Multiple-input multiple-output (MIMO) radar enjoys the advantage of increased degrees-of-freedom and spatial diversity gain, but it cannot effectively resolves the targets closely spaced in the same angle cell (but different… Click to show full abstract
Multiple-input multiple-output (MIMO) radar enjoys the advantage of increased degrees-of-freedom and spatial diversity gain, but it cannot effectively resolves the targets closely spaced in the same angle cell (but different range cells). Frequency diverse array (FDA)-MIMO radar can handle this problem by exploiting its range-dependent beampattern. FDA-MIMO radar was, thus, suggested for range–angle estimation of targets. Nevertheless, it is necessary to provide theoretical performance analysis for such a relatively new radar technique. Since multiple signal classification (MUSIC) algorithm is widely adopted in most of the FDA-MIMO literature, this paper derives the Cramér–Rao lower bound and mean square error expressions in MUSIC-based range–angle estimation algorithms for a general FDA-MIMO radar. Furthermore, the corresponding range and angle resolution thresholds in target detection and localization are also derived. Numerical results verify that the FDA-MIMO indeed outperforms conventional MIMO radar in both range–angle estimation and resolution threshold performance.
               
Click one of the above tabs to view related content.