Adaptive beamformer orthogonal rejection test

Citation
Nb. Pulsone et Cm. Rader, Adaptive beamformer orthogonal rejection test, IEEE SIGNAL, 49(3), 2001, pp. 521-529
Citations number
14
Categorie Soggetti
Eletrical & Eletronics Engineeing
Journal title
IEEE TRANSACTIONS ON SIGNAL PROCESSING
ISSN journal
1053587X → ACNP
Volume
49
Issue
3
Year of publication
2001
Pages
521 - 529
Database
ISI
SICI code
1053-587X(200103)49:3<521:ABORT>2.0.ZU;2-F
Abstract
Research in the area of signal detection in the presence of unknown interfe rence has resulted in a number of adaptive detection algorithms. Examples o f such algorithms include the adaptive matched filter (AMF), the generalize d likelihood ratio test (GLRT), and the adaptive coherence estimator (ACE), Each of these algorithms results in a tradeoff between detection performan ce for matched signals and rejection performance for mismatch signals. This paper introduces a new detection algorithm we call the adaptive beamformer orthogonal rejection test (ABORT). Our test decides if an observation cont ains a multidimensional signal belonging to one subspace or if it contains a multidimensional signal belonging to an orthogonal subspace when unknown complex Gaussian noise is present. In our analysis, we use a statistical hy pothesis testing framework to develop a generalized likelihood ratio decisi on rule, We evaluate the performance of this decision rule in both the matc hed and mismatched signal cases. Our results show that for constant power c omplex Gaussian noise, if the signal is matched to the steering vector ABOR T, GLRT, and AMF give approximately equivalent probability of detection, hi gher than that of ACE, which trades detection probability for an extra inva riance to scale mismatch between training and test data, Of these four test s, ACE is most selective and, therefore, least tolerant of mismatch, wherea s AMF is most tolerant of mismatch and, therefore, least selective. ABORT a nd GLRT offer compromises between these extremes, with ABORT more like ACE and with GLRT more like AR IF.