DocumentCode :
896471
Title :
Subcanceller: adaptive generalised sidelobe canceller with optimum subband decomposition
Author :
Yang, W.-S. ; Fang, W.-H. ; Lin, C.-Y.
Author_Institution :
Dept. of Electron. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei
Volume :
1
Issue :
3
fYear :
2007
fDate :
6/1/2007 12:00:00 AM
Firstpage :
198
Lastpage :
206
Abstract :
This paper presents a subband beamformer with the generalised sidelobe canceller (GSC) as the underlying structure. This new beamformer, referred to as the subcanceller, determines the statistically optimum filter bank succeeding the blocking matrix of the GSC based on the minimum mean-square error criterion. As a consequence, the signals passing through the lower branch of the GSC are decomposed into more appropriate subband components by such filter banks according to the input data statistics to enhance the interference suppression capability. The determination of the filter bank coefficients, however, calls for computationally demanding nonlinear optimisation. To alleviate the computational overhead, an iterative procedure is also proposed, which solves the Rayleigh quotient in each iteration. Furthermore, a detailed performance analysis of the proposed beamformer is conducted, which includes the development expression of the output signal to interference-plus-noise ratio and its implications, and the analysis of the convergence characteristic. Furnished simulations show that the new scheme yields superior interference suppression performance with a faster convergence rate compared with previous studies.
Keywords :
adaptive signal processing; channel bank filters; interference suppression; iterative methods; mean square error methods; Rayleigh quotient; adaptive generalised sidelobe canceller; interference suppression; iterative procedure; minimum mean-square error criterion; optimum subband decomposition; output signal to interference-plus-noise ratio; statistically optimum filter bank; subband beamformer;
fLanguage :
English
Journal_Title :
Radar, Sonar & Navigation, IET
Publisher :
iet
ISSN :
1751-8784
Type :
jour
Filename :
4225364
Link To Document :
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