Compressive-Sensing-Aided MIMO Radar Enabling Multi-Functional and Compact Sensors in Air Scenarios Using Optimized Antenna Arrays

Abstract

We address the problem of direction-of-arrival (DoA) estimation for air targets using a compact, multi-functional radar sensor. In order to enhance the angular resolution of such sensors while exploiting the sparseness of typical air scenarios, we consider the combination of a multiple-input multiple-output (MIMO) radar approach with suitable compressive-sensing (CS) techniques. In particular, we investigate the combination of MIMO processing for two-dimensional (2D) antenna arrays with CS-based angular processing for three-dimensional (3D) target localization and 2D DoA estimation in azimuth and elevation. We analyze the benefits of randomized antenna element positions in one and two dimensions and devise optimized array geometries for practicable aperture sizes. In particular, we take physical side constraints into account, such as the smallest realizable/ desired element spacing as well as area restrictions for antenna placement within the overall aperture. The aperture area reserved by this means could be used to accommodate additional hardware components enabling a multi-functional sensor approach. Extensive computer simulation results for different 3D target scenarios illustrate the advantages of our CS-based compact MIMO radar approach with randomized antenna elements compared to fully randomized arrays, given the same number of physical antenna elements.

Keywords

• Array optimization
• compressive sensing
• direction-of-arrival (DoA) estimation
• multi-functional sensor
• multiple-input multiple-output (MIMO) radar
• mutual coherence