Nowadays, passive and semi-passive wireless devices are increasing their appeal, particularly in the new scenario of the Internet of Things, thanks to their low complexity and low energy consumption. In this context, radio-frequency identification (RFID) and radar sensor networks (RSNs) are rising interest when the localization of (semi-)passive tags (without active transmitters) and moving passive objects is required. In this paper, we propose a novel network architecture capable of jointly localizing (semi-)passive tags and moving passive objects through the analysis of their backscattered response. The reciprocal interference in objects/tags localization arising from the signal variations caused by objects' and tags' movement is characterized. We present an analytical derivation, based on the Cramér-Rao bound, providing the theoretical localization accuracy of tags and passive objects. The proposed approach represents a fundamental design tool providing insights on how system parameters (power and signal format), network topology, interference, and network configuration (monostatic or multistatic) affect the localization performance.