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Existing wideband beampattern synthesis methods usually require multiple beamformers, each corresponding to one frequency bin, which results in excessive resource consumption in engineering practice. To alleviate the resource consumption of wideband array beamforming, we propose a novel time-domain wideband digital beamformer that can control the beam shape over the whole bandwidth for interference mitigation by using only one set of amplitude–phase weights and integer time delay filters. To tackle the resultant optimization problem, two effective algorithms are introduced, and both can solve the problem within polynomial time. One is an alternating optimization algorithm that decomposes the original problem into multiple tractable subproblems iteratively. The other is the convex approximation algorithm that transforms the original problem into a series of second-order cone programming problems iteratively. The two algorithms exhibit their respective advantages in terms of convergence and computational complexity. Extensive numerical examples are presented to evaluate the proposed time-domain wideband beamforming strategy, highlighting that it can form a deep notch in any interested spatial–spectral region to suppress the strong interferences. [ABSTRACT FROM AUTHOR]

Distributed phased Multiple-Input Multiple-Output (phased-MIMO) radar system consisting of separated subarrays possesses a high angle resolution but with sharing high sidelobes. This paper therefore focuses on the design of a virtual low-sidelobe beampattern in distributed phased-MIMO radar. An iterative framework with respect to subarray layout and receive weighting coefficients is proposed to minimize beampattern Peak Sidelobe Level (PSL) accounting for practical position constraints as well as the mainlobe level restriction. In each iteration, an efficient cyclic optimization algorithm based on the Coordinate Descent (CD) framework is developed to seek for the subarray layout through splitting high dimensional layout optimization problem into multiple one-dimensional optimization problems, and the SemiDefinite Relaxation (SDR) technique and rank one approximation are explored to design weighting coefficients. Numerical simulations are provided to assess the performance of the proposed algorithms in term of the achieved beampattern under different constraints and parameter settings. [ABSTRACT FROM AUTHOR]

This letter deals with a shaped beampattern synthesis problem through controlling the mainlobe ripple and the output filter energy based on the minimization of the peak sidelobe level in the spatial region of interest. To tackle the challenging optimization problem with nonconvex constraints, a novel first-order iterative convex approximation (FOICA) procedure that handles the nonconvex constraints with their convex upper bound functions resorting to the first-order Taylor expansion is developed. Hence, in each iteration, the original problem is approximated through a convex problem globally solved via a polynomial time method. Additionally, a nonnegative slack variable to ensure a decreasing trend in the objective function during the iteration is introduced. Finally, the numerical simulations are provided to verify that the proposed algorithm outperforms the state-of-the-art algorithms in terms of achieved beampattern performance. [ABSTRACT FROM AUTHOR]