Cooperative drone sensing improves target detection with less data upload
When Weak Reports Matter: Staged Anchored Fusion for Cooperative UAV Sensing
Networking and Internet Architecture
Summary
Detecting targets with multiple drones can be tricky because some useful hints get lost when drones try to agree on what they see. The authors found a better way to keep strong, confident signals first, then carefully check weaker hints connected to those strong signals. This approach helps find more targets without needing to share as much data between drones. Testing showed it recovers extra targets accurately while cutting down unnecessary data sharing a lot.
What this means in practice
- •For drone fleet operators: Improve target detection accuracy while reducing communication load in coordinated UAV sensing missions.
- •For defense surveillance teams: Enhance cooperative UAV sensing to find more targets with fewer false alarms and lower data transmission in tactical environments.
Authors
Xingqin Lin
Abstract
Local multipath rejection can erase evidence needed for cooperative sensing. We propose staged anchored recovery: preserve strong-only confirmations, then query compatible weak reports using unused strong anchors. For any number of sensing nodes, we prove lossless residual screening and derive corroboration and bidirectional cost laws. In 1,024 five-UAV drops, recovery adds 30 matched targets and three false outputs over strict consensus, matching one-pass anchored confirmation's detection counts while reducing weak uploads by 97.4%. Equal-sized cue/report records yield 4.5% less payload than uploading all eligible reports. Independent validation recovers four additional targets with no observed false outputs.