Navigating the Contested Battlefield: AI for GPS-Denied Drone Operations

In a peer conflict, we must assume that GPS will be one of the first casualties. This makes the ability of a drone to navigate in a GPS-denied environment a mission-critical capability. This SITREP provides a technical deep-dive into the AI-powered techniques that are making this possible, from visual-inertial odometry (VIO) to terrain-matching and signals-of-opportunity (SoOp) navigation. It's about giving our drones a digital compass that can't be jammed.

For the past three decades, we have become dangerously reliant on the Global Positioning System (GPS). It is a technological marvel, a silent, invisible utility that underpins everything from our precision-guided munitions to the navigation systems in our smartphones. But in a peer-level conflict, we must assume that GPS will be one of the first casualties. An adversary will do everything in their power to jam, spoof, and disrupt our access to this critical capability. This is why the ability of a drone to navigate in a GPS-denied environment is not just a nice-to-have feature; it is a mission-critical necessity.

Fortunately, we are on the verge of a technological revolution that will give our drones a digital compass that cannot be jammed. This revolution is being driven by artificial intelligence, and it is opening up a whole new world of possibilities for navigation in contested environments.

One of the most promising techniques is visual-inertial odometry (VIO). This is where we combine the data from a drone's camera with the data from its inertial measurement unit (IMU) to create a highly accurate estimate of its position and orientation. The IMU provides a rough estimate of the drone's movement, and the camera provides a way to correct for the drift that is inherent in any IMU. By fusing these two data streams together, we can create a navigation solution that is remarkably robust, even in the complete absence of GPS.

Another powerful technique is terrain-matching. This is where we use a drone's camera and a pre-loaded digital elevation map to determine its position. The drone takes a picture of the ground below, and then uses a sophisticated AI algorithm to match that picture to the map. It's the digital equivalent of looking out the window of a plane and recognizing a landmark.

And finally, there is the emerging field of signals-of-opportunity (SoOp) navigation. This is where we use the ambient radio frequency (RF) signals that are all around us—TV broadcasts, cell phone signals, even Wi-Fi networks—to determine our position. It's a clever way of turning the enemy's own infrastructure into a navigation aid.

The future of drone navigation is a multi-sensor, AI-powered fusion of all of these techniques. It is a future where our drones can fly anywhere, anytime, in any environment, without ever having to rely on the fragile, vulnerable signal from a satellite. It is a future where our drones will always know where they are, and where they are going.