Adaptive detection and estimation in the presence of useful signal and interference mismatches

  • Authors:
  • Antonio De Maio;Silvio De Nicola;Yongwei Huang;Shuzhong Zhang;Alfonso Farina

  • Affiliations:
  • Dipartimento di Ingegneria Elettronica e delle Telecomunicazíoni, Università degli Studi di Napoli;Dipartimento di Ingegneria Elettronica e delle Telecomunicazíoni, Università degli Studi di Napoli;Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, Hong Kong;Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, Hong Kong;SELEX-Sistemi Integrati, Rome, Italy

  • Venue:
  • IEEE Transactions on Signal Processing
  • Year:
  • 2009

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Abstract

This paper considers adaptive detection and estimation in the presence of useful signal and interference mismatches. We assume a homogeneous environment where the random disturbance components from the primary and secondary data share the same covariance matrix. Moreover, the data under test contains a deterministic interference vector in addition to the possible useful signal. We focus on the situation where an energy fraction of both the useful signal and the deterministic interference may lie outside their nominal subspaces (conical uncertainty model). Under these conditions, we devise a procedure for the computation of the joint maximum likelihood (ML) estimators of the useful signal and interference vectors, resorting to a suitable rank-one decomposition of a semidefinite program (SDP) problem optimal solution. Hence, we use the aforementioned estimators for the synthesis of adaptive receivers based on different generalized likelihood ratio test (GLRT) criteria. At the analysis stage, we assess the performance of the new detectors in comparison with some decision rules, available in open literature.