Adaptive Beamforming With Sidelobe Suppression by Placing Extra Radiation Pattern Nulls

Abstract

A new iterative adaptive beamforming (ABF) algorithm based on conventional beamformers is proposed, in order not only to steer the main lobe towards a desired signal and place radiation pattern nulls towards respective interference signals, but also to achieve a desired side lobe level (SLL). Thus, the algorithm becomes less susceptible to unpredicted interference signals than conventional beamformers. In each iteration, the algorithm finds the direction of the peak of the greatest side lobe, which is considered as direction of arrival (DoA) of a hypothetical interference signal, and the conventional beamformer is then employed to find proper antenna array weights that produce an extra null towards this direction. The iterative procedure stops when the desired SLL is obtained. The algorithm is applied on three conventional beamformers and is tested for various signal DoA, while the direction deviation of the main lobe and the nulls is recorded, to evaluate the algorithm in terms of robustness. The proposed algorithm needs a few iterations to achieve the desired SLL, and thus is much faster than any evolutionary iterative method employed for side lobe suppression. Finally, unlike methods that employ neural networks, the proposed algorithm does not need any training to become functional.

An Effective Modification of Conventional Beamforming Methods Suitable for Realistic Linear Antenna Arrays

“…Adaptive BF methods are proposed in [10] and [11], while an MVDR beamformer for null level control via quadratic programming is proposed in [12]. BF methods with sidelobe suppression are proposed in [13]- [16], while optimal BF methods implemented through convex optimization are proposed in [17] and [18]. Finally, the method proposed in [19] for pattern synthesis with low SLL takes into account the mutual coupling between the elements of a linear antenna array and could potentially be used to perform BF.…”

“…, M) that correspond to a certain polar angle θ , and therefore it can be called as the "electric phivector." By comparing (2) and (16), which express the total radiation patterns of the theoretical and the realistic array, respectively, on the xz-plane, we see that they are both produced by the dot product of the weight vector w and another vector, which is the steering vector in the case of the theoretical array or the electric phi-vector in the case of the realistic array. In other words, if a(θ) is replaced by e ϕ (θ ), then a transition is made from the radiation pattern of the theoretical array to the radiation pattern of the realistic array.…”

“…. , 16) at the inputs of the microstrip elements are shown in Table I. It seems that the impedance matching condition is fairly approximated by the two elements at the ends of the array (1st and 16th) but is fully satisfied by the rest of the array elements (m = 2, .…”

Millimetre-Wave Planar Phased Patch Array with Sidelobe Suppression for High Data-Rate Transmission

“…In order to achieve the sidelobe suppression better than 35 dB in the scan range, two sidelobe-suppression techniques are used in the design: the density tapering as the elements of subarray are deployed in diamond-shaped aperture, and the adaptive nulling algorithm [10] for adjusting the radiation power of each elements. Generally, the rectangular aperture with the triangular grid, as shown in Figure 2, is often used.…”

“…In [9], a technique is presented to place low sidelobes and nulls in desired directions by dynamically altering the thinning configuration of a linear array. In [10], the adaptive beamforming algorithm with sidelobe suppression by introducing extra nulls into the radiation pattern is proposed. In [11], a density tapering algorithm is presented for the pencil beam synthesis of linear sparse arrays.…”