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Due to increasing demands for spectral resources in both communication and radar systems, the Radio Frequency (RF) electromagnetic spectrum is becoming more and more crowded with interfering nuisances. In order to tackle the scarcity of available spectral intervals, in recent years a multitude of spectrum sensing algorithms have been developed for improving spectrum sharing. Among these, two-dimensional (2-D) spectrum sensing can be used to obtain real time space-frequency electromagnetic spectrum awareness. Specifically, this approach makes it possible to optimize the spectrum usage of certain spectrum portions whose occupancy varies both temporally and spatially. In this paper, we evaluate the effectiveness of certain space-frequency map recovery algorithms relying on the use of commercially-available hardware. To this end, we employ an inexpensive four channel coherent receiver using Software Defined Radio (SDR) components for emitter localization. Hence, after proper calibration of the receiving system, the acquired samples are used to evaluate the effectiveness of different signal processing strategies which exploit the inherent block-sparsity of the overall profile. At the analysis stage, results reveal the effectiveness of such algorithms.

Radar operation in a spectrally dense environment is nowadays a very challenging problem due to the increasing demand of spectral resources for defense/surveillance applications, remote sensing capabilities, and civilian wireless services. This paper explores the technical feasibility of radar waveforms capable of ensuring spectral coexistence with overlaid radiators via a modern digital Arbitrary Waveform Generator (AWG). To this end, a specific hardware-in-the-Ioop test bed is designed to mimic the perception-action cycle necessary for the agile management of the available radio spectrum. Then the AWG synthesized waveform is measured with a Spectrum Analyzer (SA) in order to demonstrate its compliance with the spectral constraints forced by the design algorithm as well as its fidelity with the computer simulated theoretical counterpart.

This paper deals with the design of multiple-input multiple-output radar space-Time transmit code (STTC) and space-Time receive filter (STRF) to enhance moving targets detection in the presence of signal-dependent interferences. An iterative procedure, whose convergence is analytically proved, is devised to maximize the Signal to interference plus noise ratio (SINR) accounting for both a similarity constraint and a constant modulus requirement on the probing waveform. Each iteration of the algorithm involves the solution of hidden convex problems. Specifically, both a convex problem (whose solution is provided in closed form) and a set of fractional programming problems, that can be globally solved in polynomial time via the Dinkelback's procedure, are settled. The computational complexity is linear with the number of iterations and polynomial with the sizes of the STTC and the STRF. In particular, the proposed technique provides a monotonic SINR improvement without limitations on the size of the similarity constraint and ensures convergence to a stationary point filling these important gaps in the open literature. Besides, the reported results highlight that the new devised procedure outperforms both in the optimized SINR value and the computational complexity than the available counterparts.

We deal with performance prediction of the incoherent radar receiver (i.e. squared-law plus integrator) in the presence of independent non-identically distributed (non-id) Weibull target echoes. First of all, we provide the probability density function (pdf) for the sum of independent but non-id Weibull random variables in terms of an infinite sum of Gamma pdfs. Then, we develop an analytic expression for the detection probability as a fast converging series of functions. Finally, we evaluate the impacts on the detection performance of non-id Weibull target parameters. © 2014 IEEE.

The problem of coherent multi-polarization SAR change detection assuming the availability of image pairs, collected from N multiple polarimetric channels, is addressed in this paper. At the design stage, it is assumed that the reference and test images from the same polarimetric channel may exhibit a power mismatch. The change detection problem is formulated as a binary hypothesis testing problem, the principle of invariance is used to obtain the maximal invariant statistic, and the Generalized Likelihood Ratio Test (GLRT) is exploited to form a scale-invariant Constant False Alarm Rate (CFAR) decision rule. Results on real high resolution SAR data are provided that show the effectiveness of the proposed scale-invariant decision structures.