Wideband Laguerre adaptive array with pre‐steering constraints

Abstract

Replacing TDL filters with Laguerre filters in the popular wideband Frost space-time array has resulted in a far better performance, lower computational load and faster convergence rate. Compared with IIR-based arrays, the Laguerre design also offers guaranteed convergence, much simpler design with lower computational complexity and better SINR. However, one limiting factor in all these three broadband space-time beamformers is the quantisation error in the frontend pre-steering delays which are used to compensate for the effect of misalignment between the array geometry and the look direction. To make the Laguerre beamformer robust against the quantisation error, a set of frequency domain constraints is introduced in its linearly constrained minimum variance formulation to replace the pre-steering delays. These constraints are also very flexible in incorporating different requirements such as creating multiple desired beams, placing nulls in interference directions, null broadening and pattern synthesis considerations while all these features can be handled in an adaptive manner. The comprehensive set of simulation results not only shows that the proposed algorithm outperforms the existing TDL or IIR based beamformers but it also demonstrates its great flexibility in achieving the desired pattern.

Improved Convolutional Neural Network for Wideband Space-Time Beamforming

“…To achieve accurate beam pointing and undistorted response to the signals of interest (SOIs), the pre-steering delay structures are utilized to correct the misalignment between SOI orientation and array geometry. However, this structure often has time-delay errors in practical applications, resulting in serious deterioration in performance [6,14]. Therefore, convolution constraints are introduced to remove the pre-steering delay structures [15], while this algorithm adds additional computational complexity.…”