This paper presents a proof-of-concept system for localising ground-based WiFi access points, acting as IEEE~802.11mc Fine Time Measurement (FTM) responders, from an uncrewed aerial vehicle using FTM ranging and Global Navigation Satellite System (GNSS)-referenced moving-baseline multilateration. Each associated GNSS-referenced FTM-initiator pose supplies a known reference point, turning the flight trajectory into a temporal multilateration problem. The real-time smartphone pipeline performs GNSS--ranging time association, robust outlier gating, a two-stage Gauss-Newton bootstrap, and sequential Bayesian filtering with bias tracking. Six measurement-noise configurations, including empirical and adaptive models, are evaluated on field data collected in unstructured, mountainous terrain. For a line-of-sight access point with \num{455} ranging measurements, the online Android pipeline achieves a final horizontal error of \SI{4.4}{\metre}, while offline replay of the same flight yields a time-weighted mean horizontal error of \SI{4.7}{\metre} and a best-case final horizontal error of \SI{1.1}{\metre} under the best noise model after a close flyby. For non-line-of-sight targets, the real-time pipeline does not converge because of limited measurement availability, weak geometry, and signal attenuation, although an offline robust least-squares solver recovers a coarse solution for the vegetation-only case. The system is intended as a building block for Networked One Search Agent architectures, and preliminary middleware tests demonstrate software-level interoperability, while quantitative multi-agent accuracy is left for future work.