Fighter-jet-mounted guns, air-dropped bombs, ship-launched interceptor missiles, and ground-fired air defenses can only be as effective as the accuracy and timeliness of their targeting intelligence, a simple, known reality becoming increasingly pressing and relevant as the Pentagon surges ahead with its multi-domain networking strategy.
As part of this networking strategy, the Army is accelerating development of its Integrated Air and Missile Defense Battle Command System (IBCS). The system consists of a collection of radars, fire control systems, weapons, and targeting nodes connected to one another to seamlessly share time-sensitive data in real-time. IBCS, which recently shot down several cruise missile targets in a live-fire test, is slated to become operational next year.
If an F-35 fighter jet is in position to attack an enemy ship first located by ground-based radar or ship-integrated targeting sensors, then targeting details need to be identified and transmitted in real-time. For this to happen, large volumes of intelligence, surveillance, and reconnaissance (ISR) nodes need to organize, process, and analyze incoming sensor data to identify moments, objects or developments of significance to human decisionmakers.
The growing amount of ISR data is a main reason why the Defense Department and its military services are moving so quickly to implement artificial intelligence (AI), as it could arguably provide a backbone to a massive joint network.
“Industry can deliver seekers, warheads, propellants, and radar systems, yet there is a point at which you get cognitive overload at the soldier level. We can use AI to reach out and query a sensor to determine what we want to bring in,” Army Maj. Gen. Robert Rasch, the program executive officer of Missiles and Space, told an audience at the Space and Missile Defense Symposium in Huntsville, Alabama.
Rasch went on to explain that analyzing, organizing and sharing sensor data through AI and Machine Learning “aids filtering,” as the machine can understand what sensors find and bring it into our network.”
Army Futures Command Deputy Director of the Air and Missile Defense Cross Functional Team, Daryl Youngman, told the National Interest that new developments were underway. He said the Army would be developing AI-enabled decision aides to organize information at the collection point and streamline organized data transmission.
“We will build upon the IBCS mission command system with a more integrated fire control capability and create a composite picture,” he said.
AI-enabled algorithms can receive massive amounts of incoming data, bounce it off of a limitless database and draw parallels, make identifications, perform comparisons and actually solve problems and suggest optimal solutions for humans.
Ultimately, high-speed data processing and transmission is intended to support the Defense Department’s multi-service, multi-domain Joint All Domain Command and Control problem. To this end, the Army has increased collaboration with Marine Corps, Air Force and Navy platforms using common technical protocol to achieve cross-domain connectivity.
“Each of the services has its own C2 system. For the Air Force it is ABMS (Advanced Battle Management System), and the services are trying to work on how JADC2 works with them,” Jerome Dunn, Northrop Grumman’s director of Strategy and Technology for Combat Systems and Mission Readiness, told the National Interest. “The core mission of IBCS shows that a modern open system has the ability to connect systems in a way that is very attractive to any service. This provides expanded mission sets that boost value without requiring modification.”
Kris Osborn is the defense editor for the National Interest. Osborn previously served at the Pentagon as a Highly Qualified Expert with the Office of the Assistant Secretary of the Army—Acquisition, Logistics & Technology. Osborn has also worked as an anchor and on-air military specialist at national TV networks. He has appeared as a guest military expert on Fox News, MSNBC, The Military Channel, and The History Channel. He also has a Master's Degree in Comparative Literature from Columbia University.