The U.S. military plans to introduce several changes into this year’s version of the annual Black Dart counter-drone exercise, including making the threat scenarios more complex and more challenging to defend against.

Compared to earlier Black Darts, next month’s event will increase the number of unmanned aircraft systems flying at one time and provide more variation in their direction and altitude, according to organizers. More than 20 different small- and medium-sized UAS will fly in the Sept. 11-23 demonstration, and various government and industry systems will try to detect, track and negate the drones.British Police To Test A Small Fleet Of Five Drones

“Ultimately, the goal is to get a broad understanding of what is in the realm of possible,” said Navy Lt. Cmdr. Ryan Leary, the Joint Staff’s Black Dart project officer. “We want to fly as many types of UAS in as many ways as possible so we understand what these potential counter-UAS solutions can and cannot do.”

Another change is that this year’s venue, Eglin AFB, Fla., offers a larger land range than last year’s location, Naval Base Ventura County and Sea Range at Point Mugu, Calif. The extra room will provide more opportunities for experimentation on both sides of the fight.

“We can array our counter-UAS systems and spread them out,” Leary told Defense Daily Aug. 22. “We can also spread out the threat so that they’re flying at multiple threat vectors and multiple times,” which “helps us deliver more uncertainty on the threat side.”

While UAS have been shot down in past exercises, this year’s Black Dart will focus on jamming and other “non-kinetic, non-destructive” means to bring down UAS. More than 10 different negation systems will be tested.

“There’s a large number of systems coming [to Black Dart] with some sort of non-kinetic or jamming capability,” Leary said.

Aegis combat system-equipped destroyers, five kinds of military surveillance aircraft and two types of military ground-based radar also will participate. One of the goals of the exercise is to improve the fusion of data collected by different UAS detection systems, including radar, acoustic sensors and electro-optical/infrared cameras.

“There’s no one single modality of detection where we can reliably count on detection of all types of UAS,” Leary said. “We’re really looking at how can these systems combine and fuse their data in a way that we can get a solid confidence of detection and tracking regardless of the type of UAS.”