cs.NIApr 10, 2026

"Take Me Home, Wi-Fi Drone": A Drone-based Wireless System for Wilderness Search and Rescue

Authors: Weiying Hou, Luca Jiang-Tao Yu, Chenshu Wu

Organizations: The University of Hong Kong

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Abstract

Wilderness Search and Rescue (WiSAR) represents a longstanding and critical societal challenge, demanding innovative and automatic technological solutions. In this paper, we introduce Wi2SAR, a novel autonomous drone-based wireless system for long-range, through-occlusion WiSAR operations, without relying on existing infrastructure. Our basic insight is to leverage the automatic reconnection behavior of modern Wi-Fi devices to known networks. By mimicking these networks via on-drone Wi-Fi, Wi2SAR uniquely facilitates the discovery and localization of victims through their accompanying mobile devices. Translating this simple idea into a practical system poses substantial technical challenges. Wi2SAR overcomes these challenges via three distinct innovations: (1) a rapid and energy-efficient device discovery mechanism to discover and identify the target victim, (2) a novel RSS-only, long-range direction finding approach using a 3D-printed Luneburg Lens, amplifying the directional signal strength differences and significantly extending the operational range, and (3) an adaptive drone navigation scheme that guides the drone toward the target efficiently. We implement an end-to-end prototype and evaluate Wi2SAR across various mobile devices and real-world wilderness scenarios. Experimental results demonstrate Wi2SAR's high performance, efficiency, and practicality, highlighting its potential to advance autonomous WiSAR solutions. Wi2SAR is open-sourced at https://aiot-lab.github.io/Wi2SAR to facilitate further research and real-world deployment.

Figures & tables

Figure 1. Overview of Wi 2 SAR System.
Figure 2. Typical Working Scenario.
SignalRangeID TypeLimitations & Req. violated
SatComRegionalCaller IDLimited device/region; need LoS ( Ma et al., 2024 ) ❶❺
GNSSGlobal(RX only)Need active sharing, and LoS ( Moore et al., 2023b ) ❷❺
UWB5–10 mDevice IDVery short range; need LoS ( Chen et al., 2024 ) ❺
Cellularkm-levelIMEI/IMSINeed carrier/police coordination ( Albanese et al., 2022 ) ❸❺
BLE10–100 mMAC addr.Randomized MAC ( Zehner et al., 2025 ) ❹❺
Wi-Fi∼\sim 100 mMAC addr.Randomized MAC ( Fenske et al., 2021 ) ❹❺
Table 1. Comparison of RF Signals Against WiSAR Req.
Figure 3. Design and Fabrication of the Luneburg Lens. (a) Cutaway showing graded sheet-Gyroid lattice with spherical coordinates. (b) Radial volume-fraction profile. (c) 3D-printed prototype, diameter 15 cm. (d) COMSOL ( COMSOL, 2025 ) full-wave simulation of the 15-cm Luneburg Lens at 5.745 GHz, showing electric-field focusing at the antipode.
Figure 4. Luneburg Lens Beam Patterns. (a) COMSOL simulation, (b) measured beam, and (c) chamber setup; in (a,b), the blue–red color scale indicates signal strength.
Figure 5. Proposed Dual-Phase Search Scheme. Once the target device auto-reconnects to the on-drone AP, the search scheme shifts from exploratory search to guided search .
Figure 6. Prototype of Wi 2 SAR .
Figure 7. Victim Discovery Module. ❶ Dual-mode NICs lure and overhear target’s uplink packets, which are MAC-filtered and buffered by sequence number. ❷ Packets are finalized as either complete (fast/delayed) or timed-out (with loss), while absences are transient until their timers expire. ❸ RSS snapshots are then extracted and forwarded to DFM.
Figure 8. (a) FPC antenna layout. (b) Actual deployment. (c) Alignment with drone’s coord. (roll, pitch, yaw).
Figure 9. Experiment scenarios. (a)–(d) Bird’s-eye views of four test environments: an on-hill playground, a forested hill, rugged terrain, and a hillside shoreline. (e) Zoom-in of the drone in operation. (f1)–(f10) typical placements for target devices.
Figure 10. (a, b) RSS gain with Luneburg Lens (ground). (c) Extended victim discovery range (aerial).
Figure 11. Performance of Direction Finding Module. (a) Overall performance of four scenes. (b)-(g) Impact of diverse conditions. Error bars indicate 95% bootstrap confidence intervals. (h) Comparison study with ArrayTrack.
Figure 12. Example Drone Trajectories across Trials. (a) Controlled zigzag flight with angle predictions. (b) Large-area exploratory search (400m × 400m). (c) Full WiSAR trial showing grid search, followed by direction-guided search, localizing the target under foliage within 224 s.

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