Two types of optoelectronic oscillators delivering high spectral purity microwave signals are presented in this paper. These oscillators use the Pound–Drever–Hall laser stabilization technique to lock the laser carrier onto two different types of passive optical resonators featuring high-quality factors: a fiber ring resonator (FRR) and a whispering gallery mode monocrystalline disk-shaped micro-resonator. The different noise processes occurring inside these oscillators are discussed. Particular attention is given to the conversion of the laser's amplitude and frequency noise into RF phase noise via the laser stabilization loop and the resonator, and via the photodetector nonlinearity as well. A modeling approach using CAD software is also proposed to qualitatively evaluate laser noise conversion through the optical resonator. Moreover, different contributions of nonlinear optical scattering noise are discussed, mainly in the case of the FRR-based oscillator. When controlling these nonlinear optical effects in the case of the FRR, low-phase noise operation of the oscillator has been achieved, with a −40 dBc/Hz noise level at 10 Hz offset frequency from a 10.2 GHz RF carrier.

A fast imaging algorithm for real-time use in short-range (ultra-wideband) radar with synthetic or real-array aperture is proposed. The reflected field is presented here as a convolution of the target reflectivity and point spread function (PSF) of the imaging system. To obtain a focused 3D image, the proposed algorithm deconvolves the PSF out from the acquired data volume with high speed due to fast Fourier transform and implementation in frequency-wavenumber domain. Then the result is tested against two numerical criteria for efficiency, namely error and instability, whose optimal values can be obtained iteratively. Since the PSF differs with distance, the algorithm suits mainly applications with relatively small objects such as concealed weapon detection. Using several PSFs allows us to image a certain range of interest by their successive deconvolution from the same data. Performance of the algorithm has been evaluated experimentally and compared with that of Kirchhoff migration. Measurements were carried out by a 5–25 GHz synthetic aperture radar in the lab, and scenarios included a gun and a ceramic knife in free space, on a large metal plate, and a gun concealed on a dummy under a thick raincoat. The results demonstrate sufficient image quality obtained in a fraction of time.

In this article, a novel motion model-based particle filter implementation is proposed to classify human motion and to estimate key state variables, such as motion type, i.e. running or walking, and the subject's height. Micro-Doppler spectrum is used as the observable information. The system and measurement models of human movements are built using three parameters (relative torso velocity, height of the body, and gait phase). The algorithm developed has been verified on simulated and experimental data.

The paper describes a radar demonstrator that was used to collect L-band range profiles of illuminated ground surface. The measurement results are to be used by the Institute of Geodesy and Cartography as the reference data for satellite image interpretation. The demonstrator is a software-defined noise radar composed of commercial-off-the-shelf elements. The paper conveys the theory of scattering coefficient measurement, system setup, and signal processing as well as the preliminary results of the field measurement campaigns.

In this paper, we present the results of using a frequency-stepped continuous-wave radar system to estimate the position of overlapping and electrically good conductive plates. We especially focus on polarimetric scattering effects caused by the step of a lap joint, which is a common welding-geometry. To model the step's contribution to the overall scattered signal, we use a two-dimensional combined field integral equation (CFIE) approach. For demonstrating its practical applicability, the implemented scattering model is verified by measurements. To emphasize the improvements of position estimation by using a CFIE approach, the outcomes of the model are compared to a commonly used point scattering model. Finally, the numerical signal is utilized to precisely estimate the position of the lap joint.

This paper presents the design of a multi-channel reconfigurable front-end architecture for a waveform-agile radar. At first the purpose of the design is explained following the status of research on software-defined radar at MTSR. A description of the proposed system architecture is given with details on sub-systems implementation. Then some preliminary results obtained on a prototype of the platform are shown. Finally, further developments on this system architecture are described, highlighting how this platform can support research on software-defined multi-channel radar systems.

Phase unwrapping (PU) is one of the key processing steps in reconstructing the digital elevation model (DEM) of a scene from interferometric synthetic aperture radar (InSAR) data. The PU problem entails the estimation of an absolute phase from observation of its noisy principal (wrapped) values. Recently, PU approaches based on Kalman filtering have proved their efficacy in tackling the PU problem even when strong discontinuities of the height profile and noisy data are involved. This paper presents a novel multichannel InSAR PU algorithm using several interferometric SAR images based on the extended Kalman filter. The proposed technique exploits the capability of the Kalman algorithm to simultaneously perform noise filtering, PU, and multi-sensor data fusion. The proposed method, even being a Bayesian estimator, optimally fuses height information coming from an additional maximum likelihood estimator (MLE) combining the benefits of both the Bayesian and the non-Bayesian approaches. The performance of the proposed algorithm has been tested on simulated interferometric images proving the effectiveness of the proposed method.