Enhancing Coverage and Sensing in Space–Air–Ground Networks via a UAV-Assisted ISAC Framework with Satellite Backhaul

Space–air–ground integrated networks (SAGINs) are expected to support ubiquitous communication and sensing in next-generation wireless systems. In this paper, we develop a stochastic-geometry-based analytical framework for a three-tier integrated sensing and communication (ISAC) network composed of ground base stations (BSs), unmanned aerial vehicles (UAVs), and low-earth-orbit (LEO) satellites. In the proposed architecture, ground BSs are spatially distributed according to an independent homogeneous Poisson point process (HPPP), UAVs perform sensing and uplink transmission with horizontal locations modeled by an HPPP, and LEO satellites provide relay/backhaul support with ground projections following an independent HPPP. Analytical expressions for the hop-wise communication coverage probability and the single-UAV sensing detection probability are derived. The end-to-end coverage probability is rigorously formulated as a joint event, and a tractable product-form expression is obtained by exploiting the independence of the three-tier spatial processes. Monte Carlo simulations validate the analysis and illustrate how satellite relaying, UAV deployment parameters, and propagation conditions affect communication reliability and sensing detectability. The proposed framework provides useful benchmark-level insights for the design of SAGIN-enabled ISAC systems and establishes analytical building blocks for future studies on cooperative sensing fusion.