Counter-Drone Companies: What Each Vendor Type Does (And Can't) | Airsight

The counter-drone market is projected to reach $2.32 billion by 2029, and the vendor landscape has expanded rapidly since 2023. Dozens of companies now compete for a share of $500 million in federal C-UAS grant funding, a $1.5 billion DHS contract vehicle, and new SLTT procurement authority under the SAFER SKIES Act. For buyers navigating this market, the first challenge is not choosing a vendor. It is understanding what kind of vendor you actually need.

Not all counter-drone companies do the same thing. Some build sensors. Some build jammers. Some build software. Some build complete systems. The confusion starts when every vendor claims to offer a "complete solution" regardless of what they actually make. We operate in this market as a multi-sensor detection and C2 platform provider, and we see this confusion from the inside. This guide maps the counter-drone industry into its five core technology categories, names representative companies in each, and explains where each category has structural limits that no marketing brochure will tell you.

Radar and Surveillance Sensor Companies

Companies in this category build the wide-area detection backbone: radar systems designed to track small, low-altitude objects at distances of 1 to 30+ kilometers. The core technical challenge is separating a 1-kilogram drone from birds, ground clutter, and environmental noise - a problem defined by radar cross-section (RCS) physics that we have explored in detail.

Representative companies:

• Robin Radar Systems (Netherlands/US) - Purpose-built micro-Doppler radar for drone detection. Deployed at multiple airports and used in the TSA C-UAS Test Bed Program at Miami International Airport and LAX.
• Terma (Denmark/US) - Defense-grade air surveillance radar adapted for low-altitude drone tracking. Deployed for border and critical infrastructure surveillance.
• Echodyne (US) - Compact metamaterial electronically scanned array (MESA) radar designed for small-UAS detection in both fixed and mobile configurations.

The key differentiator in this segment is how well the radar handles small-RCS targets. A radar that tracks a DJI Mavic at 2 kilometers may miss a carbon-fiber FPV drone at the same range. Buyers should ask for RCS performance data against specific drone types, not just generic range specifications.

Structural limitation: Radar detects objects but struggles to classify them. A radar track alone cannot confirm whether a contact is a drone, a bird, or debris. This is why radar-only detection architectures produce high false-positive rates without a secondary classification layer.

Radar tells you something is flying. The next question is what it is - and that is where RF detection enters the picture.

RF Detection and Cyber-Based Companies

This category includes companies that detect drones by passively monitoring their radio frequency communications. The technology ranges from directional finders that triangulate a drone's position based on its control link, to sophisticated RF-cyber platforms that parse drone communication protocols to identify the make, model, and even serial number of the aircraft. As the DHS Science and Technology Directorate has documented in its C-UAS assessment program, RF-based detection is a primary capability the federal government evaluates for operational deployment.

Representative companies:

• DroneShield (Australia/US) - RF and acoustic detection platforms used by military and law enforcement. Their DroneSentry system is deployed across multiple US government facilities.
• Dedrone (US/Germany) - Cloud-based RF detection and sensor fusion platform. Acquired by Axon in 2024, Dedrone is one of the most widely deployed commercial counter-UAS systems in the US.
• D-Fend Solutions (Israel/US) - RF-cyber takeover platform that detects and then takes control of hostile drones by exploiting their communication protocols, enabling controlled landing rather than uncontrolled crashes.
• CACI International (US) - SkyTracker RF detection family sold to US military, intelligence, and homeland security markets.

Protocol-level RF analysis is increasingly valuable under the SAFER SKIES Act, which requires SLTT agencies to establish a "credible threat" determination before taking mitigation action. RF classification provides the drone make and model data that supports that determination.

Structural limitation: RF detection depends entirely on the drone actively transmitting. A drone flying a pre-programmed GPS waypoint mission with no active control link is invisible to RF sensors. This "dark drone" gap is the reason RF-only architectures are considered incomplete by federal evaluation standards.

RF identifies the drone's identity. But security operators also need to see the target with their own eyes - and for that, the industry turns to camera-based systems.

Electro-Optical, Infrared, and Camera-Based Companies

EO/IR companies provide the visual confirmation layer. Their products use visible-light cameras, thermal imaging, or both to visually identify and track drones. AI-driven image classification - using deep learning models trained on drone image libraries - has become standard in this segment over the past three years, though as a recent Teledyne FLIR technical analysis demonstrates, most neural networks lose reliable classification cues when targets fall below approximately 10x10 pixels.

Representative companies:

• Teledyne FLIR (US) - Defense and commercial thermal imaging systems. Their Ranger HDC MR platform is deployed for critical infrastructure drone detection in Europe and the US.
• Securitas Technology (formerly Stanley Security, US) - Integrated camera-based drone detection solutions targeting commercial and government facilities.
• Axis Communications (Sweden/US) - Network cameras with AI-based drone classification capabilities, often integrated into larger multi-sensor architectures.

Structural limitation: Cameras require line of sight, and effective classification range rarely exceeds 1-2 kilometers. Weather degrades performance significantly - fog, rain, and low-light conditions reduce detection range. EO/IR works best as a confirmation layer cued by radar or RF, not as a standalone detection system.

Detection companies tell you a drone is there. Mitigation companies try to stop it. But the relationship between the two is more dependent than most buyers realize.

Mitigation and Effector Companies

Mitigation companies build the response side of the counter-UAS equation: jamming systems that disrupt control links, spoofers that manipulate GPS signals, kinetic interceptors, and directed energy weapons. This is the segment that generates the most dramatic demo videos - and the most misaligned procurement decisions.

Representative companies:

• Fortem Technologies (US) - DroneHunter autonomous net-capture interceptor. Selected for the Pentagon's Replicator-2 initiative and awarded a multimillion-dollar order for 2026 FIFA World Cup venue protection.
• AeroVironment (US) - Recently unveiled the LOCUST X3, a 20-30 kW laser counter-UAS system designed to defeat drones up to Group 3 (drones weighing 25-55 lbs with medium-altitude capability) without the logistics burden of physical interceptors.
• SkySafe (US) - Protocol-based drone takeover and safe-landing technology used by government agencies and military installations.

Structural limitation: Every mitigation system depends entirely on upstream detection and tracking to provide targeting data. A jammer that does not know where to point, a laser without a target track, or an interceptor drone without a flight vector are expensive liabilities. Under the SAFER SKIES Act, agencies must establish a "credible threat" determination before any mitigation action - which means detection infrastructure must be operational before mitigation is even relevant.

Sensors detect. Effectors respond. But neither works without the software layer that connects them - and that is where the market's center of gravity is shifting.

Command-and-Control and Integration Platform Companies

This is the segment that ties everything together. C2 platforms aggregate data from radar, RF, EO/IR, acoustic, and Remote ID sensors into a single operating picture. They automate detection workflows, reduce operator workload, and provide the decision-support interface that security teams use to assess threats and coordinate responses.

Representative companies:

• Anduril Industries (US) - Lattice AI-fueled C2 platform. In March 2026, JIATF-401 selected Lattice as the tactical C2 backbone for military counter-drone operations under an $87 million initial task order within a $20 billion contract ceiling - the largest single counter-UAS contract in US history.
• Dedrone (also operates in RF detection) - DedroneTracker C2 platform that integrates multiple sensor types. One of the few companies spanning both detection and C2 categories.
• AirSight (US) - AirGuard platform unifies radar, RF sensors, and Remote ID data into a single operating picture for airports, critical infrastructure, and event venues.

Why C2 is the strategic layer: The choice of C2 platform increasingly drives the rest of the procurement decision. A strong C2 layer that supports open integration with multiple sensor manufacturers gives buyers flexibility to mix best-of-breed hardware. A weak or closed C2 layer locks buyers into a single vendor's ecosystem and creates long-term procurement risk. This is the principle that drove JIATF-401's Lattice selection - and it applies equally to domestic security deployments.

How the Categories Work Together - And Why That Matters More Than Any Single Vendor

No single category covers the full counter-UAS mission. The architecture that federal evaluations are validating through TSA and DHS S&T testing combines detection sensors across multiple modalities, unified by a C2 platform, with mitigation capability available where legally authorized.

In practice, this means the most effective deployments pair radar companies with RF companies with EO/IR companies - all feeding a C2 platform that fuses the data and presents a single operating picture. The C2 layer is what prevents multi-sensor deployment from becoming multi-screen chaos. It is also what enables the SAFER SKIES Act's "credible threat" determination by correlating evidence across sensor types before any mitigation action is taken.

For buyers evaluating this market, the most important takeaway is that a company's category determines its structural limitations. A radar company will always need RF or EO/IR to classify targets. An RF company will always miss autonomous drones. A mitigation company will always depend on detection. Understanding these dependencies is what separates informed procurement from expensive mistakes.

Want to understand the sensor technologies these categories are built on? Read: Drone Detection Technology: The Five Sensor Modalities Every Security Buyer Should Understand.

Ready to evaluate specific vendors? Use our 4-question framework: Drone Detection Companies: The 4-Question Framework That Separates Real Solutions from Sales Pitches.

Already know what you need? Talk to our team about your site and threat profile.