This study focuses on the shaped beam pattern synthesis based on the convex optimisation method for conformal arrays. First, the original pattern synthesis problem is transformed into a constrained optimisation problem for the power pattern. Then, it is rewritten as a convex optimisation problem through a linear approximation of weight vector. In order to enhance the resiliency of the algorithm, a robust linear approximate method is proposed with an adaptive upper bound of step size. The loss between the obtained and desired pattern is defined to dynamically adjust the upper bound. Benefiting from the flexible constraint, the proposed method can achieve the arbitrary beam pattern with fast convergence and robustness. Finally, numerous typical examples are provided to demonstrate the validity of the proposed method.

In this paper, a robust mainlobe interference suppression algorithm is proposed in a space-polarization joint domain based on a dual-polarized conformal array. An oblique projection filter can eliminate the interference while retaining the desired signal information. However, little deviation in signal parameters will lead to significant performance degradation. To solve such problems, the joint steering vector of the desired signal is corrected by solving the quadratic convex optimization problem. Parameters of interferences are first estimated by using multiple signal classification (MUSIC) joint spectrum, and then, the interference covariance matrix can be reconstructed individually to further estimate the interference steering vector. After that, the joint oblique projection operator can be established by the estimated steering vectors. Consequently, an antijamming beamformer can be obtained by the joint oblique projection filter to achieve robustness on the interference parameter estimation deviation and desired signal mismatch. Simulation experiments verify the effectiveness of the proposed method.

This article investigates the problem of robust direction‐of‐arrival (DOA) estimation with unknown sensor gain and phase uncertainties. A Dual‐Polarised Regularised Multiple FOCal Underdetermined System Solver is proposed to estimate the 2‐D DOA for the dual‐polarised conformal array. Each polarisation signal is decomposed into two orthogonal components, which are regarded as a pair of coherent signals, and the polarisation parameters are merged into the signal waveform. A sparse‐based method based on the coherent signals block is presented, implementing weight sharing and grid pruning within the block to alleviate the negative influence of the errors. Meanwhile, gain and phase errors are modelled as the equivalent noise, which can be suppressed with the adaptive adjustment for the regularisation parameter. As the insensitivity of the sparse‐based algorithm to coherent signals, the proposed algorithm can realise the blind polarisation 2‐D DOA estimation. The Cramer–Rao bound is derived, and simulations exhibit the effectiveness and robustness of the proposed method with the unknown sensor gain and phase uncertainties.