Optimal condition analysis of target localization using multi-agents with uncertain positions

This paper delves into the problem of optimal placement conditions for a group of agents collaboratively localizing a target using range-only or bearing-only measurements. The challenge in this study stems from the uncertainty associated with the positions of the agents, which may experience drift or disturbances during the target localization process. Initially, we derive the Cramer–Rao lower bound (CRLB) of the target position as the primary analytical metric. Subsequently, we establish the necessary and sufficient conditions for the optimal placement of agents. Based on these conditions, we analyze the maximal allowable agent position error for an expected mean squared error (MSE), providing valuable guidance for the selection of agent positioning sensors. The analytical findings are further validated through simulation experiments.