MOMGABased Virtual Array for Radar Systems This paper introduces a novel antenna array synthesis for radar systems based on the concept of a virtual antenna array (VAA) and the method of momentsgenetic algorithm (MoMGA) synthesis method. The VAA concept is applied to both scanning and fixed radiation pattern arrays. The proposed VAA is introduced to simultaneously support the mediumrange radar (MRR) and the longrange radar (LRR) with beam width xc2xb17xc2xb0 for LRR and xc2xb137xc2xb0 for MRR. The proposed VAA is distinguished by its minimum number of antenna elements, simple feeding network, high efficiency, and gain, but all of these are at the expense of a large aperture antenna size compared to the planar antenna array (PAA). The VAA has the ability to have the feeding network and the radiating elements on the same layer, as compared to the multilayer PAA. The newly proposed concept is analyzed and verified analytically and experimentally. Two orthogonal (16 elements) VAAs are designed to operate in the frequency range from 23.55 to 24.7 GHz and to support a flatshoulder shape (FSS) radiation pattern for LRRMRR. The antenna was fabricated and tested experimentally, and good agreements between the simulated and measured results were noticed. The proposed VAA is introduced to solve the problems of large size, low isolations, low efficiency, feeding network, low resolution, and small coverage range for the antenna arrays of automotive radars. The proposed antenna array is introduced for automotive radar applications at 24 GHz.

MajorizationMinimization Algorithms for Analog Beamforming with LargeScale Antenna Arrays Beamforming with largescale antenna arrays (LSAA) is one of the predominant operations in designing wireless communication systems. However, the implementation of a fully digital system significantly increases the number of required radiofrequency (RF) chains, which may be prohibitive. Thus, analog beamforming based on a phaseshifting network driven by a variable gain amplifier (VGA) is a potential alternative technology. In this paper, we cast the beamforming vector design problem as a beampattern matching problem, with an unknown power gain. This is formulated as a unitmodulus leastsquares (ULS) problem where the optimal gain of the VGA is also designed in addition to the beamforming vector. We also consider a scenario where the receivers have the additional processing capability to adjust the phases of the incoming signals to mitigate specular multipath components. We propose efficient majorizationminimization (MM) based algorithms with convergence guarantees to a stationary point for solving both variants of the proposed ULS problem. Numerical results verify the effectiveness of the proposed solution in comparison with the existing stateoftheart techniques.