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We present an approach to partial adaptive beamforming based on a subspace selection technique. The subspace used is obtained analytically from the minimum interference output power of the fully adaptive ganrmlizrd sidrlobr canceler. We express the minimum interference output power as a function of the signal constraint, the noise autocorrelation matrix and the eigenvectors of the noise autocorrelation matrix projected onto the null space of the signal constraint.Computer simulations of this approach illustrate robust performance under a variety of adverse environments and array structures. Multiple broadband interferers can be incorporated within this framework. Simulations verify that ? amay design based on this method offers superior noise rejection as compared to other subspace methods [2,5]. The performance advantage is " s t apparent when the rank of the adaptive subspace is small. Introduction:A typical application for an array is to detect a signal s ( k ) , so that, the array output y ( k ) is an estimate of s(k). A c a m " approach to this problem is to constrain the airay. response in the direction of arrival (DOA) of Lhe S U I C~ and then minimise the D U P U~ power lu(k)12 This is a linearly constrained minimum variance (LCMV) approach to beamforming and is formulated as follows: find w s.t. n$~Iy(b)l~and C'w = f

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