1,725,309 research outputs found
Multivariate Polarimetric Bistatic Clutter Statistical Analysis
No full textThis paper deals with the analysis of simultaneously collected co- and cross-polarized bistatic sea-clutter returns with special emphasis on their representation as a Spherically Invari-ant Random Process (SIRP). The study is conducted by using appropriate testing procedures involving the complex envelope of the measured data that provide both first- and higher-order compatibility conditions. The results highlight that the SIRP model is a good candidate for the representation of bistatic coherent clutter, and usually the coherence time of the SIRP texture is longer than that in the monostatic case.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Microwave Sensing, Signals & System
Feature article: A survey on two-stage decision schemes for point-like targets in Gaussian interference
No full textIn recent years, the design of so-called tunable detectors has raised significant interest in the radar community. The class of tunable detectors has been shown to be an effective means to attack detection of mainlobe targets or rejection of coherent repeater interferers in the presence of clutter and/or possible noise-like in-terferers. Tunable detectors allow adjustment of the rate at which the probability of detection Pd decreases as the received signal departs from the nominal one. In this case, a mismatch between the nominal and the actual steering vector is present. We refer to the capability of rejecting or detecting signals as directivity. Existing architectures can be classified according to their directivity as follows [1]: ▸ Robust decision schemes provide good detection performance in the presence of echoes containing signal components not aligned with the nominal (transmitted) signal (as shown in Figure 1, where target returns lie on a direction that is not aligned with the antenna beam boresight). ▸ Selective decision schemes are capable of rejecting signals whose signature is unlikely to correspond to the signal of interest to avoid false alarm
A Clustering Approach for Jamming Environment Classification
No full textA hierarchical clustering architecture is proposed to deal with the problem of jamming environment classification when multiple noise-like jammers are possibly present. Assuming the availability of clutter-free multichannel data, a two-level hierarchical procedure is devised to unveil the presence of clusters containing range cells experiencing the same jamming interference as the cell under test. Level 1 relies on the use of covariance smoothing and model-order selection rules to make inference on the number of jamming signals affecting each range bin within the radar range swath. Level 2 allows to discriminate among possible different interfering scenarios characterized by the same number of jammers via an unsupervised learning clustering fed by a suitable feature set. At the analysis stage, the performance of the devised architecture is investigated over simulated and measured data (via software-defined radio devices) to highlight the benefits of the approach
A Robust Framework for Covariance Classification in Heterogeneous Polarimetric SAR Images and Its Application to L-Band Data
No full textIn this paper, an automatic classification approach for polarimetric covariance structure is derived and assessed. It extends the framework of Pallotta et al. "Detecting Covariance Symmetries in Polarimetric SAR Images" to the heterogeneous environment, where the pixels of the polarimetric image share the same covariance structure but different power levels. The Principle of Invariance is exploited to replace the original data with a suitable statistic whose distribution is independent of the scale factors. Then, the classification problem is formulated in terms of a multiple hypotheses test and solved by means of model order selection rules. The behavior of the newly devised classifiers is first assessed over simulated data also in comparison with the analogous counterparts for a homogeneous environment. Next, the classification performances are evaluated on real measured data corroborating the satisfactory results highlighted in the simulations
Adaptive Radar Detectors Based on the Observed FIM
No full textModified versions of Rao, Wald, and Durbin tests are considered exploiting an estimator of the Fisher Information Matrix (FIM) in place of the exact one. They are asymptotically equivalent (under some technical conditions) to the standard counterparts and rely on the use of the Observed FIM (OFIM), which is proportional to the negative Hessian of the log-likelihood. The developed framework is applied to the problem of adaptive radar detection of a point-like target in homogeneous or partially-homogeneous interference. Remarkably, for both the scenarios, it is shown that Rao, Wald, and Durbin tests with OFIM are statistically equivalent to the Generalized Likelihood Ratio Test (GLRT) for the specific detection problem (namely Kelly's detector for the homogeneous environment and the Adaptive Coherence Estimator (ACE) [S. Kraut and L. L. Scharf, "The CFAR adaptive subspace detector is a scale-invariant GLRT," IEEE Trans. Signal Process., vol. 47, no. 9, pp. 2538-2541, Sep. 1999.], also known as Adaptive Normalized Matched Filter (ANMF) [E. Conte, M. Lops, and G. Ricci, "Asymptotically optimum radar detection in compound-gaussian clutter," IEEE Trans. Aerosp. Electron. Syst., vol. 31, no. 2, pp. 617-625, Apr. 19951, for the partially-homogeneous scenario). This provides a new interpretation of the mentioned GLRTs laying the foundations for a better understanding of their theoretical validity
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