GNSS-based navigation can become unreliable when signals are blocked or deliberately interfered with. For small UAV platforms operating in complex environments, this limitation motivates the exploration of alternative positioning strategies such as opportunistic navigation (OpNav). Achieving reliable high-precision positioning under a fully non-cooperative setting remains difficult in practice where no infrastructure information is available. This mode is defined by three key constraints: unknown transmitter locations, unknown environmental topology and strictly asynchronous clocks. To address this limitation, we develop a lightweight sensing and navigation framework designed for UAV platforms operating under strict hardware constraints. We model static scattering centers as environmental anchors, proving that these features restore system observability even with a single unknown emitter. To ensure real-time performance on lightweight flight controllers, a hierarchical two-stage solver is designed: Stage I derives a robust closed-form initial estimate via an algebraic differencing method that is agnostic to reflection orders; Stage II performs manifold refinement using a Clock-Null Projection (CNP) to attain the CRLB. This framework is confirmed through experiments in urban areas using commercial LTE signals. The results show that it can map unknown RF topologies with meter-level accuracy and keep navigating without prior infrastructure, offering a strong solution for UAV autonomy in environments where GNSS is unavailable.
Bian et al. (Sun,) studied this question.