Human Factors in the Design of Human–Machine Interfaces for Counter-Drone Systems

This paper examines human–machine interfaces (HMIs) for counter‑UAS systems and identifies the interaction patterns that most strongly affect operator performance in multi‑sensor, time‑critical environments. By analysing how operators interpret fused tracks, manage alerts, and verify targets under workload, we highlight key design principles: clear presentation of uncertainty and data freshness, one‑action cross‑cueing to sensor views, compact evidence bundles that consolidate relevant cues, adaptive visual decluttering during multi‑track surges, and alerting schemes that combine severity with confidence while limiting overload. We propose a concise set of HMI‑focused performance indicators—time‑to‑acknowledge, time‑to‑track, time‑to‑verification, alert hygiene, interface stability under load, and evidence‑bundle completeness—to shift evaluation from sensor‑centric to operator‑centric metrics. The findings show that effective C‑UAS performance depends on interfaces that minimize cognitive friction, compress critical actions, and maintain situational clarity even under stress.