Comparison on system observable degree analysis methods for target tracking

The estimation accuracy depends largely on observability and observable degree of system state components for classical Kalman filters. State estimation and computation of observable degrees based on Kalman filtering (KF) frame has received many attention in research and engineering fields, but there are still no normative and acknowledged computation methods on reasonable and justified observable degrees which should be exactly consistent with estimation accuracy by far. In order to obtain a unified definition of normative observable degree and the effective computation method satisfying some constraints and requirements, it is greatly necessary to deeply analyze and compare definitions and computation methods of the current observable degrees. Motivated by this, four typical observable degree analysis (ODA) methods are briefly reviewed and pertinently compared and analyzed in this paper. Importantly, their principles and characteristics are concisely analyzed and compared and a clear understanding is provided. Finally, the effectiveness and correctness of corresponding conclusions are verified by computer simulations based on the model of “velocity + attitude” matching transfer alignment.