Millimeter wave radial enhancement imaging method and device

Abstract

The invention relates to the technical field of millimeter wave imaging, and provides a millimeter wave radial enhancement imaging method and device, and the method comprises the steps: controlling an MIMO millimeter wave radar array to scan a target region, and obtaining original echo data; performing reference-target-free delay phase self-correction by utilizing an array direct coupling signal, and eliminating phase errors between channels; the corrected data are converted into virtual array data, three-dimensional imaging is carried out through a distance accumulation algorithm, and traditional interpolation errors are avoided; and phase information of the target area is further extracted, a real phase is recovered by using a two-dimensional phase unwrapping algorithm, an accurate distance is calculated, and a high-precision radial profile of the target is reconstructed. According to the precise distance inversion method based on a self-correction mechanism of an array direct coupling signal and phase unwrapping, high-precision millimeter wave radial enhanced imaging without external reference is realized, the limitation of the traditional resolution ratio is effectively broken through, and the radial enhanced imaging with high precision, high resolution ratio and no external reference calibration is realized.

Description

Technical Field

[0001] This invention relates to the field of millimeter-wave imaging technology, and more specifically, to a millimeter-wave radial enhancement imaging method and imaging device. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Millimeter-wave radar, with its advantages of short wavelength, high resolution, strong penetration, and high safety due to non-ionizing radiation, has become the preferred sensing technology in key scenarios such as security inspection equipment, composite material structure inspection, and through-wall observation. To meet the needs of fine structure recognition and large-scene coverage, radar systems have developed a fusion scheme of multiple-input multiple-output (MIMO) architecture and synthetic aperture radar (SAR) imaging methods. This scheme combines the advantages of multi-channel spatial synthesis and virtual aperture expansion, achieving significant progress in improving three-dimensional imaging capabilities and becoming an important development direction for current millimeter-wave imaging systems.

[0004] The inventors discovered the following problems in the practical application of existing MIMO millimeter-wave SAR imaging technology: First, there is a delay phase error between channels, mainly due to inconsistent parameters of components in the RF link (such as power amplifiers, low-noise amplifiers, mixers, etc.), as well as time-varying errors caused by temperature changes and aging, resulting in significant defocusing problems in the image reconstruction results. Traditional calibration methods rely on specific reference targets or external instruments, which cannot adapt to complex field environments and are difficult to achieve online calibration. Second, there is a limited radial (range) resolution problem. Even when using range migration algorithms (such as RMA) combined with Stolt interpolation, it is difficult to achieve accurate resolution of close-range details or multi-layer structures due to high computational complexity and interpolation errors. More importantly, the range resolution of radar is limited by signal bandwidth. With limited bandwidth, it is difficult to distinguish fine structures or subtle differences between layers at close range. Although the phase of the intermediate frequency signal is sensitive to range, it is limited by phase entanglement and cannot be directly utilized. Summary of the Invention

[0005] To address the aforementioned issues, this invention proposes a millimeter-wave radial enhancement imaging method and device. Based on the self-calibration mechanism of directly coupled array signals and the precise distance inversion method of phase unwinding, it achieves high-precision millimeter-wave radial enhancement imaging without the need for external references. This effectively breaks through the traditional resolution limitations and realizes radial enhancement imaging with high precision, strong resolution, and no need for external reference calibration, making it suitable for complex scenarios such as security inspection and industrial non-destructive testing.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: One or more embodiments provide a millimeter-wave radial enhancement imaging method, comprising the following steps: The echo data after scanning the target area is acquired, and the array is used to directly couple the signal for correction. The corrected echo data is converted into virtual array data based on the principle of equivalent phase center and then transformed into three-dimensional wavenumber domain. For three-dimensional wavenumber domain data, a distance stacking algorithm is used to perform imaging processing by means of distance-by-distance slice compensation to obtain coarse imaging data containing target scattering coefficient and phase information; For the obtained coarse imaging data, the phase information of the target area is extracted, and the phase is processed by a two-dimensional phase unwinding algorithm based on reliability ranking. Based on the unwinding phase information, the accurate distance value of the pixel is calculated, and the high-precision range profile of the target object is reconstructed to obtain the radially enhanced imaging result.

[0007] One or more embodiments provide a millimeter-wave radial enhancement imaging apparatus, comprising: Millimeter-wave transceiver module, used to transmit linear frequency modulated continuous wave signals and receive echo signals; The scanning platform is used to drive the millimeter-wave transceiver module to scan the target area and achieve aperture synthesis; The signal processing module is configured to perform the steps in the millimeter-wave radial enhancement imaging method described above. One or more embodiments provide a millimeter-wave radial enhancement imaging apparatus, comprising: The phase error correction module is configured to acquire echo data after scanning the target area and perform correction using array direct coupling signals; The conversion module is configured to convert the corrected echo data into virtual array data based on the equivalent phase center principle, and perform three-dimensional wavenumber domain conversion; The range stacking imaging module is configured to perform imaging processing on three-dimensional wavenumber domain data using a range stacking algorithm and a range-by-range slice compensation method to obtain coarse imaging data containing target scattering coefficients and phase information. The phase unwinding and imaging module is configured to extract phase information of the target region from the obtained coarse imaging data, process the phase using a two-dimensional phase unwinding algorithm based on reliability ranking, calculate the precise distance value of the pixel based on the unwinding phase information, reconstruct a high-precision range profile of the target object, and obtain radially enhanced imaging results.

[0008] A computer program product includes a computer program / instructions that, when executed by a processor, implement the steps of the millimeter-wave radial enhancement imaging method described above. An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the steps in the millimeter-wave radial enhancement imaging method described above.

[0009] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the steps in the above-described millimeter-wave radial enhancement imaging method.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: The method of this invention improves the radial resolution of millimeter-wave imaging systems, eliminates system errors through self-calibration technology, achieves high-precision phase compensation without additional hardware, and enhances the system's stability and adaptability in field environments. The range stacking algorithm avoids the interpolation errors and computational burden of traditional Stolt interpolation, improving processing efficiency. Phase unwrapping and range inversion techniques allow the phase information of the intermediate frequency signal to be fully utilized for range reconstruction, overcoming the bandwidth limitation on resolution and enabling clear rendering of millimeter-scale details. The overall solution, while maintaining system simplification, significantly improves imaging accuracy and applicability, making it suitable for high-precision detection tasks in complex scenarios.

[0011] The advantages of the present invention, as well as its additional advantages, will be described in detail in the following specific embodiments. Attached Figure Description

[0012] The accompanying drawings, which form part of this invention, 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 a limitation thereof.

[0013] Figure 1 This is a flowchart of a millimeter-wave radial enhancement imaging method according to Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of a typical transceiver channel structure for multi-base antenna array imaging according to Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of a typical transceiver channel structure for multi-base antenna array imaging according to Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the distance stacking imaging and phase retrieval logic in Embodiment 1 of the present invention; Figure 5 This is a schematic diagram of the structure of a millimeter-wave radial enhancement imaging device according to Embodiment 2 of the present invention. Detailed Implementation

[0014] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0015] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0016] It should be noted that the terminology used herein is for describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof. It should be noted that, without conflict, the various embodiments and features within those embodiments can be combined with each other. The embodiments will now be described in detail with reference to the accompanying drawings.

[0017] Example 1 In one or more of the technical solutions disclosed in the embodiments, such as Figures 1 to 5 As shown, a millimeter-wave radial enhancement imaging method includes the following steps: Step 1: Acquire echo data after scanning the target area and perform correction using array direct coupling signals; Step 2: Convert the corrected echo data into virtual array data based on the principle of equivalent phase center, and perform three-dimensional wavenumber domain conversion; Step 3: For the three-dimensional wavenumber domain data, the distance stacking algorithm is used to perform imaging processing by compensating for distance slices one by one to obtain coarse imaging data containing target scattering coefficient and phase information. Step 4: For the obtained coarse imaging data, extract the phase information of the target area, process the phase using a two-dimensional phase unwinding algorithm based on reliability ranking, calculate the precise distance value of the pixel based on the unwinding phase information, reconstruct the high-precision range profile of the target object, and obtain the radially enhanced imaging result.

[0018] This implementation method is based on the fusion of MIMO millimeter-wave radar system and SAR imaging mechanism. First, it uses the direct coupling signal received by the array as a self-calibration reference to solve the problem of delay phase error introduced by device inconsistencies or environmental changes between channels, achieving online calibration without the need for an external reference target. Next, it constructs a virtual array using the equivalent phase center principle, increasing the array aperture, enhancing lateral spatial resolution, and completing data transformation in the three-dimensional wavenumber domain. Then, by introducing a range stacking algorithm, it compensates for the target's phase error by slicing it range-wise, effectively restoring the target's scattering characteristics and contour information, obtaining a coarse imaging result. Based on this, phase extraction is performed on the target area in the coarse imaging image. A reliability-ranked two-dimensional phase unwrapping method is used to remove the entangled phase, and then the accurate range value is retrieved based on the high-sensitivity phase information to construct a high-resolution range image, achieving the restoration of the target's surface microstructure and enhancing longitudinal imaging capabilities.

[0019] This implementation significantly improves the radial resolution of millimeter-wave imaging systems. It eliminates system errors through self-calibration technology, achieving high-precision phase compensation without additional hardware, and enhancing the system's stability and adaptability in field environments. The range stacking algorithm avoids the interpolation errors and computational burden of traditional Stolt interpolation, improving processing efficiency. Phase unwrapping and range inversion techniques allow the phase information of the intermediate frequency signal to be fully utilized for range reconstruction, overcoming bandwidth limitations on resolution and enabling clear rendering of millimeter-scale details. The overall solution maintains system simplification while significantly improving imaging accuracy and applicability, making it suitable for high-precision detection tasks in complex scenarios.

[0020] like Figure 2 As shown, a typical millimeter-wave transceiver channel in a MIMO millimeter-wave radar array includes devices such as an oscillator, power amplifier (PA), low-noise amplifier (LNA), mixer, filter, and switching network. Signals experience transmission delays as they pass through these devices, where the total delay along the transmission path is [missing information]. Total delay of the receiving path These represent the sum of the delays of each device along the path.

[0021] In step 1, the MIMO millimeter-wave radar array is controlled to scan the target area and acquire raw echo data; In step 1, the specific calibration process is as follows: Figure 3 As shown, the echo data is corrected using array-coupled signals, specifically including the following steps: Step 11: Based on the Identical Channel Design (ICD) assumption, extract the direct coupling signals of all channels, calculate the difference between the peak position of the direct coupling signal echo and the theoretical physical distance, and estimate the average delay value of all channels. Among them, the direct coupling signal is the signal that leaks directly from the transmitter to the receiver without being reflected by the target; it is automatically acquired when the radar pulse is actually transmitted, and the transmitting antenna sends FMCW or pulse signals; each receiving channel can receive a portion of the leakage component on all channels, especially the receiving antenna that is close to the transmitting antenna; the early, high-amplitude, non-target path waveform formed by these leaks is the direct coupling signal.

[0022] Due to inconsistencies in device parameters across different channels and variations with temperature and time, delay and phase errors occur between channels. First, based on the Identical Channel Design (ICD) assumption, the average delay of all channels is estimated using the difference between the peak position of the directly coupled signal and the physical spacing between the antennas. :

[0023] in, The observed direct coupling distance, Let m be the physical distance between the transmitting antenna and n be the receiving antenna, c be the speed of light, and M and N be the number of transmitting and receiving antennas, respectively. Step 12: Based on the multiple-transmit single-receive (MISO) structure and the single-transmit multiple-receive (SIMO) structure, estimate the forward delay of each transmit channel and the backward delay of each receive channel.

[0024] Construct multiple-in-one-out (MISO) and single-in-one-multiple-out (SIMO) architectures and estimate the forward delay of each transmit channel. and backward delay of each receiving channel .

[0025] Step 13, bias removal: Based on the average delay value, the forward and backward delays of each channel are debiased to obtain the estimated channel delay. The formula for calculating the channel delay after bias removal is as follows: ; Step 14: Based on the estimated delay of each channel, calculate the corresponding phase error, and then compensate for the phase of the received signal of each channel to obtain the corrected signal. This enables phase alignment and correction between channels; Based on the channel delay, the received signal of the corresponding channel will be... Phase shift correction is performed using the following formula: ; in, The corrected signal, The original signal, where c is the central wavenumber and c is the speed of light. This is the estimated channel delay after bias removal.

[0026] In the above implementation of this embodiment, a delay phase error model is established based on the direct coupling signals between MIMO array elements. The average channel delay and forward / backward delay are estimated using the same channel design assumption. The estimated delay phase error values ​​for each transmit and receive channel are calculated, and the original echo data is phase-corrected. This full-array self-calibration method avoids the dependence on external reference targets or environmental stability found in traditional schemes, significantly improving the system's practicality and adaptability. By separating and removing the forward / backward delay deviations of the channels, more accurate phase alignment is achieved, thereby eliminating systematic errors caused by inconsistent device parameters or temperature changes, ensuring the stability and accuracy of subsequent wavenumber domain transformation and image reconstruction. Furthermore, the signal correction process has excellent automation characteristics and can be embedded within the system for online real-time compensation, further improving imaging efficiency and system reliability.

[0027] In step 2, the corrected echo data is converted into virtual array data based on the principle of equivalent phase center, including the following steps: Step 21: Obtain the corrected five-dimensional echo data This includes the horizontal dimension (x-direction) of the transmitting antenna, the horizontal dimension (x-direction) of the receiving antenna, the vertical dimension (y-direction) of the transmitting antenna, the vertical dimension (y-direction) of the receiving antenna, and the radial dimension (z-direction). Step 22: Construct a virtual array based on the principle of equivalent phase center. Using the principle of equivalent phase center, the echo signal of each pair of transmit-receive antennas is equivalently mapped to a phase center point; this phase center point is the midpoint between the transmit antenna and the receive antenna, that is, the signal is considered to be generated and received by a virtual antenna located at the midpoint. The above process is Figure 4 The process of dimensionality reduction in Chinese data involves equivalence, after which five-dimensional data becomes three-dimensional, including only the horizontal, vertical, and radial dimensions.

[0028] Step 2, the method for wavenumber domain transformation of the virtual array data, includes the following steps: Step 201: Extract the converted virtual array data into multiple two-dimensional slice data along the distance direction. ; Step 202: Perform a two-dimensional Fourier transform on each slice of data to convert it to the wavenumber domain; after the transformation, we obtain... ; Step 3, Range Stacking Imaging RSA: For three-dimensional wavenumber domain data, a range stacking algorithm is used to perform imaging processing through range-by-range slice compensation to obtain coarse imaging data containing target scattering coefficients and phase information. This method includes the following steps: Step 31: Extract the distance depth of each distance slice data in the wavenumber domain. Generate the corresponding matched filter phase compensation factor. ; Step 32: Based on phase compensation factor Compensate the corresponding range slice data and integrate the phase information into the range slice data; Step 33: Stack all the compensated range slice data in the range direction to obtain a three-dimensional wavenumber data cube. ; Step 34: Perform a two-dimensional inverse Fourier transform to obtain the three-dimensional scattering coefficients, i.e., the target scattering coefficients, thus obtaining the three-dimensional image scattering distribution in the spatial domain and completing the coarse imaging: ; in, The three-dimensional scattering coefficient of the target. For three-dimensional echo data, FFT and IFFT represent Fourier transform and inverse transform, respectively. Image center correction factor For reference distance; Radial wavenumber This implementation achieves efficient 3D imaging without relying on traditional complex processing methods such as Stolt interpolation. By combining range stacking and phase compensation, it significantly reduces image blurring and energy leakage caused by phase misalignment at different depths, improving the focusing effect and resolution of the imaging. Simultaneously, this method avoids frequency domain interpolation calculations, improving overall computational efficiency and making it suitable for real-time processing requirements. The resulting coarse imaging data not only preserves the target's scattering intensity but also fully contains phase information, laying the foundation for subsequent accurate range reconstruction and enhanced imaging, and exhibiting good data coherence and physical consistency.

[0029] Step 4 involves phase retrieval and radial enhancement. Phase information of the target region is extracted and phase unwrapping is performed. Specifically, a two-dimensional phase unwrapping algorithm based on reliability ranking is used. The reliability value is determined by calculating the second-order difference of the pixel phase, and adjacent pixels are preferentially removed along paths with high reliability. A transition occurs, restoring continuous phase.

[0030] Specifically, step 4, the process of generating the radially enhanced imaging result, includes the following steps: Step 41, Phase Information Extraction: Extract the phase information of the target region data from the target scattering coefficients obtained by range-stacking imaging (RSA imaging); Because phase is usually confined to Directly calculating the distance between them will produce ambiguity; Step 42, Phase Unwrapping: A two-dimensional phase unwrapping algorithm based on reliability ranking is adopted. The reliability value is determined by calculating the second-order difference of the pixel phase. Phase unwrapping is preferentially performed along the path with high reliability to obtain the unwrapped continuous phase. ; Step 43: Utilize the high sensitivity of continuous phase to range (e.g., in a 60GHz radar, a 1 rad phase change corresponds to approximately 0.385 mm of range change) to calculate the precise radial range: ; in, For the precise radial distance to the target point, For reference distance, This is the center wavelength of the radar.

[0031] Step 44: Use the obtained precise distance values ​​to correct the voxel positions in the 3D image, reconstruct the radial depth information of the target, and obtain the target surface profile with high radial resolution.

[0032] This implementation method enhances radial resolution by utilizing phase information from the target region based on the preliminary 3D image generated by range stacking imaging (RSA). First, the phase values ​​of the corresponding pixels in the target region are extracted from the coarse imaging results. Since millimeter-wave intermediate frequency signals are highly sensitive to distance changes, their phase changes can be used for high-precision distance estimation. To address the discontinuity problem caused by phase entanglement, a two-dimensional phase untangling algorithm based on reliability ranking is employed. This algorithm calculates the phase change stability through the second-order difference of the pixel phase, establishes a pixel reliability ranking map, and prioritizes phase unwrapping along the path with the highest reliability to construct a continuous phase distribution. Subsequently, based on the functional relationship between millimeter-wave wavelength and phase, the phase distribution is converted into precise radial distance information, which is further used to correct the position of each voxel in the 3D image, achieving accurate depth localization of the target point. Finally, a high-precision contour map of the target surface is reconstructed, achieving longitudinal imaging enhancement.

[0033] The above-described implementation significantly improves the radial resolution of millimeter-wave imaging systems. By mining the phase information of the intermediate frequency signal, it breaks through the resolution bottleneck under traditional bandwidth-limited conditions, achieving sub-millimeter-level distance estimation accuracy. The employed two-dimensional phase unwinding strategy exhibits high robustness and adaptability, enabling stable recovery of continuous phase even in the presence of noise interference or complex structures, ensuring accurate distance inversion. Fine-tuning of the voxel positions in the three-dimensional image effectively reduces imaging artifacts and blurring, resulting in clearer and more accurate reconstructed target contours. This makes it suitable for high-precision applications such as complex microstructure detection and interlayer defect identification in composite materials. Furthermore, the process features high algorithmic modularity and computational parallelism, making it suitable for integration into automated imaging systems for real-time processing.

[0034] This embodiment achieves reference-free delayed phase self-correction by directly coupling signals to the array, ensuring basic phase accuracy. It also incorporates a distance stacking algorithm to avoid interpolation errors and further utilizes the phase information of the intermediate frequency signal to calculate precise distances through unwinding technology, thereby overcoming bandwidth limitations to achieve radial enhancement imaging. This method effectively overcomes the limitations of traditional imaging algorithms, offering advantages such as high imaging accuracy, high resolution, and no need for external reference calibration, making it suitable for complex scenarios such as security inspection and industrial non-destructive testing.

[0035] Example 2 Based on Embodiment 1, this embodiment provides a millimeter-wave radial enhancement imaging device, such as... Figure 5 As shown, it includes: Millimeter-wave transceiver module, used to transmit linear frequency modulated continuous wave signals and receive echo signals; The scanning platform is used to drive the millimeter-wave transceiver module to scan the target area and achieve aperture synthesis; The signal processing module is configured to perform the steps in the millimeter-wave radial enhancement imaging method described in Embodiment 1; Alternatively, it may include a display module for displaying the reconstructed 3D image and the radially enhanced target profile.

[0036] Specifically, the scanning platform includes a moving frame, motors mounted on the moving frame including an X-axis motor and a Y-axis motor, and fiber switches mounted on the moving frame; The X-axis motor and Y-axis motor are respectively connected to the stepper motor driver, and the signal processing module sends drive signals to control the operation of each motor.

[0037] The imaging device provided in this embodiment integrates MIMO radar with a high-precision mechanical scanning platform and combines advanced signal processing algorithms, which can effectively overcome the problems of phase error caused by inconsistent device parameters and low longitudinal resolution due to bandwidth limitation in traditional millimeter-wave imaging.

[0038] Experiments show that in tests on tilted metal plates (3cm in distance, less than the theoretical resolution of 3.75cm), the device successfully reproduced the tilt angle and surface details of the metal plates, verifying a significant improvement in radial resolution.

[0039] Example 3 Based on Embodiment 1, this embodiment provides a millimeter-wave radial enhancement imaging device, including: The phase error correction module is configured to acquire echo data after scanning the target area and perform correction using array direct coupling signals; The conversion module is configured to convert the corrected echo data into virtual array data based on the equivalent phase center principle, and perform three-dimensional wavenumber domain conversion; The range stacking imaging module is configured to perform imaging processing on three-dimensional wavenumber domain data using a range stacking algorithm and a range-by-range slice compensation method to obtain coarse imaging data containing target scattering coefficients and phase information. The phase unwinding and imaging module is configured to extract phase information of the target region from the obtained coarse imaging data, process the phase using a two-dimensional phase unwinding algorithm based on reliability ranking, calculate the precise distance value of the pixel based on the unwinding phase information, reconstruct a high-precision range profile of the target object, and obtain radially enhanced imaging results.

[0040] It should be noted that each module in this embodiment corresponds one-to-one with each step in embodiment 1, and their specific implementation process is the same, so it will not be repeated here.

[0041] Example 4 Based on Embodiment 1, this embodiment provides a computer program product, including a computer program / instruction, characterized in that, when the computer program / instruction is executed by a processor, it implements the steps of the millimeter-wave radial enhancement imaging method described in Embodiment 1.

[0042] The storage medium provided in this embodiment can permanently store computer instructions related to millimeter-wave radial enhancement imaging, ensuring that the system can repeatedly execute high-precision imaging tasks in different situations. This storage medium has efficient data access capabilities and plays a crucial role in real-time data processing and subsequent analysis during the measurement process. Through the pre-stored program instructions, users can directly perform imaging operations without needing to install additional complex applications.

[0043] Example 5 Based on Embodiment 1, this embodiment provides an electronic device, including a memory and a processor, as well as computer instructions stored in the memory and running on the processor. When the processor executes the computer instructions, it completes the steps in the millimeter-wave radial enhancement imaging method described in Embodiment 1.

[0044] Example 6 Based on Embodiment 1, this embodiment provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of a millimeter-wave radial enhancement imaging method described in Embodiment 1.

[0045] The electronic devices proposed in this invention can be mobile terminals or non-mobile terminals. Non-mobile terminals include desktop computers, while mobile terminals include smartphones (such as Android phones, iOS phones, etc.), smart glasses, smartwatches, smart bracelets, tablet computers, laptops, personal digital assistants, and other mobile internet devices capable of wireless communication.

[0046] It should be understood that in this invention, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0047] The memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of the memory may also include non-volatile random access memory. For example, the memory may also store information about the device type.

[0048] In implementation, each step of the above method can be completed by integrated logic circuits in the processor hardware or by instructions in software. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or by a combination of hardware and software modules in the processor. The software modules can reside in mature storage media in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here. Those skilled in the art will recognize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0049] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0050] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0051] If the aforementioned functions 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, the technical solution of the present invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0052] 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.

[0053] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A millimeter-wave radial enhancement imaging method, characterized in that, Includes the following steps: The echo data after scanning the target area is acquired, and the array is used to directly couple the signal for correction. The corrected echo data is converted into virtual array data based on the principle of equivalent phase center and then transformed into three-dimensional wavenumber domain. For three-dimensional wavenumber domain data, a distance stacking algorithm is used to perform imaging processing by means of distance-by-distance slice compensation to obtain coarse imaging data containing target scattering coefficient and phase information; For the obtained coarse imaging data, the phase information of the target area is extracted, and the phase is processed by a two-dimensional phase unwinding algorithm based on reliability ranking. Based on the unwinding phase information, the accurate distance value of the pixel is calculated, and the high-precision range profile of the target object is reconstructed to obtain the radially enhanced imaging result.

2. The millimeter-wave radial enhancement imaging method as described in claim 1, characterized in that: Correcting the echo data using array-coupled signals includes the following steps: Based on the assumption of the same channel design, the direct coupling signals of all channels are extracted, the difference between the peak position of the direct coupling signal echo and the theoretical physical distance is calculated, and the average delay value of all channels is estimated. Based on the multiple-transmit single-receive structure and the single-transmit multiple-receive structure, the forward delay of each transmit channel and the backward delay of each receive channel are estimated respectively. Based on the average delay value, the forward and backward delays of each channel are de-biased to obtain the estimated channel delay. Based on the estimated delays of each channel, the corresponding phase errors are calculated, and then the phase of the received signal for each channel is compensated to obtain the corrected signal. This enables phase alignment and correction between channels.

3. The millimeter-wave radial enhancement imaging method as described in claim 1, characterized in that: The method for wavenumber domain transformation of virtual array data includes the following steps: The transformed virtual array data is extracted into multiple two-dimensional slice data along the distance direction; Each slice of data is converted to the wavenumber domain by performing a two-dimensional Fourier transform.

4. The millimeter-wave radial enhancement imaging method as described in claim 1, characterized in that: For three-dimensional wavenumber domain data, a method is used to obtain coarse imaging data containing target scattering coefficients and phase information by employing a range stacking algorithm and performing imaging processing through range-wise slice compensation. The method includes the following steps: Extract the distance depth of each distance slice data in the wavenumber domain Generate the corresponding matched filter phase compensation factor. ; Based on phase compensation factor Compensate the corresponding range slice data and integrate the phase information into the range slice data; Stack all the compensated distance slice data in the distance direction; The three-dimensional scattering coefficients, i.e. the target scattering coefficients, are obtained by performing a two-dimensional inverse Fourier transform.

5. The millimeter-wave radial enhancement imaging method as described in claim 1, characterized in that: The process of generating radially enhanced imaging results includes the following steps: Phase information of the target region data is extracted from the target scattering coefficients obtained by range stacking imaging; A two-dimensional phase unwrapping algorithm based on reliability ranking is adopted. The reliability value is determined by calculating the second-order difference of the phase of each pixel, and the phase unwrapping is preferentially performed along the path with high reliability to obtain the continuous phase after unwrapping. ; Utilizing the high sensitivity of continuous phase to distance, the accurate radial distance can be calculated: The obtained precise distance values ​​are used to correct the voxel positions in the 3D image, reconstruct the radial depth information of the target, and obtain the target surface contour as the final imaging result.

6. A millimeter-wave radial enhancement imaging device, characterized in that, include: Millimeter-wave transceiver module, used to transmit linear frequency modulated continuous wave signals and receive echo signals; The scanning platform is used to drive the millimeter-wave transceiver module to scan the target area and achieve aperture synthesis; The signal processing module is configured to perform the steps of the millimeter-wave radial enhancement imaging method according to any one of claims 1-5.

7. A millimeter-wave radial enhancement imaging device, characterized in that, include: The phase error correction module is configured to acquire echo data after scanning the target area and perform correction using array direct coupling signals; The conversion module is configured to convert the corrected echo data into virtual array data based on the equivalent phase center principle, and perform three-dimensional wavenumber domain conversion; The range stacking imaging module is configured to perform imaging processing on three-dimensional wavenumber domain data using a range stacking algorithm and a range-by-range slice compensation method to obtain coarse imaging data containing target scattering coefficients and phase information. The phase unwinding and imaging module is configured to extract phase information of the target region from the obtained coarse imaging data, process the phase using a two-dimensional phase unwinding algorithm based on reliability ranking, calculate the precise distance value of the pixel based on the unwinding phase information, reconstruct a high-precision range profile of the target object, and obtain radially enhanced imaging results.

8. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the millimeter-wave radial enhancement imaging method according to any one of claims 1-5.

9. An electronic device, characterized in that, It includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, perform the steps in a millimeter-wave radial enhancement imaging method according to any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, complete the steps in a millimeter-wave radial enhancement imaging method according to any one of claims 1-5.

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