A high-resolution radar through-wall imaging method based on fusion of multiple communication signals and spatial spectrum shift

Abstract

The application discloses a kind of high-resolution microwave through-wall imaging methods based on cellular base station multi-mode communication signal fusion and space spectrum shift, face integrated application scene of sensing.The method comprehensively utilizes the spectrum resource of multiple orthogonal frequency division multiplexing (OFDM) communication signals coexisting in cellular base station, introduces space spectrum shift imaging method, and combines wall structure path compensation algorithm, realizes the high-resolution imaging of target.The present application is based on distributed cellular base station transmission and reception architecture, fusion multiple OFDM signals and the resolution advantage of space spectrum shift, effectively overcome the shortcomings of existing through-wall imaging technology in low resolution, target contour fuzzy etc., significantly improve the definition of imaging and the accuracy of target identification.The method uses base station communication signal to realize high-resolution through-wall imaging, is suitable for security monitoring, anti-terrorism search and rescue etc. through-wall detection scene in city, and has important significance to improve the through-wall radar imaging performance and the ability of integrated application scene of sensing.

Description

Technical Field

[0001] This invention relates to the field of integrated through-wall radar imaging and communication sensing, specifically to a high-resolution through-wall radar imaging method based on the fusion of multiple communication signals and spatial spectrum shifting. This method is particularly applicable to the various types of cellular base stations and their different communication standards (3G, 4G, 5G, etc.) widely covering urban environments. By fusing multiple communication signals of different standards to fill the spatial spectrum matrix and then using a convolution shifting strategy, the resolution limitation of standard narrow-bandwidth communication signals is effectively overcome, thereby achieving high-resolution imaging of targets obscured by walls. Background Technology

[0002] With the development of modern building technology, complex structures and thick walls are widely used in urban environments, posing a severe challenge to traditional through-wall radar imaging technology. When traditional microwave imaging technology penetrates such walls for target detection, it generally faces problems such as low resolution, blurred imaging, target defocus, and positional shift, making it difficult to meet the high-precision perception requirements of applications such as security monitoring, disaster relief, and building monitoring.

[0003] On the other hand, fifth-generation (5G) and sixth-generation (6G) mobile communication technologies are driving the rapid development of "Integrated Communication and Sensing" (ISAC). As core nodes of urban cellular networks, macro base stations and micro base stations are densely deployed, possessing natural advantages such as wide coverage, superior location, and abundant hardware resources. This has prompted academia and industry to explore the use of ubiquitous communication infrastructure to collaboratively complete high-precision environmental perception and target localization tasks, namely "Integrated Communication and Sensing." Integrated communication and sensing in urban base stations has become one of the key technological directions for future wireless networks. Its core objective is to achieve deep integration and resource sharing of communication and sensing functions, thereby empowering various smart city applications at extremely low marginal costs.

[0004] However, integrating sensing technology, especially using urban base station communication signals for through-wall imaging, still faces many technical bottlenecks:

[0005] The inherent contradiction between sensing resolution and communication efficiency: High-resolution imaging typically requires extremely high bandwidth and large aperture arrays, which contradicts the design goals of communication systems, which prioritize spectral efficiency and link reliability. The signal resources and array aperture of a single base station are limited, making it difficult to simultaneously meet the requirements of high distance and high angular resolution when used directly for imaging.

[0006] Waveform distortion caused by walls: Electromagnetic waves undergo refraction, reflection, and attenuation when penetrating walls, leading to changes in signal propagation path, phase distortion, and increased time delay. Without precise compensation, this will directly cause image defocusing and target positioning errors, which is crucial for imaging algorithms that rely on accurate path measurements.

[0007] The non-cooperative and heterogeneous nature of signal sources: In the ideal model of integrated sensing, the sensing party may not be able to control the transmission parameters of all communication signals. How to effectively fuse heterogeneous OFDM signals transmitted from different base stations with different center frequencies, bandwidths and modulation parameters, and extract consistent sensing information from them, is a huge challenge.

[0008] Existing through-wall imaging solutions, such as those based on sparse reconstruction or compressed sensing, can recover targets to some extent using limited data. However, their complex optimization algorithms are computationally intensive, have low operating efficiency, and heavily rely on prior models or training data, making it difficult to meet the real-time and robustness requirements of integrated sensing systems.

[0009] In summary, in the context of integrated sensing, there is an urgent need for an innovative through-wall imaging method. This method should fully utilize the abundant multi-base station and multi-standard communication signal resources in cities, overcome the limitations of a single signal source and the wall effect through effective signal fusion and processing mechanisms, and ultimately achieve efficient, high-resolution, and low-cost through-wall sensing within the framework of the communication network. This invention is proposed based on this objective. Summary of the Invention

[0010] The purpose of this invention is to overcome the shortcomings of existing through-wall radar imaging technology, such as low resolution, large data volume, high equipment cost, and strong dependence on prior information, and to provide a high-resolution radar through-wall imaging method based on the fusion of multiple communication signals and spatial spectrum shifting.

[0011] To achieve the above objectives, the present invention adopts the following technical solution:

[0012] A high-resolution radar through-wall imaging method based on the fusion of multiple communication signals and spatial spectrum shifting is proposed. Its core lies in achieving high-resolution, high-precision through-wall imaging through a distributed cellular base station structure, the fusion of multiple OFDM communication signals, wall path compensation, and spatial spectrum shifting technology. The method specifically includes the following steps:

[0013] Step 1: Construct a distributed cellular base station transmit and receive antenna system: A coprime MIMO array structure consisting of M transmit elements and N receive elements is adopted, where the element spacing between the transmit and receive subarrays is d. This structure can achieve a larger equivalent aperture with fewer physical elements, laying the foundation for high angular resolution imaging, while effectively reducing system complexity and hardware cost.

[0014] Step 2: Transmitting and Receiving Signals: The M transmitting array elements transmit wide-bandwidth OFDM signals into the detection area behind the wall. After being scattered by the target, the echo signals are received by the N receiving array elements.

[0015] Step 3: Wall Path Compensation and Signal Preprocessing: Based on the known dielectric constant and thickness of the wall, a wall structure path compensation algorithm based on the law of refraction is used to accurately compensate for the increased propagation time delay and refraction effect caused by the wall in the echo signal, correcting phase distortion to eliminate target defocus and position offset. Subsequently, the time waveform information carried by the transmitted signal itself in the echo signal is removed, and the signal component containing only the target's spatial position information is extracted.

[0016] Step 4: Spatial Spectrum Generation and Shifting: The compensated and preprocessed signal is analyzed, and its phase information is mapped to the spatial frequency domain to generate the original spatial frequency points corresponding to each transmit-receive antenna pair. Through mathematical transformations, these frequency points are filled to construct the initial spatial spectrum matrix.

[0017] Step 5: Multi-signal spectrum fusion: Utilizing the rich subcarrier characteristics of various OFDM communication signals, the spectrum of signals with different carrier frequencies, bandwidths, and subcarriers is systematically converged and fused to form a spatial spectrum matrix covering all base station transceiver antenna combinations and all communication signals. This process is equivalent to filling the spatial frequency domain with more and wider-distributed frequency points, significantly expanding the effective coverage of the spatial spectrum, thereby overcoming the limitations of resolution imposed by the bandwidth of a single signal or the array aperture.

[0018] Step 6, Spatial Spectrum Shift: Perform pairwise convolutions on the spatial frequency points in the spatial spectrum matrix obtained in Step 5 to form new spatial frequency and spatial spectral point information, and then fill these into the new spatial spectrum matrix.

[0019] Step 6, High-resolution imaging: Perform a two-dimensional inverse Fourier transform on the spatial spectrum matrix obtained in Step 6 to directly remap the spatial spectrum information to the image domain, and finally reconstruct a high-resolution, high-precision radar image of the target behind the wall.

[0020] The beneficial effects of this invention are as follows:

[0021] By leveraging existing cellular base station infrastructure and integrating various OFDM signal spectrum resources inherent in the city, the spatial bandwidth is first expanded. Then, through spatial spectrum convolution shifting, a spatial spectrum matrix with multiple expansion is achieved, further increasing the spatial bandwidth. This enables high-resolution through-wall imaging without actually increasing hardware complexity or changing the communication signal waveform.

[0022] A precise wall path compensation algorithm was introduced to effectively correct the phase distortion and propagation path changes caused by electromagnetic waves passing through the wall, which greatly reduced the problems of image defocusing and target position offset, and improved the imaging accuracy. Attached Figure Description

[0023] Figure 1This is a schematic diagram of the processing flow of the present invention.

[0024] Figure 2 This is a schematic diagram of a three-dimensional scene of the present invention.

[0025] Figure 3 A schematic diagram of wall structure path compensation for verification simulation in this invention.

[0026] Figure 4 The images presented in this invention are the results of fusing different OFDM signals. (a) shows the imaging result using only signal 1 from Table 1; (b) shows the imaging result using signals 1-5 from Table 1; and (c) shows the imaging result using signals 1-6 from Table 1. Detailed Implementation

[0027] The following will describe in detail, with reference to the accompanying drawings, a high-resolution radar through-wall imaging method based on the fusion of multiple communication signals and spatial spectrum shifting, according to the present invention. This embodiment is only used to clearly illustrate the technical solution of the present invention and is not intended to limit the scope of protection of the present invention.

[0028] A through-wall radar imaging method based on spatial spectrum shifting effectively improves the resolution and anti-interference capability of through-wall radar imaging by combining distributed cellular base stations, high-bandwidth signals with spatial spectrum shifting, and wall structure path compensation algorithms.

[0029] Constructing imaging scenes, such as Figure 2 and Figure 3 As shown, the wall thickness is set to d, and its relative permittivity is ε. r (This can be obtained through pre-measurement or by consulting a database of common building materials). A coprime base station receiving system is deployed on one side of the wall. Its transmitting array contains M elements, and its receiving array contains N elements, with an element spacing of d (typically half the wavelength λ / 2). M and N are coprime integers. This design aims to generate a uniform linear array with M×N virtual elements with the fewest physical elements, thereby greatly expanding the equivalent aperture.

[0030] The target echo signal is received by the receiving base station receiving subarray. First, M OFDM signals are transmitted using the transmitting base station. s ,in For signal amplitude, f c The center frequency of the signal. Δf Let n be the subcarrier spacing and n be the number of subcarriers. After the signal is transmitted from the transmitting antenna, the microwaves illuminate the object and are scattered by the object. Assuming the object's size is much larger than the wavelength, the object can be considered as a set of scattering points. Assume there are Q targets in the far field of space. Let be the scattering coefficient of the target object's scattering point. After being reflected by Q targets in space, the M signals are received by N elements of the receiving subarray. The echo signal expression is:

[0031]

[0032] The echo signal can be considered as a modulation component carrying target information superimposed on the original communication signal, where This refers to the actual path length from the transmitting antenna to the target, affected by the wall during the beam's penetration. Similarly... This is the actual path length of the beam from the target to the receiving antenna.

[0033] Path compensation processing is performed on the echo signal based on the wall structure. Due to the high dielectric constant of the wall, the propagation time delay of electromagnetic waves is increased, and refraction occurs at the wall-air interface, causing defocusing and positional shift of the target image.

[0034] Taking the two-dimensional wall structure path compensation algorithm as an example, the equivalent length from the antenna to the target can be expressed as:

[0035]

[0036] in, Let be the dielectric constant of the wall. For transmitting antenna To the point where the wall meets the air The straight-line distance The boundary between the wall and the air To the target The straight-line distance.

[0037] The equivalent electric length can be further calculated using the law of refraction and the angle of incidence. express:

[0038]

[0039] in, For transmitting antenna To the target The straight-line distance For the thickness of the wall, The elevation angle of the beam. The azimuth angle of the beam.

[0040] To avoid angle of incidence The calculation can be further approximated as:

[0041]

[0042] in, To transmit beam and The angle between axes.

[0043] The time waveform information carried by the transmitted signal is removed from the echo signal. The wall structure path compensation algorithm in 3D spatial imaging is similar to that in 2D wall structure path compensation, and the wall structure path compensation algorithms for receiving and transmitting antennas are similar. To extract spatial information from the echo signal, other useless information needs to be removed; therefore, the first step is to eliminate… The time waveform information carried within it is obtained through... get:

[0044]

[0045] set up This formula can be further transformed using Taylor expansion:

[0046]

[0047] Subsequently, the above Substituting the expression In the phase term, the term that is independent of the target coordinates is the constant phase term. Eliminating this term yields an expression that is only related to the spatial frequency and the target position, namely:

[0048]

[0049] The above equation is essentially a spatial frequency point, and its corresponding spatial frequency can be expressed as:

[0050]

[0051] The above process essentially achieves spatial decoupling of the Fourier basis. This process is applied to the echoes at all antenna locations and filled into a spatial spectrum matrix, thus completing the generation of the original spatial spectrum.

[0052] By constructing and fusing a spatial spectrum matrix using multiple OFDM signals, the spatial frequency points are expanded, thereby improving imaging resolution.

[0053] The echo signal can be represented as:

[0054]

[0055] This form is the same as the two-dimensional discrete Fourier transform form, so the target image can be obtained by performing a two-dimensional inverse Fourier transform on the original spatial spectrum matrix.

[0056] Imaging experiments were conducted using the above algorithm. A 9-transmitter, 9-receiver antenna and various OFDM signals were used to perform through-wall imaging on a 37cm thick wall. The various OFDM signals used are shown in Table 1. Figure 4(a) is the imaging result of a single signal 1 in Table 1. It can be clearly seen that the upper and lower points in the imaging result are aliased and cannot be distinguished. Figure 4 (b) shows the imaging results of signals 1-5 in Table 1. Through the fusion of multiple communication signals, the four imaging points can be clearly distinguished, but there are still some imaging artifacts. (c) shows the imaging results of signals 1-6 in Table 1. The four imaging points are clearly distinguished, and the artifacts are somewhat eliminated. The maximum resolution can reach about 15cm. This verifies the high-resolution radar through-wall imaging method based on the fusion of multiple communication signals and spatial spectrum shifting, and achieves the expected effect of this invention.

[0057] Table 1: OFDM signals used in the experiment

[0058]

Claims

1. A high-resolution microwave through-wall imaging method based on the fusion of multiple communication signals and spatial spectrum shifting, characterized in that, Includes the following steps: Step 1, Signal Transmission and Reception: Using a coprime cellular base station system, each cellular base station can transmit and receive signals. Its transmitting array contains M array elements and its receiving array contains N array elements. The transmitting array elements are controlled to transmit various OFDM communication signals to the detection area behind the wall, and the receiving array elements are used to receive the echo signals from the detection area behind the wall. Step 2, Wall Path Compensation and Demodulation: Based on the electromagnetic parameters of the wall, the echo signal is compensated for its propagation path to correct the phase distortion and propagation path changes caused by the wall; and the echo signal is demodulated to eliminate the time waveform information carried by the transmitted signal itself in the echo signal and extract the baseband phase signal that is only related to the target spatial position. Step 3, Joint Spatial Spectrum Construction Step: The demodulated baseband phase signal is mapped to a unified spatial frequency domain coordinate system according to the corresponding physical location of the transmitting source and the geometric relationship between the receiving array and the base station, to generate the subspace spectrum corresponding to each communication signal under each transceiver base station combination; Step 4, Spectrum Fusion and Transfer: The multiple subspace spectra are fused and filled into a new spatial spectrum matrix. By convolving the frequency points in the spatial spectrum matrix pairwise, new spatial frequencies and spatial frequency points are generated, and a new joint spatial spectrum is regenerated. Its coverage in the spatial frequency domain is greater than that of a certain subspace spectrum. Step 5: High-resolution imaging: Perform a two-dimensional inverse Fourier transform on the joint spatial spectrum to reconstruct a high-resolution image of the target behind the wall.

2. The high-resolution microwave through-wall imaging method based on the fusion of multiple communication signals and spatial spectrum shifting according to claim 1, characterized in that, The cellular base station described in step one serves as a transmit and receive antenna structure, with a total number of array elements of M+N, where M and N are coprime.

3. The method according to claim 1 or 2, characterized in that, The wall path compensation and demodulation steps described in step two refer to the compensated equivalent path length for the path from the transmitting antenna m to the target q. Represented as: in, Let m be the straight-line distance from the transmitting antenna to the target q. For wall thickness, The relative permittivity of the wall is . The angle between the emitted beam and the direction of the wall normal.

4. The method according to claim 1, characterized in that, Step two involves demodulating the echo signal to eliminate the time waveform information carried by the transmitted signal, thereby improving the reception signal. With the corresponding transmission signal Conjugate multiplication is used to obtain a signal containing only path phase information. .

5. The method according to claim 1 or 4, characterized in that, The spatial frequency of the joint spatial spectrum mentioned in step three Determined by the following formula: in, For signal frequency, At the speed of light, The angle related to the transmitting antenna m, Let n be the angle with the receiving antenna n.

6. The method according to claim 1, characterized in that, The spectrum fusion and shifting step described in step four refers to fusing the spectra of multiple OFDM communication signals with different center frequencies, bandwidths, or transmission positions, and then convolving and shifting the fused spatial spectrum matrix to effectively expand the system's synthetic bandwidth and synthetic aperture.

7. The method according to claim 1, characterized in that, The two-dimensional inverse Fourier transform described in step five is applied to the spatial spectrum matrix obtained after the fusion in step four, which is filled more densely and has a wider coverage in the spatial frequency domain.

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