A number of radar applications require knowledge of the full target state vector.
Localization-driven topology optimization can outperform the location- and velocity-driven one.
The log-determinant cost function allows for a lower computational complexity than the frame potential cost function.
The greedy optimization of the log-determinant gives better performance than the convex optimization of the maximum eigenvalue.