New ECCM Techniques Against Noiselike and/or Coherent Interferers

Multiple-stage adaptive architectures are conceived to face with the problem\nof target detection buried in noise, clutter, and intentional interference.\nFirst, a scenario where the radar system is under the electronic attack of\nnoise-like interferers is considered. In this context, two sets of training\nsamples are jointly exploited to devise a novel two-step estimation procedure\nof the interference covariance matrix. Then, this estimate is plugged in the\nadaptive matched filter to mitigate the deleterious effects of the noise-like\njammers on radar sensitivity. Besides, a second scenario, which also includes\nthe presence of coherent jammers, is addressed. Specifically, the sparse nature\nof data is brought to light and the compressive sensing paradigm is applied to\nestimate target response and coherent jammers amplitudes. The likelihood ratio\ntest, where the unknown parameters are replaced by previous estimates, is\ndesigned and assessed. Remarkably, the sparse approach allows for echo\nclassification and estimation of both angles of arrival and number of the\ninterfering sources. The performance analysis, conducted resorting to simulated\ndata, highlights the effectiveness of the newly proposed architectures also in\ncomparison with suitable competing architectures (when they exist).\n