Joint Formation and Resource Optimization for Multi-agent Sensing Systems

Multi-agent sensing systems are gaining widespread deployment due to their dynamic flexibility and collaborative benefits. Nonetheless, the sensing task's dependence on localization and formation results in a decline in sensing accuracy due to errors in these two aspects. In this paper, we provide a comprehensive analysis of the error coupling among localization, formation, and sensing. By utilizing Fisher information, we evaluate the influence of measurement and control noises on sensing accuracy, enabling us to determine an objective function for sensing under wireless resource constraints. Then we propose an iterative optimization algorithm for control strategy and resource allocation, which effectively improves sensing accuracy by minimizing the effects of localization and control errors on sensing. Simulation results demonstrate the significant performance improvements achieved by our proposed joint optimization.