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Clutter is obtained by applying physical optics to a sea surface described by a fractal model. This approach gives two interesting advantages. It is possible to control sea, radar and geometry parameters so reproducing a realistic scenario in which the clutter signal is generated. The main drawback of the clutter stochastic models which generate statistical clutter-like random sequences without directly accounting for the operating conditions in which this clutter is expected, is overcome. Secondly, the fractal nature of the sea clutter is intrinsically taken into account through the fractal characterisation of the sea surface. This aspect leads to a rigorous theoretical study on the fractal nature of the sea clutter and is also useful in new remote sensing research concerning fractal analysis of clutter for classification and detection purposes. The clutter generator was finally validated by statistical analysis of the output data. The results show a statistical behaviour comparable with that obtained from experimental data in the literature.

Decentralised detection systems with parallel decision fusion topology have received significant attention, especially for surveillance radar systems. Typically, a deterministic test (DT) is employed, and the optimal local decision strategies and the fusion rule are determined according to the Neyman–Pearson (N–P) criterion. The authors show how, in practical applications, the communication bottle-neck may significantly limit the detection performance of distributed systems employing a conventional DT. A paradigm is introduced for decentralised detection under communication constraints, based on the concept of dependent randomisation (or scheduling) of the local decision and fusion rules. Numerical results show that the proposed approach provides improved performance over decentralised detection strategies based on deterministic tests, with a moderate increase in system complexity; the improvement is particularly noticeable in spiky (non-Gaussian) clutter environments.

The problem of decentralised constant false alarm rate (CFAR) detection in a distributed multiradar system is considered. First, the way in which an incorrect assumption of the clutter model affects the false alarm rate (FAR) of state-of-the-art decentralised multiradar systems is investigated, revealing current flaws of distributed detection techniques developed under the Gaussian assumption. Results show that the FAR of current distributed architectures degrades intolerably when non-Gaussian spiky clutter is present. On the other hand, state-of-the-art biparametric CFAR algorithms for non-Gaussian clutter are computationally demanding and lossy, so the question that arises is: are they really necessary? It is shown that the answer is ‘no’, or rather, ‘not always’. A new distributed detection strategy with simple monoparametric multipulse CFAR detectors is proposed, that, in spite of the single parameter estimation, allows one to obtain a false alarm probability at the fusion centre robust against changes of the degree of clutter spikiness. The robustness is obtained by the joint action of multisensorial integration and local temporal integration, in conjunction with a specific choice of the local monoparametric estimator. After a robustness analysis of the algorithm the detection performance of the multiradar network is determined and a comparison with a decentralised system employing biparametric estimation algorithms presented.

The paper is devoted to a detailed analysis of experimental data, collected at Osborne Head Gunnery Range with McMaster University IPIX radar, to test theoretical models developed in the literature. The validity of the compound model has been proven for VV polarisation both for amplitude and correlation properties. Cross-polarised data also exhibit a compound behaviour but require an additional Gaussian component due to thermal noise. HH data deviate from the K model and seem to better approach a log-normal distribution. Previous results have been obtained by a correlation test that allows separation of the short and long correlation terms, a modified Kolmogoroff–Smirnoff test to verify the fitting and a cumulants domain analysis to quantify the Gaussian component. The interest of the work lies in its application for successful radar design.

Aim of the present study is to model the echo formation process from tissues assuming a parametric regularity of the scatterers. The tissue is modelled as a collection of ideal randomly distributed scatterers, filtered by a time-invariant system that represents the measurement apparatus, to obtain the backscattered signal. The model is derived from a stochastic approach where the scatterer distribution has been regarded as a sample function of the echo formation process. The gamma distribution has been assumed to describe the process and the interarrival time has been studied, namely the time-delay between two subsequent events “presence of a scatterer”. The results of the spectral analysis describe the parametric regularity in the scatterer position starting from the power spectral density of any single realization. The interarrival time univocally identifies the relative amplitude and the frequency band into which the spectral fluctuations correlated with tissue structure regularity fall, i.e., the presence of any spatial organization has a direct influence on such fluctuations. The model has been proposed to extend the knowledge of the mechanisms of echo formation from tissues.

This work deals with detection optimisation issues in distributed multiradar systems employing parallel decision fusion from local detectors with local discrete and continuous free-design parameters. The authors propose an efficient partial optimisation approach that avoids the exhaustive search for the optimal discrete parameters and allows a large reduction in the computational load for global system optimisation.

Expressions for the bandwidth and the output to input signal/noise ratio in quasisingle sideband f.m. are derived as a function of the modulation index and the peak input amplitude to the exponentiator, to show that q.s.s.b. f.m. provides higher demodulation gains, while requiring approximately the same bandwidth as s.s.b. f.m.

The authors introduce an adaptive suboptimum procedure for the detection of a signal of known form in the presence of a disturbance, which is assumed to be a mixture of coherent K-distributed and Gaussian distributed clutter sources with unknown distributions. A generalised likelihood ratio test is derived exploiting a simple idea: by normalising the clutter samples from each range cell with the estimated local power, the detection problem is reduced to a Gaussian problem and a simple adaptive detector is obtained.

The problem of determining the design parameters for a class of preset equalisers using transversal filters is considered. Simple and well approximated expressions for the optimum attenuation steps per tap are given to ease the design work or to initiate a computer-aided synthesis.

In a practical variable frequency crystal oscillator the difference between the operating and series resonant frequencies is always smaller than fp- fs. This limitation can be overcome by a negative capacitance realized using a NIC which does not seriously degrade overall stability.