Microwave Imaging Method Research Articles

Object Localization in Highly Cluttered Environments Using Neural Network Learning on Microwave Scattering Data

ABSTRACTBifocusing‐based microwave imaging is a promising direct imaging method for object localization in various applications. However, the method has the limitation that it only works well in environments with a homogenous background. In this paper, we present a direct microwave imaging method using a neural network (NN) model that can localize a small object even in highly cluttered environments with strong scatterers. The NN model is trained on some data sets obtained through multistatic measurements in a nonhomogeneous environment. To verify the approach, we prepared an experimental testbed equipped with a water tank containing 3 strong scatterers and 16 antennas to obtain 920 MHz multistatic scattering data. This experiment shows good localization performance, with an average localization error of approximately 4 mm (1/9 of a wavelength) over the entire experimental area, even in a strong scattering background.

Microwave Tomography Method for Solving the Inverse Problem on Cylindrical Bodies

Microwave Tomography Method for Solving the Inverse Problem on Cylindrical Bodies

Near-Field Microwave Imaging Method of Monopole Antennas Based on Nitrogen-Vacancy Centers in Diamond.

Visualizing the near-field distribution of microwave field in a monopole antenna is very important for antenna design and manufacture. However, the traditional method of measuring antenna microwave near field distribution by mechanical scanning has some problems, such as long measurement time, low measurement accuracy and large system volume, which seriously limits the measurement effect of antenna microwave near field distribution. In this paper, a method of microwave near-field imaging of a monopole antenna using a nitrogen-vacancy center diamond is presented. We use the whole diamond as a probe and camera to achieve wide-field microwave imaging. Because there is no displacement structure in the system, the method has high time efficiency and good stability. Compared with the traditional measurement methods, the diamond probe has almost no effect on the measured microwave field, which realizes the accurate near-field imaging of the microwave field of the monopole antenna. This method achieves microwave near-field imaging of a monopole antenna with a diameter of 100 µm and a length of 15 mm at a field of view of 5 × 5 mm, with a spatial resolution of 3 µm and an imaging bandwidth of 2.7~3.2 GHz, and an optimal input microwave phase resolution of 0.52° at a microwave power of 0.8494 W. The results provide a new method for microwave near-field imaging and measurement of monopole antennas.

Microwave Imaging Method Based on Reconfigurable Spatial Dispersion Radiation

Microwave Imaging Method Based on Reconfigurable Spatial Dispersion Radiation

A Measurement Mode Selection Method for Computational Microwave Imaging

A Measurement Mode Selection Method for Computational Microwave Imaging

A Modified Microwave Imaging Method for Brain Stroke Detection

A Modified Microwave Imaging Method for Brain Stroke Detection

Improved Methods for Fourier-Based Microwave Imaging.

Fourier-based imaging has been widely adopted for microwave imaging thanks to its efficiency in terms of computational complexity without compromising image resolution. Together with other backpropagation imaging algorithms like delay-and-sum (DAS), they are based on a far-field approach to the electromagnetic expression relating to fields and sources. To improve the accuracy of these techniques, this contribution presents a modified version of the well-known Fourier-based algorithm by taking into account the field radiated by the Tx/Rx antennas of the microwave imaging system. The impact on the imaged targets is discussed, providing a quantitative and qualitative analysis. The performance of the proposed method for subsampled microwave imaging scenarios is compared against other well-known aliasing mitigation methods.

Designs of three different octagonal-shaped antennas for microwave-based breast cancer detection

Today, there are numerous studies on Microwave Imaging Methods. Thanks to these studies, the success and accuracy rate, especially in breast cancer diagnosis, increases. Microstrip antennas are used in the microwave imaging method. In this study, three different antenna models aimed to be used in microwave imaging methods were designed on the CST Studio Suite program. The designed antennas have been tested on the phantom model in the simulation environment. The test results were examined, and the designed antennas were produced using 3D printing technology. The built antennas were tested in the laboratory using the phantom and tumor-containing phantom models and obtained results were compared.

Real-Time 3D Microwave Medical Imaging With Enhanced Variational Born Iterative Method.

In this paper, we present a new variational Born iterative method (VBIM) for real-time microwave imaging (MWI) applications. The S-parameter volume integral equation and waveport vector Green's function are implemented to utilize the measured signal of the MWI system. Meanwhile, the real and imaginary separation (RIS) approach is used at each iterative step to simultaneously reconstruct the dielectric permittivity and conductivity of unknown objects. Compared with the Born iterative method and distorted Born iterative method, VBIM requires less computational time to reach the convergence threshold. The graphics processing unit based acceleration technique is implemented for real-time imaging. To demonstrate the efficiency and accuracy of this VBIM-RIS method, synthetic analysis of a complex multi-layer spherical phantom is first conducted. Then, the algorithm is tested with measured data using our new MWI system prototype. Finally, a synthetic brain-tumor phantom model under a thermal therapy procedure is monitored to exemplify the real-time imaging with about 5 seconds per reconstruction frame.

Sparse-Induced Current-Based Real-Time Microwave Imaging Method

Sparse-Induced Current-Based Real-Time Microwave Imaging Method

Continuous Monitoring of Hyperthermia Treatment of Breast Tumors With Singular Sources Method

Qualitative microwave imaging methods provide a fast and accurate reconstruction of the shapes of the targets from scattered electric field measurements. In this paper, a qualitative imaging method, the singular sources method (SSM), is analyzed for two-dimensional transverse magnetic electromagnetic (2D-TM EM) inverse scattering scenarios. The contribution of the paper can be briefly summarized as: (i) The SSM was previously proposed for the far-field scenario, here we extend the SSM in the near field - inhomogeneous background setup. While making the extension each step (which includes an integral equation) is explained by exploiting the linearity and reciprocity principles to give physical insights. (ii) The relation between the electrical parameters of the scatterers and the indicator of SSM is derived. (iii) To analyze the performance of SSM in real-world problems, the proposed method is tested for monitoring hyperthermia treatment problems with a realistic breast model. Obtained results show that the SSM can handle realistic breast phantoms for monitoring hyperthermia problems.

Wide-field microwave imaging using nitrogen-vacancy center ensembles in diamond

Microwave chips dependent devices constitute the cornerstone of many classical and emerging quantum technologies. To meet the demand for high-resolution, lossless, and fast wide-field imaging of microwave devices, we propose a wide-field microwave imaging method based on diamond nitrogen-vacancy center ensembles by combining continuous wave optically detected magnetic resonance technology with optical wide-field imaging technology. First, the optimal selection of laser parameters is achieved by measuring different laser powers. Then the accuracy of the wide-field microwave imaging technique is demonstrated by measuring the near-field imaging of the antenna surface at different microwave input powers and different microwave input frequencies. The spatial resolution of the imaging system is 5 μm over a field of view of 2400 μm × 1350 μm, and the optimal microwave precision measurement sensitivity is 5.6 μT / Hz1/2. The above results are expected to provide a practical reference for applications such as fault diagnosis of highly integrated microwave circuits, antenna radiation profiling, and electro magnetic compatibility testing of integrated microwave circuits.

A Neural Network-Based Microwave Imaging Method for Object Localization

This paper presents a new microwave imaging method using artificial neural networks to localize an object. The trained neural network reconstructs a tomographic image from the measured scattering data, such as a nonlinear electromagnetic inverse scattering solver. The appropriate number of hidden neurons is determined through the cross-entropy between network predictions and target values. To verify this method experimentally, we set up a testbed consisting of 16 antennas that transmit and receive 950 MHz microwaves underwater and used a metal rod with a diameter of 2 mm as a localizing target. The results show excellent imaging performance with fewer artifacts and less than a 2-mm localization error.

Breast Tumor Detection and Classification Based on Microwave Imaging

Limitations caused by traditional breast cancer detection and screening techniques have encouraged researchers to investigate alternative solutions. This study examines the use of a microwave-based approach for tumor detection in breast tissue and related tumor type classification using matched-filtering. Radar-like confocal microwave imaging (CMI) method constructs the foundation of such tumor detection approach. In particular, a microwave pulse is first transmitted, then back-scattered pulses are collected. All major reflective sites in the breast tissue are detected by repeating this procedure on a microwave pulse transmission-reception grid, aligning captured signals in-time to focus on a particular region in the breast tissue and superimposing such time-shifted signals to improve signal-to-clutter level. In the observed signals, clutter is originated by the heterogeneity of the breast tissue while signal is originated by a tumor site as a function of its water content.
 All calculations, in the study, were performed computationally in terms of a 3D Finite-Difference Time-Domain (FDTD) simulation models. For the antenna system, two cross-polarized resistively loaded bow-ties antennas were used in the computational model, and the tumor site was modeled using five different size and morphologies. Matched-filtering, on the other hand, was performed matching such obtained observations with that of a homogenous breast tissue, namely clutter-free model. Performance of the proposed approach was tested for two different antenna array resolutions, and it was observed that this parameter is important for successful detection and classification of a tumor-site in a realistic heterogenous breast tissue model.

Combination of Sentinel-1 and Sentinel-2 Data for Tree Species Classification in a Central European Biosphere Reserve

Microwave and optical imaging methods react differently to different land surface parameters and, thus, provide highly complementary information. However, the contribution of individual features from these two domains of the electromagnetic spectrum for tree species classification is still unclear. For large-scale forest assessments, it is moreover important to better understand the domain-specific limitations of the two sensor families, such as the impact of cloudiness and low signal-to-noise-ratio, respectively. In this study, seven deciduous and five coniferous tree species of the Austrian Biosphere Reserve Wienerwald (105,000 ha) were classified using Breiman’s random forest classifier, labeled with help of forest enterprise data. In nine test cases, variations of Sentinel-1 and Sentinel-2 imagery were passed to the classifier to evaluate their respective contributions. By solely using a high number of Sentinel-2 scenes well spread over the growing season, an overall accuracy of 83.2% was achieved. With ample Sentinel-2 scenes available, the additional use of Sentinel-1 data improved the results by 0.5 percentage points. This changed when only a single Sentinel-2 scene was supposedly available. In this case, the full set of Sentinel-1-derived features increased the overall accuracy on average by 4.7 percentage points. The same level of accuracy could be obtained using three Sentinel-2 scenes spread over the vegetation period. On the other hand, the sole use of Sentinel-1 including phenological indicators and additional features derived from the time series did not yield satisfactory overall classification accuracies (55.7%), as only coniferous species were well separated.

A Three-Dimensional Microwave Sparse Imaging Approach Using Higher-Order Basis Functions

This paper presents a novel method for three-dimensional microwave imaging based on sparse processing. To enforce the sparsity of the unknown function, we take advantage of the fact that arbitrary three-dimensional electromagnetic fields can be decomposed into two components with respect to the radial direction: one with transverse-magnetic polarization and the other with transverse-electric polarization. Each component can be further expressed as a sum of spherical harmonics, which provide the dictionary exploited by the sparse processing algorithm. Our measurement model relates the data and the parameters of the spherical harmonics’ sources, which are uniformly distributed on a grid sampling the imaging domain. By relying on the theory of degrees of freedom of electromagnetic fields, it can be shown that only a few harmonics are sufficient to accurately represent the measured scattered field from objects whose diameter is of the order of the wavelength, thus allowing reducing the dimension of the adopted dictionary. We analyze several imaging scenarios to assess the algorithm’s performance, including different object shapes, sensor orientations, and signal-to-noise ratios. Moreover, we compare the obtained results with other state-of-the-art linear imaging techniques. Notably, thanks to the adopted dictionary, the proposed algorithm can yield accurate images of both convex and concave objects.

Experimental Evaluation of an Axillary Microwave Imaging System to Aid Breast Cancer Staging

The number of metastasised Axillary Lymph Nodes (ALNs) is a key indicator for breast cancer staging. Its correct assessment affects subsequent therapeutic decisions. Common ALN screening modalities lack high enough sensitivity and specificity. Level I ALNs produce detectable backscattering of microwaves, opening the way for Microwave Imaging (MWI) as a complementary screening modality. Radar-based MWI is a low-cost, non-invasive technique, widely studied for breast cancer and brain stroke detection. However, new specific challenges arise for ALN detection, which deter a simple extension of existing MWI methods. The geometry of the axillary region is more complex, limiting the antenna travel range required for maximum resolution. Additionally, unlike breast MWI setups, it is impractical to use liquid immersion to enhance energy coupling to the body; therefore, higher skin reflection masks ALNs response. We present a complete study that proposes dedicated imaging algorithms to detect ALNs dealing with the above constraints, and evaluate their effectiveness experimentally. We describe the developed setup based on a 3D-printed anthropomorphic phantom, and the antenna-positioning configuration. To the authors’ knowledge, this is the first ALN-MWI study involving a fully functional anatomically compliant setup. A Vivaldi antenna, operating in a monostatic radar mode at 2-5 GHz, scans the axillary region. Pre-clinical assessment in different representative scenarios shows Signal-to-Clutter Ratio higher than 2.8 dB and Location Error lower than 15 mm, which is smaller than considered ALN dimensions. Our study shows promising level I ALN detection results despite the new challenges, confirming MWI potential to aid breast cancer staging.

Hybrid Microwave Imaging of 3-D Objects Using LSM and BIM Aided by a CNN U-Net

This paper presents an efficient and accurate three-dimensional (3-D) quantitative hybrid microwave imaging method. The linear sampling method (LSM) is first carried out to quickly find the approximate shapes and locations of the unknown objects in the imaging domain based on the scattered field data recorded by receivers which are placed in the far-field zone and wrap the domain. Then the full-wave inversion (FWI) is implemented in a downsized domain which tightly encloses the unknown objects instead of in the whole domain through the Born iterative method (BIM) to quantitatively retrieve the dielectric model parameters of the objects. Because the LSM fails to obtain the sufficiently accurate shapes of the unknown objects, a trained 3-D CNN U-Net is inserted between the LSM imager and the BIM solver to further refine the obtained shapes of LSM, which is expected to aid the following FWI. The proposed hybrid method is validated via the quantitative imaging of both inhomogeneous isotropic scatterers and multiple homogeneous anisotropic scatterers. It is shown that the hybrid method can achieve both higher reconstruction accuracy and lower computational cost compared with the direct BIM inversion. Meanwhile, its antinoise ability is also tested.

Application of the migration method for radiotomography of breast cancer

A new method to visualize microwave image is presented to early non-invasive detection of breast cancer tumors. A new processing method to compute microwave images of heterogeneity in a biological environment is described here, as well as a new algorithm for accelerating the calculation of three-dimensional radio images. Sounding of synthetic phantoms with dielectric properties of breast tissue was carried out in the range of 2–8 GHz using a special radar system developed by the authors. Results show that it is possible to use this microwave imaging method to form 3D accurate images using hemispherical scan Images of tumor phantoms were obtained during probing in the 2–8 GHz range with a resolution of about 5–7 mm.According to the results of the reconstruction of three-dimensional radio images, it was revealed that the calculation time can be reduced by at least 2 times with an insignificant loss of quality.

Fast 3D microwave imaging inside cavity with minimum number of antennas and modified inverse algorithm

AbstractThis article proposes an optimized method for 3D microwave imaging of various unknown objects inside a perfect electric conductor cavity. The total field scattered field technique uses the finite difference time domain method to obtain scattered fields inside a cavity in the forward scattering problem. However, the conjugate gradient method is optimized and used alongside a combined regularization term in the inverse scattering problem, which is essential for the reconstruction process. A dipole antenna is located as an incident wave from the transmitting antenna. Besides, one antenna acts as the receiver. Identifying the unknown objects with different shapes, sizes, materials, and locations using the minimum number of transmitting and receiving antennas, and the newly developed algorithm with less computation time, are the main advantages of this article. Also, the implemented method can be used in the 3D microwave imaging of multi‐scattering problems.