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Microwave imaging
Microwave imaging
Microwave imaging
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Microwave imaging is a science which has been evolved from older detecting/locating techniques (e.g., radar) in order to evaluate hidden or embedded objects in a structure (or media) using electromagnetic (EM) waves in microwave regime (i.e., ~300 MHz-300 GHz).[1] Engineering and application oriented microwave imaging for non-destructive testing is called microwave testing, see below.

Microwave imaging techniques can be classified as either quantitative or qualitative. Quantitative imaging techniques (are also known as inverse scattering methods) give the electrical (i.e., electrical and magnetic property distribution) and geometrical parameters (i.e., shape, size and location) of an imaged object by solving a nonlinear inverse problem. The nonlinear inverse problem is converted into a linear inverse problem (i.e., Ax=b where A and b are known and x (or image) is unknown) by using Born or distorted Born approximations. Despite the fact that direct matrix inversion methods can be invoked to solve the inversion problem, this will be so costly when the size of the problem is so big (i.e., when A is a very dense and big matrix). To overcome this problem, direct inversion is replaced with iterative solvers. Techniques in this class are called forward iterative methods which are usually time consuming. On the other hand, qualitative microwave imaging methods calculate a qualitative profile (which is called as reflectivity function or qualitative image) to represent the hidden object. These techniques use approximations to simplify the imaging problem and then they use back-propagation (also called time reversal, phase compensation, or back-migration) to reconstruct the unknown image profile. Synthetic aperture radar (SAR), ground-penetrating radar (GPR), and frequency-wave number migration algorithm are some of the most popular qualitative microwave imaging methods[1].

Principles

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In general, a microwave imaging system is made up of hardware and software components. The hardware collects data from the sample under test. A transmitting antenna sends EM waves towards the sample under test (e.g., human body for medical imaging). If the sample is made of only homogeneous material and is of infinite size, theoretically no EM wave will be reflected. Introduction of any anomaly which has different properties (i.e., electrical/magnetic) in comparison with the surrounding homogeneous medium may reflect a portion of the EM wave. The bigger the difference between the properties of the anomaly and the surrounding medium is, the stronger the reflected wave will be. This reflection is collected by the same antenna in a monostatic system, or a different receiver antenna in bistatic configurations.

A general view of a microwave imaging system. (http://hdl.handle.net/10355/41515)

To increase the cross-range resolution of the imaging system, several antennas should be distributed over an area (which is called the sampling area) with a spacing less than the operating wavelength. However, the mutual coupling between the antennas, which are placed close to each other, may degrade the accuracy of the collected signals. Moreover, the transmitter and receiver system will become very complex. To address these problems, one single scanning antenna is used instead of several antennas. In this configuration, the antenna scans over the entire sampling area, and the collected data is mapped together with their antenna position coordinates. In fact, a synthetic (virtual) aperture is produced by moving the antenna (similar to the synthetic aperture radar principle[2]). Later, the collected data, which is sometimes referred to as raw data, is fed into the software for processing. Depending on the applied processing algorithm, microwave imaging techniques can be categorized as quantitative and qualitative.

Applications

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Microwave imaging has been used in a variety of applications such as: nondestructive testing and evaluation (NDT&E, see below), medical imaging, concealed weapon detection at security check points, structural health monitoring, and through-the-wall imaging.

Microwave imaging for medical applications is also becoming of more interest. The dielectric properties of malignant tissue change significantly in comparison with the properties of normal tissue (e.g., breast tissue). This difference translates into a contrast which can be detected by microwave imaging methods. As one example, there are several research groups all around the world working on developing efficient microwave imaging techniques for early detection of breast cancer.[3]

3D image of rebars with corrosion produced using microwave imaging, http://hdl.handle.net/10355/41515

Ageing of infrastructure is becoming a serious problem worldwide. For example, in reinforced concrete structures, corrosion of their steel reinforcements is the main cause of their deterioration. In U.S. alone, repair and maintenance cost due to such corrosion is about $276 billion per year,[4] [3].

Recently, microwave imaging has shown great potential to be used for structural health monitoring. Lower frequency microwaves (e.g., <10 GHz) can easily penetrate through concrete and reach objects of interest such as reinforcement bars (rebars). If there is any rust on the rebar, since rust reflects less EM waves in comparison with sound metal, the microwave imaging method can distinguish between rebars with and without rust (or corrosion).[citation needed] Microwave imaging also can be used to detect any embedded anomaly inside concrete (e.g., crack or air void).

These applications of microwave imaging are part of non-destructive (NDT) testing in civil engineering. More on microwave imaging in NDT is described in the following.

Microwave testing

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Microwave testing uses the scientific basics of microwave imaging for the inspection of technical parts with harmless microwaves. Microwave testing is one of the methods of non-destructive testing (NDT). It is restricted to tests of dielectric, i. e. non-conducting material. This includes glass-fibre reinforced plastic (GRP, GFRP).[5] Microwave testing can be used to inspect components also in a built-in state, e. g. built-in non-visible gaskets in plastic valves.

B-scan of a foam-GFRP sandwich at 100 GHz. The indication at x = 120 mm results from moisture in the foam at a depth of about 20 mm below the DUT surface. (Becker, Keil, Becker Photonik GmbH: Jahrestagung DGZfP 2017, Beitrag Mi3C2)

Principle

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GFRP pipe wall. C-scan. In the middle: indication of a defect in 60 mm depth, 24 GHz

The microwave frequencies extend from 300 MHz to 300 GHz corresponding to wavelengths between 1 m and 1 mm. The section from 30 GHz to 300 GHz with wavelengths between 10 mm and 1 mm is also called millimeter waves. Microwaves are in the order of the size of the components to be tested. In different dielectric media they propagate differently fast and at surfaces between them they are reflected. Another part propagates beyond the surface. The larger the difference in the wave impedance, the larger is the reflected part.

In order to find material defects, a test probe, attached or in a small distance, is moved over the surface of the device under test. This can be done manually or automatically.[6] The test probe transmits and receives microwaves.

Changes of the dielectric properties at surfaces (e. g. shrinkage cavities, pores, foreign material inclusion, or cracks) within the interior of the device under test reflect the incident microwave and send a part of it back to the test probe, which acts as a transmitter and as a receiver.[7][8]

The electronic data evaluation leads to a display of the results, e. g. as a B-scan (cross sectional view) or as a C-scan (top view). These display methods are adopted from ultrasonic testing.

NIDIT through transmission image of a rotor blade trailing edge with artificially distributed adhesive

Procedures

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Besides the reflection method also the through transmission method is possible, in which separate transmit and receive antennas are used. The backside of the device under test (DUT) must be accessible and the method gives no information about the depth of a defect within the DUT.

Microwave tests are possible with constant frequency (CW) or with continuously tuned frequency (FMCW). FMCW is advantageous to determine the depth of defects within the DUT.

A test probe attached to the DUT's surface gives information about the material distribution below the point of contact. When moving over the DUT surface point by point many such information is stored and then evaluated to give an overall image. This takes time. Directly imaging procedures are faster: Microwave versions are either electronic[9] or make use of planar microwave detector consisting of a microwave absorbing foil and an infrared camera (NIDIT procedure[10]).

Gauge FSC fort the non-destructive measurement of paint thickness on CFRP, here on an aerobatic aircraft

Applications

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Microwave testing is a useful NDT method for dielectric materials. Among them are plastics, glass-fiber reinforced plastics (GFRP), plastic foams, wood, wood-plastic composites (WPC), and most types of ceramics. Defects interior in the DUT and at its surface can be detected, e. g. in semi-finished products or pipes.

Special applications of microwave testing are non-destructive

  • moisture measurements
  • wall thickness measurements
  • measurements of paint thickness on carbon composites (CFRP)
  • condition monitoring, e. g. presence of gaskets in assembled valves, rubber based piping in heat exchangers[11]
  • measurement of material parameters, e.g. permittivity and residual stress
  • disbond detection in strengthened concrete bridge members retrofitted with carbon fiber reinforced (CFRP) composite laminates[12]
  • corrosion and precursor pitting detection in painted aluminum and steel substrates[12]
  • flaw detection in spray-on foam insulation and the acreage heat tiles of the Space Shuttle.[12]

Microwave testing is used in many industrial sectors:

  • aerospace, e. g. non-destructive paint thickness measurements on CFRP[13]
  • automobile, e. g. NDT of organo sheet components and of GFRP leaf springs[14]
  • civil engineering, e. g. radar applications[15]
  • energy supply, e. g. test of rotor blades of wind power plants, riser pipe[16]
  • security, e. g. body scanner on airports[9]

In the last years the need for NDT has increased generally and especially also for dielectric materials. For this reason and because microwave technics more and more are used in consumer products and hereby became much less expensive, NDT with microwaves increases. In recognizing this growing importance, in 2011 the Expert committee for microwave and THz procedures[17] of the German Society of Non-Destructive Testing (DGZfP) was founded as in 2014 the Microwave Testing Committee of the American Society for Non-Destructive Testing (ASNT). Standardization work is at the beginning.

References

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Microwave imaging

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Microwave imaging is a non-invasive electromagnetic technique that employs radio waves in the microwave frequency band, typically ranging from 300 MHz to 30 GHz, to visualize the internal structures, properties, or anomalies within objects by measuring , reflected, or transmitted signals and reconstructing images through the solution of inverse problems. This method exploits contrasts in the and conductivity of materials relative to the , enabling penetration into non-conductive media such as biological tissues, composites, or without the use of , which distinguishes it from techniques like X-ray imaging. The core principles of microwave imaging involve transmitting low-power microwave signals via antennas—either in near-field (close proximity for high resolution) or far-field (distant for broader coverage) configurations—and capturing the interactions with the material under test (MUT), such as backscattering or patterns. often relies on algorithms like (SAR) for backprojection or nonlinear for detailed mapping, with resolution influenced by frequency, (1 m to 1 cm), and scanning geometry—achieving sub-millimeter detail at higher frequencies like millimeter waves. Unlike conductive materials where penetration is limited by skin depth, microwave imaging excels in and semi-conductive substances, making it suitable for real-time, cost-effective applications. Key applications span multiple fields, including medical diagnostics, where it supports detection, monitoring, and brain imaging by highlighting dielectric contrasts in tissues; non-destructive testing and evaluation (NDT&E) in and for identifying voids, cracks, or delaminations in composites and structures; and security and material characterization, such as concealed detection or assessment in foods and building materials. Recent advancements integrate , particularly machine and models like convolutional neural networks (CNNs), to enhance image reconstruction accuracy, reduce computational demands, and enable portable systems for clinical and industrial use. Despite challenges like limited in complex media and ill-posed inverse problems, ongoing research continues to expand its clinical validation and hybrid integrations with modalities like .

Fundamentals

Definition and Overview

Microwave imaging is a non-ionizing technique that employs electromagnetic waves in the frequency range of 300 MHz to 30 GHz to detect, locate, and characterize hidden or embedded objects within various media. It operates by analyzing the interactions of these waves with the target, including reflection, transmission, and , to reconstruct images based on differences in electromagnetic properties such as and conductivity. This approach enables the mapping of internal structures without physical contact, leveraging the sensitivity of microwaves to material contrasts. The technique originated from radar technology developed during in the 1940s, where microwave frequencies were harnessed for remote detection and ranging of objects. By the 1970s, microwave imaging evolved toward biomedical applications, with initial experiments exploring its potential for early detection through dielectric property variations in tissues. A significant milestone occurred in the 1980s with the advent of the first microwave tomography systems, which introduced quantitative reconstruction methods and broadened its utility beyond qualitative detection. In scope, microwave imaging distinguishes itself from modalities like , which uses with associated health risks, and , which depends on mechanical waves susceptible to attenuation in heterogeneous media. Its key advantages include deep penetration into lossy materials like biological tissues and high contrast sensitivity to dielectric differences, enabling safe, portable, and cost-effective imaging without the need for compression or contrast agents.

Physical Principles

Microwaves are transverse electromagnetic waves characterized by wavelengths ranging from 1 mm to 1 m, corresponding to frequencies between 300 MHz and 300 GHz. These waves propagate at the in vacuum and interact with materials through their electric and components, enabling imaging by detecting perturbations in the wave fields. A key property is the frequency dependence of penetration and resolution: higher frequencies (e.g., around 30 GHz) provide submillimeter but limit penetration to depths of about 1 mm or less in biological tissues, while lower frequencies (e.g., 915 MHz to 2.45 GHz) allow deeper penetration of 2–4 cm at the cost of coarser resolution. Microwave interactions with materials occur primarily through reflection at interfaces caused by impedance mismatches between media, where the depends on the ratio of intrinsic impedances. Transmission into dielectrics involves partial wave with due to material losses, while arises from inhomogeneities that perturb the incident field. Absorption is governed by the material's conductivity and , converting electromagnetic energy into heat and reducing signal amplitude. The response of materials is described by the complex ϵ=ϵ′−jϵ′′\epsilon = \epsilon' - j\epsilon'', where ϵ′\epsilon' represents the real part related to and polarization, and ϵ′′\epsilon'' the imaginary part associated with . In biological tissues, water-rich structures such as muscle or exhibit high real values of ϵ′≈50\epsilon' \approx 50--70 at frequencies around 1--3 GHz, providing strong contrast for imaging anomalies like tumors. In contrast, industrial materials like composites often feature low-loss characteristics with ϵ′≈2\epsilon' \approx 2--10 and minimal ϵ′′\epsilon'', enabling applications in non-destructive testing of low-attenuation structures. Image formation in microwave imaging relies on reconstructing the spatial distribution of dielectric properties from measured scattered fields via inverse scattering theory, which solves for the object's permittivity from boundary data. For weakly objects, the simplifies this by linearly relating the scattered field to the contrast: Esc≈G⋅(ϵr−1)⋅Einc\mathbf{E}_{sc} \approx \mathbf{G} \cdot (\epsilon_r - 1) \cdot \mathbf{E}_{inc}, where G\mathbf{G} is the , ϵr\epsilon_r the , and Einc\mathbf{E}_{inc} the incident field. This approximation facilitates initial reconstructions but assumes low contrast and neglects multiple effects.

Imaging Techniques

Active Techniques

Active microwave imaging encompasses systems that actively illuminate a target with signals and analyze the backscattered or transmitted electromagnetic fields to reconstruct images of the target's properties or structure. These techniques exploit the contrast in and conductivity between the target and its surroundings to generate two-dimensional or three-dimensional maps, typically through raster scanning of probes or the use of antenna arrays. Radar-based methods form a core subset of active microwave imaging. Ground-penetrating radar (GPR) transmits short microwave pulses into subsurface media, such as soil or concrete, and processes the reflected signals to detect buried objects or interfaces, enabling non-destructive evaluation of hidden features. (SAR), on the other hand, utilizes the motion of a platform or scanned antenna to simulate a large , achieving high-resolution imaging via phase-coherent . In SAR, the cross-range resolution is approximated by δ ≈ λ / (2 sin θ), where λ denotes the microwave wavelength and θ represents the aspect angle subtended by the synthetic aperture. Tomographic approaches in active microwave imaging, such as microwave tomography (MWT), rely on multi-view or multi-frequency measurements from surrounding antennas to solve the electromagnetic inverse problem. A widely adopted for permittivity reconstruction is the distorted Born iterative method (DBIM), which iteratively refines an initial estimate by incorporating the nonlinear effects of multiple through successive linear approximations of the field propagation. Distinctions between near-field and far-field configurations are critical for optimizing resolution and application range. Near-field operates at distances comparable to the , often with probes positioned at approximately λ/2π to capture evanescent waves, enabling sub- resolution for high-precision, contact-based inspections. In contrast, far-field techniques, where the target lies beyond several , support standoff with resolution limited primarily by the and beamwidth, suitable for broader scenarios. Hardware for active microwave imaging typically includes specialized antennas like horn feeds or phased arrays for efficient and reception, integrated with transceivers that handle amplification, modulation, and down-conversion. occurs in either time-domain mode using pulsed excitations for direct ranging or frequency-domain mode with continuous-wave (CW) sweeps for precise phase and amplitude measurements, often facilitated by vector network analyzers.

Passive Techniques

Passive microwave imaging techniques detect and map thermal emissions or ambient microwave radiation naturally present in the scene, without employing an active signal source. These methods operate on the principles of , leveraging the fact that all objects above emit microwave radiation proportional to their physical , as governed by where equals absorptivity. A core approach in passive microwave imaging is microwave radiometry, which quantifies the TbT_b, defined as the temperature a blackbody would need to exhibit the observed radiance at microwave frequencies under the Rayleigh-Jeans approximation. The is derived from the solution to the equation, approximated for a non-scattering medium along the as Tb=∫0∞T(τ)e−τ dτT_b = \int_0^\infty T(\tau) e^{-\tau} \, d\tau, where T(τ)T(\tau) is the physical at optical depth τ\tau, and τ\tau represents the cumulative absorption along the path. This integral accounts for the attenuation of emissions from deeper layers due to absorption, enabling mapping in semi-transparent media such as the atmosphere or biological tissues. Interferometric techniques enhance passive imaging by employing to achieve higher than single-antenna systems, particularly in applications. These methods correlate signals received by multiple antennas separated by baselines, exploiting the van Cittert-Zernike theorem to sample the visibility function in the Fourier domain of the distribution. For instance, the correlation of from antenna pairs allows reconstruction of images through inverse , as demonstrated in systems like the Soil Moisture and Ocean Salinity (SMOS) mission's MIRAS instrument with 69 receivers arranged in a Y-shaped . In detection scenarios, passive radar utilizes ambient transmitters such as television broadcasts as opportunistic illuminators, capturing reflections from targets to form images without a dedicated source, though this results in lower signal-to-noise ratios compared to controlled illumination due to unpredictable signal characteristics and interference. Key system components include radiometers for signal detection and . Total power radiometers directly measure incoming power but are susceptible to gain variations; Dicke-type radiometers mitigate this by rapidly switching between the antenna signal and a stable reference load, effectively modulating the input to reduce fluctuation noise while preserving sensitivity. Antenna arrays provide by spatially sampling the field, with element spacing determining the synthesized size and thus the achievable resolution, often on the order of the divided by the maximum baseline.

Applications

Biomedical Applications

Microwave imaging leverages the dielectric contrast between healthy and malignant tissues, primarily due to the higher in tumors, which results in elevated (ε') and conductivity values. In tissues, for instance, malignant regions exhibit mean ε' values around 49 at 5 GHz, compared to approximately 5-6 in adipose-dominated normal tissue, providing up to a 10:1 that enables tumor differentiation at frequencies of 1-10 GHz. This contrast arises from physiological differences, such as increased and cellular density in cancerous areas, making microwave imaging suitable for non-invasive detection without . In detection, microwave imaging (MIS) and systems exploit this mismatch to identify early-stage tumors. Pioneering work includes the clinical prototype developed in the 2000s, featuring a 16-element array operating at 300-1000 MHz, which achieves spatial resolutions of 5-10 mm in phantom and patient studies. These systems immerse the breast in a coupling medium to facilitate signal transmission, reconstructing 2D or 3D images via algorithms like the distorted Born iterative method, particularly beneficial for dense breasts, where traditional faces challenges, by avoiding tissue compression. Recent integrations with , such as for reconstruction, enhance accuracy by addressing ill-posed inverse problems, with pilot studies demonstrating improved tumor localization. Beyond , microwave techniques detect strokes by capitalizing on the high contrast of hemorrhagic (ε' ≈ 60-70 at 1 GHz) against surrounding tissue (ε' ≈ 40-50), enabling portable devices for pre-hospital identification with resolutions down to 5 mm in realistic head phantoms. In cardiovascular applications, the method differentiates and muscle layers based on their differences ( ε' ≈ 5-10, muscle ≈ 50-60 at 1-3 GHz), supporting dynamic monitoring of arterial waves and cardiac activity via systems, though static anatomical imaging remains challenging due to clutter. For , microwave imaging provides real-time, non-invasive mapping by tracking changes with ( sensitivity ≈ -0.5-1% per °C), guiding treatment for tumors like those in or with 3D differential imaging at rates exceeding 10 frames per second. Clinically, microwave imaging devices for remain in research and investigational phases as of 2025, with FDA-cleared systems limited to trial use under investigational device exemptions, such as prototypes evaluated in multi-site studies involving hundreds of patients. As of 2025, systems like MammoWave are undergoing large-scale multicentric clinical trials, such as NCT06291896, to further validate their efficacy in screening. Advantages include lower costs compared to MRI and patient comfort from no compression or , positioning it as a complementary tool to , especially for high-risk screening. Safety profiles are favorable, as microwaves are non-ionizing with power levels typically below 1 , resulting in specific absorption rates (SAR) well under the 1.6 /kg limit set by regulatory bodies like the FCC and ICNIRP, ensuring negligible tissue heating during imaging sessions lasting 5-10 minutes.

Industrial and Non-Destructive Testing

Microwave plays a crucial role in non-destructive evaluation (NDE) of industrial materials, enabling the detection of internal defects such as voids and delaminations in composites without causing damage to the structure. These defects alter the dielectric properties of the material, leading to measurable changes in microwave . Specifically, wave occurs due to absorption and by inhomogeneities, while phase shift arises from variations in the propagation velocity caused by differences in . Scattering from these inhomogeneities provides contrast for , allowing localization of flaws based on reflected or transmitted signals. Typical procedures involve scanning the material surface with waveguides or antennas to transmit and receive microwave signals, often in the 1-20 GHz range for optimal penetration and resolution. In time-domain reflectometry approaches, the time-of-flight (TOF) of reflected signals determines defect depth using the formula d=v⋅Δt2d = \frac{v \cdot \Delta t}{2}, where dd is the depth, vv is the microwave speed in the material (adjusted for its permittivity), and Δt\Delta t is the time delay relative to the reference signal. For surface and near-surface imaging, near-field probes, such as open-ended coaxial lines, provide high spatial resolution by focusing fields close to the probe tip, detecting subtle changes in reflection coefficients. Integration with robotic systems facilitates automated scanning of large-scale structures, improving efficiency and repeatability in inspections. Standards such as ASTM D7449 guide the measurement of complex permittivity during these evaluations, ensuring consistent characterization of material properties. In aerospace applications, microwave imaging detects cracks and delaminations in composite materials like carbon fiber reinforced polymers, critical for ensuring structural integrity in components. For instance, reflectometry techniques have identified voids in layered composites with depths up to several centimeters. In civil engineering, it assesses corrosion by monitoring changes in dielectric contrast around embedded , where microwave signals penetrate cover layers to reveal rust-induced voids or thickness loss. The food industry employs microwave NDT to measure content in grains non-invasively, using attenuation variations to quantify water distribution and prevent spoilage during storage. Key advantages of microwave imaging over methods like include its non-ionizing nature, eliminating radiation safety concerns, and deep penetration through non-conductive materials—up to 1 m in low-loss dielectrics such as polymers or dry —while maintaining sensitivity to and variations. This makes it particularly suitable for in-situ inspections where portability and speed are essential.

Challenges and Future Directions

Limitations and Challenges

One major limitation of microwave imaging is its resolution, constrained by the diffraction limit, which is approximately half the (λ/2) of the operating . At typical GHz frequencies (e.g., 1–10 GHz), wavelengths range from 30 cm to 3 cm in free space, resulting in cm-scale that is inferior to optical imaging (sub-micron scale) but superior to low-frequency systems (meter-scale). A fundamental exists between and resolution in microwave imaging, particularly in lossy media like biological tissues, where higher provide better resolution but attenuate more rapidly due to increased absorption. This is quantified by the skin depth, given by the formula δ=1πfμσ,\delta = \frac{1}{\sqrt{\pi f \mu \sigma}},
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