.

10. An electronic device, characterized in that, include: The method for multi-parameter detection of particle streams based on MIMO-FMCW radar as described in any one of claims 1 to 8 includes at least one processor, at least one memory, and computer program instructions stored in the memory, wherein the computer program instructions are executed by the processor.

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