Formation Control for CRLB-Optimal Cooperative Sensing in Low-Altitude Wireless Networks

TL;DR

This paper develops a formation control strategy for UAVs in low-altitude wireless networks that optimizes sensing accuracy based on CRLB, resulting in a regular polygon formation that enhances target localization.

Contribution

It analytically derives the optimal UAV formation geometry for CRLB minimization and proposes a distributed control method to achieve this formation from arbitrary initial positions.

Findings

Optimal formation is a regular polygon with isotropic Fisher information.

The proposed control scheme outperforms benchmarks in CRLB reduction.

Numerical results confirm reliable convergence and improved sensing accuracy.

Abstract

Cooperative sensing with uncrewed aerial vehicles (UAVs) is a key enabler for low-altitude wireless networks (LAWNs), where sensing accuracy critically depends on the spatial configuration of the UAV formation. In this paper, we study formation design and control for Cramer-Rao lower bound (CRLB)-optimal cooperative target sensing. We first establish a sensing performance model based on range measurements and derive the Fisher information matrix (FIM) of the target location. By adopting the A-optimality criterion, we analytically characterize the formation geometry that minimizes the CRLB of the estimation error. The optimal formation is shown to exhibit isotropic Fisher information in the horizontal plane, leading to a regular polygon geometry with an elevation angle determined by the tradeoff between path loss and geometric diversity. Building on this result, we further develop a distributed formation control strategy that steers UAVs from arbitrary initial deployments toward the sensing-optimal configuration while maintaining formation motion and obstacle avoidance. Numerical results demonstrate that the proposed scheme consistently outperforms benchmark formations in terms of CRLB and achieves reliable convergence under practical constraints.