Hybrid beamforming structure, which consists of digital precoding and analog beamforming, is a low-cost solution to millimeter wave large-scale antenna systems. In this letter, we study the sum rate maximization problem where analog beamformer is selected from a discrete codebook. A two-stage scheme is proposed in order to avoid exhaustive search. First, the lower bound of sum rate is derived, and the trace inverse of equivalent channel is determined as a novel metric for beam selection. Based on this metric, we formulate a convex problem to derive an initial beam set. Finally, an iterative algorithm is designed to update beams for further performance improvement. Simulation results demonstrate that the proposed scheme achieves a near-optimal sum rate performance and outperforms the existing schemes.

The synthetic aperture radar (SAR) imaging methods based on compressive sensing endure great computational complexity since they have to deal with a large measurement matrix when processing the raw data. An efficient ℓ _q regularisation algorithm for SAR imaging is proposed, which uses a decoupling operator constructed by means of chirp scaling. It can reduce the computational complexity from the square order to the linear logarithm order compared with the conventional ℓ _q regularisation‐based imaging algorithm while preserving the equivalent imaging quality. The proposed algorithm is efficient in the sense that it allows reconstruction of the sparse scenes with the sub‐sampling data.

With a short linear array configured in the cross-track direction, downward looking sparse linear array three-dimensional synthetic aperture radar (DLSLA 3-D SAR) can obtain the 3-D image of an imaging scene. To improve the cross-track resolution, sparse recovery methods have been investigated in recent years. In the compressive sensing (CS) framework, the reconstruction performance depends on the property of measurement matrix. This paper concerns the technique to optimize the measurement matrix and deal with the mismatch problem of measurement matrix caused by the off-grid scatterers. In the model of cross-track reconstruction, the measurement matrix is mainly affected by the configuration of antenna phase centers (APC), thus, two mutual coherence based criteria are proposed to optimize the configuration of APCs. On the other hand, to compensate the mismatch problem of the measurement matrix, the sparse Bayesian inference based method is introduced into the cross-track reconstruction by jointly estimate the scatterers and the off-grid error. Experiments demonstrate the performance of the proposed APCs’ configuration schemes and the proposed cross-track reconstruction method.

Multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) is a promising technology in radar imaging which provides a better balance of azimuth resolution and swath width compared with traditional single-input single-output (SISO) SAR. It has the potential to help scientists and engineers to design ambitious SAR system with higher resolution and wider swath. This paper studies the principle of MIMO SAR using orthogonal coding waveform and then provides the performance analysis in resolution and swath width. By using orthogonal coding waveform, lower channel interference is obtained, which makes MIMO SAR achieve wider unambiguous range swath and lower azimuth ambiguity. Simulations are carried out by means of the system parameters of real spaceborne SAR platform. A ground-based MIMO SAR imaging system with up and down chirp modulation is also designed. The performances of MIMO SAR and SISO SAR are compared, and the validity and advantage of MIMO SAR are verified.

Group sparsity based wide angle synthetic aperture radar imaging model is developed and propose a novel algorithm called backprojection based group complex approximate message passing to recover the anisotropic scene. Compared with conventional backprojection based complex approximate message passing algorithm for the recovery of isotropic scene, the proposed method accommodates aspect dependent scattering behaviour better and can produce better imagery. Simulated and experimental results are presented to demonstrate the validity of the proposed algorithm.