Adaptive Beamformer Orthogonal Rejection Test (ABORT)

Nicholas B. Pulsone and Charles M. Rader
MIT Lincoln Laboratory
Lexington, MA

Abstract Research in the area of signal detection in the presence of unknown interference has resulted in a number of adaptive detection algorithms. Examples of such algorithms include the Adaptive Matched Filter (AMF), the Generalized Likelihood Ratio Test (GLRT), and the Adaptive Coherence Estimator (ACE). Each of these algorithms results in a tradeoff between detection performance for matched signals and rejection performance for mismatch signals. For example, AMF has better matched signal detection characteristics than ACE, but ACE has better mismatched signal rejection capabilities. This paper introduces a new detection algorithm which we call Adaptive Beamformer Orthogonal Rejection Test (ABORT). Our test decides if an observation contains 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 hypothesis framework to develop a generalized likelihood ratio decision rule. We evaluate the performance of this decision rule in both the matched and mismatched signal cases. Our results show that in the matched signal case, ABORTís detection performance exceeds that of ACE and is comparable to AMF and GLRT. In the mismatched signal case, ABORTís discrimination capability is better than AMF and GLRT, but not as good as ACEís.

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