Fact check: What technologies do coast guards use to detect drug boats?

1. Bold claims pulled from the record: what people are asserting and why it matters

Multiple recent accounts assert that coast guards now rely on a layered sensor and data‑fusion approach to spot drug boats at sea. Specific claims include operational use of Shield AI V‑BAT and Airbus Flexrotor drones for patrol and interdiction missions, routine deployment of ship and aircraft EO/IR suites such as FLIR systems, and growing reliance on spaceborne SAR and RF geolocation to find “dark” ships that turn off AIS or spoof signals. Other claims emphasize programmatic shifts — such as the US Coast Guard’s Project Minerva and contracts for data‑fusion processors — that pivot forces from manual patrols to targeted, networked interdiction. The mix of operational sorties, procurement awards, and satellite capabilities implies a deliberate move toward persistent maritime domain awareness rather than ad hoc detection. ^{[1] [2] [3] [4] [5]}

2. The toolbox: concrete technologies coast guards are using right now

Public reporting documents a consistent toolkit: small‑boat detection using airborne EO/IR and multi‑sensor gimbals (SeaFLIR and WESCAM derivatives), UAVs for persistent overwatch (Shield AI V‑BAT, Airbus Flexrotor), and maritime surveillance payloads like ViDAR on UAVs to scan wide areas optically. Space assets contribute with SAR constellations and RF‑mapping satellites that can image regardless of weather or day/night and geolocate emissions from vessels. On the command side, C2 and data‑fusion systems ingest sensor feeds and apply analytics to cue assets for interdiction. This combination of sensors, unmanned platforms, and fusion software forms the operational backbone for modern anti‑smuggling missions. ^{[6] [7] [1] [8] [3] [5]}

3. Recent deployments and milestones that prove the concept in action

In 2025 the US Coast Guard publicly expanded V‑BAT operations in the Pacific and reported successful interdictions supported by that UAS, while earlier seasonal deployments used Flexrotor drones for persistent tracking that enabled seizures. Teledyne FLIR contracts and modernization programs aboard USCG aircraft likewise indicate active sensor refreshes to improve EO/IR coverage. At the satellite level, providers such as ICEYE have expanded wide‑area SAR modes explicitly marketed for maritime domain awareness, and bigger radar missions like NISAR offer additional imagery layers. These recent events show operational uptake: drones and modern sensors are not just experiments, they are being employed in interdictions and supported by procurement decisions. ^{[1] [9] [8] [2] [3] [10]}

4. The next wave: integration, autonomy and AI are reshaping detection workflows

Programmatic efforts such as Project Minerva, ACOR‑N data‑fusion work, Mk11 radar/IFF integrations for smaller vessels, and C2 suites like SitaWare highlight a strategic push to unify disparate sensors into actionable tracks. These programs emphasize AI/ML analytic layers that correlate radar, EO/IR, AIS, and RF detections, prioritize targets, and support decision aids for interdiction. Unmanned surface vessels and persistent autonomous sensors are also being evaluated to extend presence without increasing manpower. The result is a transition from patrol‑heavy doctrine toward sensor‑driven, rapid targeting that can close with suspect vessels more efficiently. ^{[4] [5] [11] [12]}

5. What this approach still struggles with: dark ships, jamming and legal limits

Smugglers exploit vulnerabilities by operating “dark” — disabling AIS, running low signatures, or exploiting poor sensor coverage — and by using tactics such as nocturnal transfers and dispersion. Satellite and RF mapping reduce those blind spots but are not foolproof; AIS jamming and GNSS interference complicate identification and navigation. Legal and operational constraints also shape real‑world detection and response: strikes or kinetic actions against suspect vessels generate diplomatic and legal scrutiny, and concerns over technology misuse (for example, foreign tech used in strikes) have sparked debate. Detection improvements do not automatically resolve chain‑of‑custody, jurisdictional, or human‑rights questions tied to interdiction. ^{[13] [14] [15] [16] [17]}

6. Competing viewpoints and the political stakes behind the sensors

Advocates stress that layered sensors and AI fusion dramatically improve interdiction rates and reduce personnel risk, pointing to successful interdictions enabled by drones and advanced sensors as proof. Critics warn that expanded surveillance and kinetic possibilities raise legal and geopolitical risks — unilateral strikes or intelligence sharing without oversight can set precedents that adversaries may exploit. Transparency questions arise when third‑party technologies are used in contested operations, prompting calls for clearer export oversight and human‑rights assessment. The debate now centers less on whether the technology works and more on how it should be governed, shared, and constrained in law and policy. ^{[9] [16] [17] [7]}