RAA Liaison Letter 2024 - 2025 Edition

RAA Liaison Letter – 2024 / 2025 Edition 90 a competitive edge to its targeting capability. There are presently three primary areas where the Army could leverage 4IR technologies to enhance its support joint targeting: situational awareness, kill-chain responsiveness, and strike coordination. Situational Awareness. One of the greatest challenges to personnel involved in the targeting cycle is to maintain the situational awareness necessary to detect targets. Historically this has been achieved through electronic, acoustic, seismic and visual detection methods, the fidelity of which is inevitably limited by range and meteorological conditions. 25 4IR technologies have revolutionised wide-area surveillance by transcending traditional sensor limitations. For instance, the US has created AI-generated maps that instantaneously track environmental events, like bushfires and climate shifts, on a global scale. 26 Better still, the Ukrainian Armed Forces are spearheading the use of autonomous software that simultaneously fuses feeds from drones, social media and intelligence into a single multi- layered picture of the battlefield. 27 Additionally, within the next 12 months, the US will transition its ground moving target indicator capability from aircraft to AI-enabled satellites. This development will offer significant improvements in how ground forces are able to be spotted and tracked all over the world. 28 These examples demonstrate how 4IR technologies will transform battlefield situational awareness, greatly aiding decision superiority. 29 The Army’s ability to harness such technologies will require high levels of interoperability with the joint intelligence community. Based on realistic combat-oriented training, resilient liaison networks must be forged by the Army with the Australian Geospatial-Intelligence Organisation and the Australian Signals Directorate. The Army will also need to effectively integrate semi-autonomous programming, machine learning and deep learning into its future battle management systems. Kill-Chain Responsiveness. Another key challenge entailed in targeting is the time taken to progress from initial target detection through to a post-strike assessment, otherwise known as the kill chain. 30 Augmented intelligence programs can accelerate certain aspects of the kill chain to reduce the total closure time. For instance, the Tactical Intelligence Targeting Access Node program can allow tactical nodes to aggregate vast quantities of raw data from secure and open- source media to identify targets for potential engagement from across a battlespace. 31 Once targets are found, other programs such as Watchbox can then process, exploit and disseminate (PED) targets to engagement decision-makers. 32 Following a strike, the process of battle damage assessment (BDA) can be expedited using change detection software that autonomously senses variations on the earth’s surface, with convolutional neural networks then processing inputs from cyber, visual and electromagnetic sensors (such as satellites) to provide a summary of the effects delivered across wide areas. 33 Finally, machine learning programs can catalogue the effectiveness of different weapon combinations, as they are used during tactical engagements, to shape subsequent targeting priorities. 34 While these technologies are still in their infancy, Australia should be swift to seize upon their potential as they mature. Strike Coordination . Finally, AI can greatly improve how the Army coordinates its long- range strikes with the joint force. This can be achieved using autonomous AI and machine- learning programs that digitally integrate numerous joint force firing systems into a single shared network to increase the number of potential kill-chain pathways. One such program is the Fires Synchronisation to Optimise Response in Multi-Domain Operations (FIRESTORM) in use by the US Army. The FIRESTORM program ingests data from numerous sensors and friendly units to rapidly produce strike recommendations to decision- makers. 35 This will ultimately enhance Army’s ability to contribute to joint force kill chains, … During testing, FIRESTORM successfully ingested a sensor feed, conducted target recognition, updated the digital common operating picture, and produced a strike recommendation, all in 32 seconds. 36 Another US program, Joint All-Domain Command and Control (JADC2), seeks to harness AI and machine learning to ‘extract, consolidate and process only the relevant data and information’ from a vast array of joint force sensors and information sources. 37 Programs such as these will become increasingly critical to the Army as it seeks to synchronise its newly acquired long- range strike systems with the ADF’s joint missile fleet, which will soon include the Naval Strike Missile and Tomahawk. 38 This will ultimately