New USAF focuses: fighter-like drones and electromagnetic warfare

‘Listening to new options’, according to a senior civilian advisor, is a key piece of the US Air Force process of force redesign.

One of those options is using the fighter-like drones that will come from the Collaborative Combat Aircraft (CCA) program, which was central to a panel discussion at the US Mitchell Institute’s Air Power Futures Forum in November. Another is a tighter focus on electromagnetic spectrum operations (EMSO), the currently favored term for electromagnetic warfare (EW) and related activities.

CCAs, formerly called loyal wingmen, will be much cheaper than crewed fighters and are intended to work with them and enhance their value—for example, by moving forward to detect targets. EMSO encompasses such decisive effects as seeing what is going on in a battle while blinding or deceiving the enemy’s sensors, foiling the guidance of its weapons, and disrupting its communications while preserving one’s own.

Both designs chosen for the CCA program’s Increment 1, from General Atomics and Anduril, have passed critical design review, according to Colonel Timothy Helfrich, cyber systems lead in Air Force Material Command. The project is ‘ahead in some areas’ of an overall objective to achieve initial operational capability by the end of the decade, he said—because demands had been relaxed where necessary. ‘We need to be able to know when good enough is enough. Instead of adding features, we have made tough decisions.’

Helfrich added that the air force had learned ‘appetite control’ in Increment 1, and that attitude is going into Increment 2, which is to produce new designs and will be the subject of concept refinement studies with industry early in 2025. ‘It’s dangerously close to getting started,’ he said.

Pilots are getting experience with CCAs in the complex Joint Simulation Environment, developed to support the F-35, as well as with live surrogate aircraft. One lesson: ‘Pilots are finding that they can take custody of more CCAs than we thought.’ Helfrich said. The F-35 has flown with Kratos’s Valkyrie test aircraft to demonstrate ‘disaggregation of sensors’—sharing sensor tasks between two aircraft. Helfrich calls the technique ‘unbelievably powerful’.

Mike Shortsleeve, vice president for strategy and business development for General Atomics, said that the first aircraft built under the Increment 1 contract, based on the XQ-67A design, would fly soon. Diem Salmon, vice president for air dominance for Anduril stressed that ‘the schedule is the capability, being able to deliver at the point of need is the capability.’

The air force’s goal is to own and manage a common architecture to build autonomy into CCAs, Helfrich said. Rather than ‘platform-specific autonomy’, the government side is building an industry consortium to create an evolving architecture. His point was echoed by Mike Benitez, director of strategic product development at software-focused Shield AI: ‘You need two things. You need a standard and you need governance—and not one-and-done; it requires continuous involvement.’

Autonomy is not easy. Benitez notes that ‘for every hour of mission autonomy, you need 100 hours of hardware-in-the-loop testing. Behind that is 10,000 hours of high-fidelity, real-time systems-in-the-loop testing, and that’s backed up by 100,000 hours of faster than real-time, low-fidelity systems simulation.’

Once that’s done the picture changes. In development, ‘processing is huge,’ says Shortsleeve, but once you’ve done it, the decision-making by the system is simplified and within the capacity of commercial off-the-shelf chips.

Result: CCAs will evolve in the direction of more autonomy and more onboard sensor processing, increasing the number of vehicles one pilot can manage and lightening the load on communications systems. But in the process, they will rely more on advances in EMSO to keep their systems up to date in the face of a threat that will also evolve rapidly.

‘If we lose in the spectrum, we lose the fight in the air,’ says Colonel Larry Fenner, commander of the 350th Spectrum Warfare Wing, ‘and we’re going to lose quickly. Our job is to make sure that doesn’t happen.’

The wing was activated at Eglin Air Force Base in Florida just over three years ago, and its primary function is to translate electronic and other intelligence into the mission data files (MDFs) loaded into active and passive EW systems. It assumed oversight of the F-35 Partner Support Complex, which manages the MDFs for non-Israeli exported F-35s.

There is a back-story here: as panel moderator Brigadier General (retired) Houston Cantwell explained, ‘for the last three decades, EMSO fell below the Air Force cut-line’ in budget requests and was not properly funded. Cantwell blamed budgets, but active EW, such as jamming, fell by the wayside in the era when stealth was dominant. Panelist Chris Moeller was from the BAE Systems EW business in Nashua, New Hampshire, which was once Lockheed Sanders, and in the early 1990s, the director of engineering at Sanders declared that ‘we see traditional jammer business going the way of buggy whips.’

It didn’t.

The hardware side is coming back, Moeller citing the L3Harris EA-37B Compass Call communications jamming system, built into an adaptation of the Gulfstream G550 business jet, as a system comprising ‘20-plus third-party apps on a BAE baseline’. The open architecture runs with the help of flexible software-defined radio (SDR) components.

Together with a modular approach to assembling the system—and sharing modules between different applications and uses, that opens the way, Moeller says, to upgrading without having to find more space, supply more power and carry more weight. It’s a concept already used on space systems, which is the near-term goal as EMSO technology reaches towards the target of ‘cognitive EW’—systems that can detect a previously unknown signal and respond without human intervention.

‘We’re not there yet,’ says Fenner about cognitive EW, but the government and industry are working on ways to use artificial intelligence and machine learning on the ground, to speed the flow of new data into front-line systems. ‘The data’, adds Fenner, ‘is the weapon.’