Sensor selection by greedy method for linear dynamical systems: comparative study on Fisher-information-matrix, observability-Gramian and Kalman-filter-based indices

Objective functions for sensor selection are investigated in linear time-invariant systems with a large number of candidates. This study compared the performance sets obtained using three types D-optimality-based indices as objective based on greedy method. The computed snapshot-to-snapshot Fisher information matrix, observability Gramian and Kalman filter-based matrix. Both random eigenmodes considered, selecting best-performing set each identified, well computational complexity corresponding wall clock times. optimized index works best that index, expected. We also clarified trend selected by method function terms other function.