In this thesis, the joint DOA-range estimation of stationary targets is investigated using multiple FMCW MIMOs with super-resolution capability. To address the low azimuth resolution problem of single small MIMO, a novel topology of array is used, which consists of multiple MIMOs arranged along the azimuth to increase azimuth resolution by extending the effective aperture size. According to such topology, signal models are formulated using FMCW waveform. To accurately model the scenarios, targets are considered as near-field objects for the system, but they are treated as far-field targets for each MIMO.

After formulating signal models, two algorithms are investigated and tested to localize targets in the observing domain. The generalized 2D-MUSIC algorithm is applicable for both multi-static and mono-static configurations of the system. The FBSS technique is used to tackle highly correlated signals. Though this algorithm provides super-high resolutions, it requires prior knowledge of the number of targets (model order). The performance would drop significantly by incorrect estimation of model order. To avoid this limitation, an augmented Lagrangian method is introduced for the first time to address the localization problem, which is named extended C-SALSA. This method casts target localization problem as a sparse representation problem, and then the problem is transferred from estimating targets' locations to the problem of sparse spectrum estimation. It utilizes variable splitting and augmented Lagrangian to handle objective functions. For both algorithms, with the accurate positions of sensors in the system, geometrical constraints of the system can be maintained by applying the same search grid to all virtual arrays, consequently, data association is avoided.

The feasibility of both proposed methods are analyzed with numerical simulations of point targets and electromagnetic simulations of an extended target. MATLAB simulation results demonstrate that the azimuth resolution is increased using multiple MIMOs with both proposed algorithms. Besides the resolution, the accuracy of the generalized 2D-MUSIC is also compared with the derived CRLB. Moreover, CRLB is used to analyze the potential accuracy for the estimation results of the mono-static configuration. In spite of the requirement of model order, the generalized 2D-MUSIC outperforms the extended C-SALCA for extended targets and is more robust for off-grid targets.