Title :
Low-complexity subspace selection for partial adaptivity
Author :
Goldstein, J.Scott ; Reed, Irving S. ; Smith, Richard N.
Author_Institution :
Space Commun. Branch, US Air Force Rome Lab., Rome, NY, USA
Abstract :
This paper introduces low-complexity frequency domain approximations of optimal partially adaptive sensor array processors for space communications. Space-segment sensor arrays, for military and other critical communications links, require adaptivity to provide ECCM and mitigate interference. The size, weight, and power restrictions of such platforms, however, prohibit full adaptivity. The design of low-complexity reduced-rank processors are investigated in this paper. It is demonstrated that the performance of full-rank adaptive arrays is obtainable by low-rank processors through the use of frequency domain implementations of a cross-spectral metric
Keywords :
Wiener filters; adaptive signal processing; array signal processing; electronic countermeasures; frequency-domain analysis; interference suppression; least mean squares methods; military communication; spectral analysis; ECCM; MMSE; MVDR; Wiener filter rank; cross-spectral metric; design; frequency domain approximations; full-rank adaptive arrays; interference mitigation; low-complexity reduced-rank processors; low-complexity subspace selection; military communications links; minimum variance distortionless response; optimal partially adaptive sensor array processors; partial adaptivity; power restrictions; space communications; space-segment sensor arrays; Adaptive arrays; Array signal processing; Covariance matrix; Discrete Fourier transforms; Discrete cosine transforms; Frequency domain analysis; Interference; Narrowband; Sensor arrays; Signal processing;
Conference_Titel :
Military Communications Conference, 1996. MILCOM '96, Conference Proceedings, IEEE
Conference_Location :
McLean, VA
Print_ISBN :
0-7803-3682-8
DOI :
10.1109/MILCOM.1996.569414