Optimal Beacon Deployment for Positioning in Cluttered Indoor Environments

Accurate indoor positioning is vital for many indoor autonomous systems. This article focuses on the influence of beacon placement on overall positioning quality in cluttered indoor environments. We first propose a metric based on the Fisher information matrix (FIM) to evaluate the performance of the positioning service provided by a specific beacon layout. After analyzing the characteristics of the FIM, we introduce an additional penalty term in the performance metric to handle singular cases. We then investigate the optimal beacon placement with respect to overall positioning quality. We derive the gradient of the optimization objective and propose an efficient optimization method called the quotient-space gradient-based particle swarm optimization (QGPSO), which combines the quotient-space PSO with the gradient ascent method, enabling the particle swarm to obtain more accurate optimization results locally while retaining the original global exploration capability. Numerical results validate our analysis and the superiority of the proposed optimization method over other baselines.