Can We Detect Small Drones Like the One That Crashed at White House? Yes, We Can

Last week's drone incursion at the White House was harmless, but future ones might not be

2 min read
Can We Detect Small Drones Like the One That Crashed at White House? Yes, We Can
The DJI Phantom drone that crashed on a White House lawn last week.
Photo: U.S. Secret Service

Last week, a small drone belonging to a federal worker crashed on the White House grounds. Just what caused the little flyer to head off to one of the most security-sensitive sites in the world is not certain, but in any event the results were pretty harmless. Still, the incident sparked much interest in the White House’s aerial defenses should someone want to use a small drone of this kind to do real mischief.

The New York Times reported that the ill-fated drone, a DJI Phantom, was “too small and flying too low to be detected by radar,” according to government officials. So how might the U.S. Secret Service—or others worried about drone incursions to the properties they oversee—detect them? I contacted T. Adam Kelly, the CTO of DeTect, a specialty radar company based in Panama City, Fla., to discuss this issue.

Kelly told me immediately that the notion that a DJI Phantom is too small to detect with radar is, well, not exactly correct. Sure, you can’t detect one with ordinary radar, but Kelly’s company, among others, has been making systems capable of doing just that. The tricky part, he says, is not so much in sensing the subtle radar returns but in distinguishing a small drone from the many birds that your radar will also pick up.

“You’d just be floored by how many birds there are around,” says Kelly. “And you’re looking for this one incident in this mass of activity.”

Despite the difficulty, Kelly says it’s indeed possible to distinguish small drones from birds, by measuring the motion of the targets and other subtle aspects of each radar return and then applying machine intelligence to the problem. That is, you can automate the process of picking out any targets that don’t match what you’d expect for a bird or other source of radar clutter. Kelly’s company has done this, for example, for a client in Spain who needed to monitor what was in the air at a UAV-testing site.

Using radar is not the only strategy for keeping tabs on small drones, though. DroneShield, a company based in Washington, D.C., offers a system that detects nearby drones by the distinctive sounds they make. The problem with that approach, Kelly points out, is that wind noise can make it very difficult for the microphones to do their job. And, I would surmise, such a system wouldn’t be able to detect an incoming fixed-wing drone programmed to dive silently toward its target while unpowered—in the style of an early V1, say.

There’s also the possibility of detecting small drones by virtue of the radio signals that at least some of them (or their controllers) produce. That won’t help if the drone has been preprogrammed to fly to its destination without radio uplinks or downlinks. But it could, presumably, help thwart some worrisome scenarios. Defenders might even be able to stop a malicious drone by jamming its controllers’ signals. “That’s technically illegal,” says Kelly. “But the rules might be different if you’re defending the Commander-in-Chief.”

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How the U.S. Army Is Turning Robots Into Team Players

Engineers battle the limits of deep learning for battlefield bots

11 min read
Robot with threads near a fallen branch

RoMan, the Army Research Laboratory's robotic manipulator, considers the best way to grasp and move a tree branch at the Adelphi Laboratory Center, in Maryland.

Evan Ackerman

“I should probably not be standing this close," I think to myself, as the robot slowly approaches a large tree branch on the floor in front of me. It's not the size of the branch that makes me nervous—it's that the robot is operating autonomously, and that while I know what it's supposed to do, I'm not entirely sure what it will do. If everything works the way the roboticists at the U.S. Army Research Laboratory (ARL) in Adelphi, Md., expect, the robot will identify the branch, grasp it, and drag it out of the way. These folks know what they're doing, but I've spent enough time around robots that I take a small step backwards anyway.

This article is part of our special report on AI, “The Great AI Reckoning.”

The robot, named RoMan, for Robotic Manipulator, is about the size of a large lawn mower, with a tracked base that helps it handle most kinds of terrain. At the front, it has a squat torso equipped with cameras and depth sensors, as well as a pair of arms that were harvested from a prototype disaster-response robot originally developed at NASA's Jet Propulsion Laboratory for a DARPA robotics competition. RoMan's job today is roadway clearing, a multistep task that ARL wants the robot to complete as autonomously as possible. Instead of instructing the robot to grasp specific objects in specific ways and move them to specific places, the operators tell RoMan to "go clear a path." It's then up to the robot to make all the decisions necessary to achieve that objective.

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