this month, the debrief reported that the US Department of Defense (DOD) had launched the low-profile“Autonomous Multi-Domain Adaptive Swarms-of-Swarms” (AMASS) project to develop autonomous drone swarms that can be launched from sea, air and land to overwhelm enemy air defenses.
The report says that AMASS aims to develop the capability to launch and command thousands of autonomous drones, working together to destroy an enemy’s defenses including air defenses, artillery pieces, missile launchers and intelligence, surveillance and reconnaissance (ISR) platforms.
The Debrief notes that while details of the project are highly classified, pre-solicitation documents show that autonomous drone swarms are likely to focus on deterring or defeating a Chinese invasion of Taiwan.
“The DARPA AMASS program is exploring the use of swarms-of-swarms to conduct military operations in highly contested environments” with“low-cost swarms with diverse sensors and kinetic and non-kinetic effectors would primarily be pre-positioned forward and launched remotely, providing rapid response and adaptability to overcome the adversary’s time-distance-mass advantage,” said a DARPA spokesperson quoted by The Debrief.
The report notes that US$78 million has been allocated for the AMASS program, with the award expected to go to a single private contractor.
in may 2022, asia times reported on the potential decisive effects of drone swarms during a Taiwan Strait crisis. Simulations done by the RAND Corporation think tank in 2020 showed that drone swarms linked by a laser“mesh” data-sharing network were decisive in ensuring a US victory in defending Taiwan against a Chinese invasion.
The US drone swarms formed a decoy screen for manned aircraft such as the F-22 and F-35, extending the latter’s sensor ranges through data-sharing and enabling them to maintain electronic silence upon approaching their targets.
The drone swarms also drastically increased the situational awareness and target acquisition capabilities of manned platforms while flooding enemy radar scopes with multiple targets, forcing the latter to expend limited missiles and ammunition and reveal their positions for manned platforms and loitering munitions to move in for the kill.
Machine learning and AI also allow drone swarms to look at targets from multiple angles, cross-check various targeting data streams and suggest the best way to attack.
Recent experience from the ongoing Ukraine war has shown the potential effectiveness of drone swarms in large-scale conventional wars. in a january article for the royal united services institute , Uzi Rubin notes that Iran’s Shahed 131/136 has been a game-changing precision weapon that has severely threatened Western air defense systems deployed to Ukraine.
Rubin notes that the Shahed’s simplicity, uncanny accuracy, low cost and long range make it unique among strategic standoff weapons. In practice, he mentions that the Shahed is operated in swarms and shows pinpoint accuracy in destroying stationary tanks, command vehicles and large installations.
Shahed’s trump card, Rubin notes, is that it is very low cost compared to cruise and ballistic missiles, meaning it can be mass-produced cheaply and deployed massively to overwhelm enemy air defenses.
It should be noted, however, that the 2020 Rand simulation resulted in a Pyrrhic victory for US and allied forces vis-à-vis China. Previous simulations resulted in the same Pyrrhic scenario, with drone swarms unlikely to prevent such an outcome.
asia times reported this january that the US might likely repel a Chinese invasion of Taiwan, but both sides will incur massive losses. In addition, a report released by the Center for Strategic and International Studies (CSIS) think tank about a simulated Chinese invasion of Taiwan in 2026 shows that defending Taiwan resulted in massive losses for the US, Japan, Taiwan and China.
In the scenario, the US and Japan lost 449 combat aircraft and 43 ships, including two aircraft carriers, and the US lost 6,960 personnel, with 3,200 killed in action. Taiwan also sustained staggering losses in the simulation, losing half of its air force, 22 ships and 3,500 ground troops with a third killed in action.
The simulation’s figures were likewise bleak for China with a loss of 138 ships, 155 combat aircraft and 52,000 ground troops, with 7,000 casualties and a third of that number killed in action, 15,000 soldiers lost at sea with half that number assumed dead and 30,000 prisoners of war from landing force survivors in Taiwan.
Fast-evolving countermeasures against drone swarms may limit their effectiveness in future conflicts. for example, in an august 2022 article in small wars journal , Ryan Bridley and Scott Pastor mention several methods to counter drone swarms including traditional machine guns and missiles, microwave weapons, laser weapons, signal jamming, underground concealment of critical facilities and deploying defensive drone swarms.
However, Bridley and Scott note that these proposed counter-swarm measures have various drawbacks. They note that machine guns have a very limited range and arcs of fire, and their accuracy degrades in bad visibility conditions.
At the same time, missiles are ineffective against very low-flying drones. They also mention that the high cost of directed energy weapons takes them out of developing countries’ reach while adverse weather conditions can affect the effectiveness of lasers. Drones can also be built with reflective coatings to mitigate laser heat damage.
Bridley and Scott say that while signal jamming can be effective against low-quality drones, they can still be programmed with inertial navigation technology if signal jamming is detected and that high-end drones have various anti-jamming features.
They also note that while concealing sensitive targets underground covers and shields them from drone swarm attacks, underground concealment is costly and time-consuming. Lastly, they mention that defensive drone swarms are at risk of friendly fire from other drones and require support from other defensive systems to be effective.