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008			220601s2009 sz | s |||| 0|eng d
020			_a9783031025327
024	7		_a10.1007/978-3-031-02532-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK6580 _b2009 EB
100	1		_aBandiera, Francesco _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687636
245	1	0	_aAdvanced Radar Detection Schemes Under Mismatched Signal Models _cby Francesco Bandiera, Danilo Orlando, Giuseppe Ricci
250			_a1st edition 2009
264		1	_aCham _bSpringer International Publishing _c2009
300			_a1 recurso en línea (IX, 95 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Signal Processing _x1932-1694
505	0		_aIntroduction -- Adaptive Radar Detection of Targets -- Adaptive Detection Schemes for Mismatched Signals -- Enhanced Adaptive Sidelobe Blanking Algorithms -- Conclusions.
520			_aAdaptive detection of signals embedded in correlated Gaussian noise has been an active field of research in the last decades. This topic is important in many areas of signal processing such as, just to give some examples, radar, sonar, communications, and hyperspectral imaging. Most of the existing adaptive algorithms have been designed following the lead of the derivation of Kelly's detector which assumes perfect knowledge of the target steering vector. However, in realistic scenarios, mismatches are likely to occur due to both environmental and instrumental factors. When a mismatched signal is present in the data under test, conventional algorithms may suffer severe performance degradation. The presence of strong interferers in the cell under test makes the detection task even more challenging. An effective way to cope with this scenario relies on the use of "tunable" detectors, i.e., detectors capable of changing their directivity through the tuning of proper parameters. The aim of this book is to present some recent advances in the design of tunable detectors and the focus is on the so-called two-stage detectors, i.e., adaptive algorithms obtained cascading two detectors with opposite behaviors. We derive exact closed-form expressions for the resulting probability of false alarm and the probability of detection for both matched and mismatched signals embedded in homogeneous Gaussian noise. It turns out that such solutions guarantee a wide operational range in terms of tunability while retaining, at the same time, an overall performance in presence of matched signals commensurate with Kelly's detector. Table of Contents: Introduction / Adaptive Radar Detection of Targets / Adaptive Detection Schemes for Mismatched Signals / Enhanced Adaptive Sidelobe Blanking Algorithms / Conclusions.
988			_aSynthesis Collection of Technology_2009
650		7	_2embne _9139959 _aRadar
650		7	_2embne _9669508 _aProceso adaptativo de señales
700	1		_aOrlando, Danilo _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686071
700	1		_aRicci, Giuseppe _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687637
776	0	8	_iPrinted edition: _z9783031014048
776	0	8	_iPrinted edition: _z9783031036606
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02532-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI