Identifiability and performance concerns for location estimation

Common localization approaches require a large amount of information to be available in order to achieve identifiability, when the signal propagates in a strictly Non-Line-of-Sight (NLOS) environment. Furthermore, even if they achieve identifiability, they usually perform poorly. In this contribution we investigate the conditions that must be met for identifiability to be feasible and for performance to be adequate. Through basic theorems and simple numerical examples, we study the benefit of exploiting additional information, if such is available and we provide intuitive conclusions that can be proved useful for any localization scheme.