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The present-day ocean remote sensing instruments that operate at low microwave frequencies are limited in spatial resolution and do not allow for monitoring of the coastal waters. This is due to the difficulties of employing a large reflector antenna on a satellite platform, and generating high-quality pencil beams at multiple frequencies. Recent advances in digital beamforming focal-plane arrays (FPAs) have been exploited in this paper to overcome the above problems. A holistic design procedure for such novel multibeam radiometers has been developed, where: 1) the antenna system specifications are derived directly from the requirements to oceanographic surveys for future satellite missions and 2) the numbers of FPA elements/receivers are determined through a dedicated optimum beamforming procedure minimizing the distance to coast. This approach has been applied to synthesize FPAs for two alternative radiometer systems: a conical scanner with an offset parabolic reflector and a stationary wide-scan torus reflector system, each operating at $C$ -, $X$ -, and Ku-bands. Numerical results predict excellent beam performance for both systems with as low as 0.14% total received power over the land.

Frequent and spatially distributed measurements of soil moisture (SMC), at different spatial scales, are advisable for all applications related to the environmental disciplines, such as climatology, meteorology, hydrology and agriculture. Satellite sensors operating in the low part of microwave spectrum represent an important tool for this purpose, and their signals can be directly related to the moisture content of the observed surfaces, provided that all the contributions from soil and vegetation to the measured signal are properly accounted for. Among the algorithms used for the retrieval of SMC from microwave sensors (both active, such as Synthetic Aperture Radar-SAR, and passive, radiometers), the artificial neural networks (ANN) represent the best compromise between accuracy and computation speed. ANN based algorithms have been developed at IFAC, and adapted to several radar and radiometric satellite sensors, in order to generate SMC products at a resolution varying from hundreds of meters to tens of kilometers (according to the spatial scale of each sensor ). These algorithms, which are based on the ANN techniques for inverting theoretical and semi-empirical models, such as Advanced Integral Equation (AIEM) and Oh models and on Radiative transfer Theory (RTT, in the simplified form of the 'Water-Cloud' model), have been adapted to the C- to Ka- band acquisitions from spaceborne radiometers (AMSR-E/AMSR2), SAR (Envisat/ASAR, Cosmo-SkyMed) and real aperture radar (MetOP ASCAT). Large datasets of co-located satellite acquisitions and direct SMC measurements on several test sites worldwide have been used along with simulations derived from forward electromagnetic models for setting up, training and validating these algorithms. An overall quality assessment of the obtained results in terms of accuracy and computational cost was carried out, and the main advantages and li

This paper introduces the theory of fire detection in moving vehicles by microwave radiometers. The system analysis is discussed and a feasibility study is illustrated on the basis of two implementation hypotheses. The basic idea is to have a fixed radiometer and to look inside the glass windows of the wagon when it passes in front of the instrument antenna. The proposed sensor uses a three-pixel multi-beam configuration that allows an image to be formed by the movement of the train itself. Each pixel is constituted by a direct amplification microwave receiver operating at 31.4 GHz. At this frequency, the antenna can be a 34 cm offset parabolic dish, whereas a 1 K brightness temperature resolution is achievable with an overall system noise figure of 6 dB, an observation bandwidth of 2 GHz and an integration time of 1 ms. The effect of the detector noise is also investigated and several implementation hypotheses are discussed. The presented study is important since it could be applied to the automatic fire alarm in trains and moving vehicles with dielectric wall/windows.

We have investigated the use of microwave heating and radiometry to safely heat urine inside a pediatric bladder. The medical application for this research is to create a safe and reliable method to detect vesicoureteral reflux, a pediatric disorder, where urine flow is reversed and flows from the bladder back up into the kidney. Using fat and muscle tissue models, we have performed both experimental and numerical simulations of a pediatric bladder model using planar dual concentric conductor microstrip antennas at 915 MHz for microwave heating. A planar elliptical antenna connected to a 500 MHz bandwidth microwave radiometer centered at 3.5 GHz was used for noninvasive temperature measurement inside tissue. Temperatures were measured in the phantom models at points during the experiment with implanted fiberoptic sensors, and 2-D distributions in cut planes at depth in the phantom with an infrared camera at the end of the experiment. Cycling between 20 s with 20 Watts power for heating, and 10s without power to allow for undisturbed microwave radiometry measurements, the experimental results show that the target tissue temperature inside the phantom increases fast and that the radiometer provides useful measurements of spatially averaged temperature of the illuminated volume. The presented numerical and experimental results show excellent concordance, which confirms that the proposed system for microwave heating and radiometry is applicable for safe and reliable heating of pediatric bladder. � 2011 IEEE.

This paper deals with passive microwave imaging for flre detection by means of a single-channel ground-based radiometer. The simulation of images sensed in the presence of flre spots under difierent environmental and operative conditions will be presented. We will refer to a low-cost ground-based radiometer operating at 12.65GHz. Scenarios where flres are un-visible and IR sensors are not useful with respect to a microwave imager will be investigated in deep, such as in the presence of vegetation canopy optically masking flre sources and smoke plumes in the early stage. These simulations will assess limits and capabilities of microwave imaging for the identiflcation of little flres masked by forest areas.

This paper focuses on the opportunities offered by the latest advances in silicon technologies for realizing system-on-chip microwave radiometer. Such a highly integrated, low-cost, radiometer chip could be applied to the environmental remote sensing and, in particular, to the forest fire detection. The feasibility study is carried-out in two steps. First, a proof of the concept is given by means of a discrete-component radiometer operating at 12.65 GHz. This radiometer exploits TV-SAT components such as low-noise down-converter and dish antenna. On-field measurements shows a radiometric contrast (increase of the antenna noise temperature due to the fire with respect to the background) of about 8 K for a wooden fire of 0.38 m 2 placed 30 m away from the antenna. Then, a single-chip 13 GHz radiometer has been designed exploiting a CMOS 90 nm standard process. The sensor is based on a direct-conversion architecture with integrated LNA, Gilbertpsilas cell mixer and PLL frequency synthesizer. The IF chain includes an active (gm-C) low-pass filter and a CMOS square-law detector. The circuit simulations show a total receiver gain of 72 dB, an equivalent input noise temperature of 105 K and an IF bandwidth of 100 MHz.