NDLI: Robust adaptive beamforming for passive sonar using eigenvector/beam association and excision

Content Provider	IEEE Xplore Digital Library
Author	Kogon, S.M.
Copyright Year	2002
Description	Author affiliation: Lincoln Lab., MIT, Lexington, MA, USA (Kogon, S.M.)
Abstract	A new eigenvector-based robust adaptive beamforming (ABF) algorithm is presented for use with passive sonar arrays. Robustness refers to protection against self-nulling in the presence of signal mismatch. The algorithm is based on an eigenvector decomposition, similar to ABF algorithms such as dominant mode rejection (DMR) and principal components inverse (PCI). For robustness, the proposed method removes the eigenvector from the ABF weight computation deemed as the contributor to self-nulling. This approach is in contrast to eigenvector-based ABF with a white noise gain constraint which instead changes the weighting of all eigenvectors. By identifying and removing the offending eigenvector, robustness to self-nulling can be restored. The proposed eigenvector/beam association and excision (EBAE) algorithm, associates each eigenvector with a beam or angle and removes it from that beam only. The EBAE eigenvector-based ABF is compared to other robust ABF algorithms in both simulation and experimental data where it is shown to provide improved performance both in terms of interference rejection and signal separation.
Sponsorship	IEEE Signal Process. Soc
Starting Page	33
Ending Page	37
File Size	759369
Page Count	5
File Format	PDF
ISBN	0780375513
DOI	10.1109/SAM.2002.1190994
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-08-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Array signal processing Interference Acoustic beams Protection Sonar measurements Sensor arrays Noise robustness White noise Frequency domain analysis Sonar detection
Content Type	Text
Resource Type	Article

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