A new projection based algorithm for low sidelobe pattern synthesis in adaptive arrays

The primary objective of adaptive beamforming is to suppress jamming signals while maintaining the response of the array in the desired signal direction. It is also desirable to obtain low sidelobes in the adaptive beam pattern and to minimise sidelobe jitter in order to aid the performance against clutter and pulsed deception jammers. Sample matrix inversion (SMI) is one of the simplest adaptive beamforming algorithms, involving minimisation of the average output power for a set of input data vectors (snapshots), subject to constraints on the beam pattern. However, the basic SMI algorithm tends to produce beam patterns with high sidelobes away from the jammer directions and considerable weight and sidelobe jitter. Penalty function methods as given in Hughes and McWhirter (see SPIE Proc.2563, p.170-81) and methods based on subspace projection e.g. Richardson (see Proc. of EUSIPCO-94, vol.3, p.1301-4, 1994), are two types of method which can be used to overcome the problem of high sidelobes and weight jitter while maintaining an acceptable signal to noise plus interference ratio (SNIR). This paper presents a new algorithm, which has been termed 'constrained adaptive beam pattern synthesis' (CAPS). It is a projection based algorithm which incorporates the pattern fitting element of penalty function methods in order to obtain the best possible sidelobe levels. It therefore combines the benefits of subspace and penalty function approaches. Following an explanation of the algorithm, an investigation of its performance in the presence of mainlobe and sidelobe jamming is presented.