The knowledge of frequency and temperature dependent dielectric properties of tissue is essential to develop ultra-wideband diagnostic technologies, such as a non-invasive temperature monitoring system during hyperthermia treatment. To this end, we characterized the dielectric properties of animal liver, muscle, fat and blood in the microwave frequency range from 0.5 GHz to 7 GHz and in the temperature range between 30 °C and 50 °C. The measured data were modeled to a two-pole Cole-Cole model and a second-order polynomial was introduced to fit the Cole-Cole parameters as a function of temperature. The parametric model provides access to the dielectric properties of tissue at any frequency and temperature in the specified range.

The western societies are increasingly faced with the challenges of enabling a self‐determined and safe life for a growing number of elderly people. Remote monitoring of vitality is an important tool for health risk mitigation but many of the current methods either deliver only infrequent information or require conscious cooperation of the senior. The authors propose an ultra‐wideband (UWB) radio sensor network based on M‐sequence technology specifically designed for the vitality monitoring of persons living alone. It uses the frequency band in the range from 6 to 8.5 GHz (electronic communications committee (ECC)‐band), and provides precise localisation, captures breathing motion during rests, can be used for fall detection and allows the extraction of gait features. The sensor network can be installed in common living spaces. It operates continuously in the background without any user interaction. Vitality monitoring by radar sensors is based on motion detection and tracking. This poses some challenges to radar devices because of the harsh multi‐path conditions in apartments. This study discusses these challenges, illustrates how to meet them and gives examples for vitality features which can be extracted from UWB‐radar data.

Wideband microwave imaging is of interest wherever optical opaque scenarios need to be analyzed, as these waves can penetrate biological tissues, many building materials, or industrial materials. One of the challenges of microwave imaging is the computation of the image from the measurement data because of the need to solve extensive inverse scattering problems due to the sometimes complicated wave propagation. The inversion problem simplifies if only spatially limited objects—point objects, in the simplest case—with temporally variable scattering properties are of interest. Differential imaging uses this time variance by observing the scenario under test over a certain time interval. Such problems exist in medical diagnostics, in the search for surviving earthquake victims, monitoring of the vitality of persons, detection of wood pests, control of industrial processes, and much more. This paper gives an overview of imaging methods for point-like targets and discusses the impact of target variations onto the radar data. Because the target variations are very weak in many applications, a major issue of differential imaging concerns the suppression of random effects by appropriate data processing and concepts of radar hardware. The paper introduces related methods and approaches, and some applications illustrate their performance.

Magnetic nanoparticle-aided microwave imaging is recently gaining an increasing interest as potential tool for breast cancer diagnostics. This is due to the peculiar features of magnetic nanoparticles, which are biocompatible, can be selectively targeted to the tumor and may change their microwave magnetic response when modulated by a polarizing magnetic field. This latter aspect is particularly appealing, as it enables the physical separation of the microwave signal due the malignancy, targeted by the nanoparticles, from that due to healthy tissue. This increases the specificity of the diagnostic tool, in principle allowing a diagnosis based solely on the detection of the signal due to the nanoparticles response. In this respect, a proper choice of the polarizing field modulation can remarkably increase the detection performances. This paper deals with this issue, by providing the mathematical framework for such an optimization and a procedure for estimating the required quantities from a set of proper measurements. The procedure is then experimentally demonstrated by applying it to a recently developed ultra-wide band radar system for the magnetic nanoparticle-aided detection of breast cancer. For such a system, the optimal magnetic field modulation is determined.

Recently, noninvasive vital signs detection is widely used in through the wall (TTW) human detection and healthcare monitoring. In indoors and TTW environments, low signal to noise ratio make the detection of the weak vital signs difficult, and causes errors in the estimation of heartbeat, respiration rate. In this paper, different techniques are applied to the signal collected using a M-sequence ultra wideband sensor from the human subject, in order to suppress the clutter, detect the target range and estimate the heartbeat and respiration rate. First, moving average method is used to remove the stationary clutter. Next, Singular Value Decomposition (SVD) is applied to cancel the non-stationary clutter. Then, variance analysis is applied to estimate the range; when range has been detected, one dimensional Singular Spectrum Analysis (SSA) is applied to the range bin containing the subject data. It is observed that SSA completely succeeds to decompose the signal into heartbeat and respiration signal and a collection of unwanted signals as clutter, noise, and harmonics. Finally, Fast Fourier transform (FFT) is used for the estimation of the heartbeat and respiration rate. Comparison results show that the proposed algorithm outperforms a reference SVD based algorithms for heartbeat and respiration rate estimation.

We present in this paper a field-grade method for the determination of the electric permittivity of the explosives used in Improvised Explosive Devices (IED) found in Colombia. The paper presents a direct simplified method used to calculate the permittivity of dielectric materials. The efficiency of the direct method is analyzed using computer simulations of known low-loss and lossy materials. Additionally, the field deployable system and measurement setup are explained and their performance for field measurements is compared against reference measurements performed by a vector network analyzer in the frequency range from 0.3 GHz to 3 GHz. Finally, the measurements of complex permittivity of improvised explosives made of Ammonium Nitrate- Fuel Oil (ANFO) are presented.