Array Design for Angle of Arrival Estimation Using the Worst-Case Two-Target Cramér-Rao Bound

Array Design for Angle of Arrival Estimation Using the Worst-Case Two-Target Cramér-Rao Bound

Blog Article

Sparse array design is used to help reduce computational, hardware, and power requirements compared to uniform arrays while maintaining acceptable performance.Although minimizing the Cramér-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown target directions.To handle the unknown target directions when optimizing LIPSTICK SUNSET CRUISE the Cramér-Rao bound, we propose to use the worst-case Cramér-Rao bound of two uncorrelated equal power sources with arbitrary angles.

This new worst-case two-target Cramér-Rao bound metric has some resemblance to the peak sidelobe level metric which is commonly used in unknown multi-target scenarios.We cast the sensor selection problem for 3-D arrays using the worst-case two-target Cramér-Rao bound as a convex semi-definite program and obtain the binary selection by randomized rounding.We illustrate the proposed method through numerical examples, comparing it to solutions obtained by minimizing the single-target Cramér-Rao bound, minimizing the Cramér-Rao bound for known target angles, the concentric rectangular array and the boundary array.

We show that our method selects a combination of edge and Hemorrhoidal center elements, which contrasts with solutions obtained by minimizing the single-target Cramér-Rao bound.The proposed selections also exhibit lower peak sidelobe levels without the need for sidelobe level constraints.