Two-Dimensional DOA Estimation Using Sparse Arrays

Two-dimensional (2D) sparse arrays have received a lot of attention in the last decade. The main objective for such configurations is to estimate the azimuth and elevation angles of active sources. Different 2D sparse array configurations have been proposed in the literature including but not limited to L-shape, cross-shape, and planar arrays. An efficient array configuration is the one that has large degree of freedom (DOF) and proper aperture size. Moreover, large separation between the array elements is also desired to reduce the mutual coupling. In this proposal, a new 2D array configuration will be proposed. We are going to evaluate the required aperture size, and the difference coarray for the proposed array. The array will be further optimized under certain constrains. Sparse 2D-DOA estimation is used to find the angles, which shall be paired automatically. Lasso in addition to other 2D-DOA algorithms shall be implemented for comparison. The proposed configuration will be evaluated with MATLAB simulations and experimentally. The implemented system will be tested in the laboratory with dense multipath environment. Furthermore, a software-defined radio (SDR) platform will be implemented for sparse 2D-DOA estimation based on sparse array configurations. With an SDR, the system becomes flexible, simple, practical, reconfigurable, and can be experimentally-tested.