The Digital Transformation of Battlespaces
Modern battlespaces are increasingly becoming Multi-Domain Operations (MDO) shaped by advances in AI and defense technology. Every platform, from aircraft to ground systems, now depends on secure and resilient networks. This transformation is not only redefining military strategy – but how militaries also fight offensively, how they protect forces and how the supporting communication infrastructure must evolve to counter a myriad of threats to achieve mission success.
Suppression of Enemy Air Defense (SEAD) missions illustrate this shift. SEAD missions are designed to neutralize or suppress enemy air defense systems to ensure friendly aircraft can maneuver without prohibitive risk. By enabling freedom of action for strike and support platforms, SEAD ensures that joint operations can proceed with confidence. Without suppression, air missions would face unacceptable losses and reduced effectiveness. Once defined primarily by missile strikes and kinetic operations, SEAD now adopts Artificial Intelligence/Machine Learning (AI/ML) to enable advanced capabilities in sensor fusion, electronic war fare and cyber capabilities to counter sophisticated adversaries. In this new environment, secure communications are fundamental. They sustain operational integrity and ensure teams can coordinate in real time across contested domains.
New challenge in MDO and SEAD missions for communication systems
Multi-domain and multi-modality sensing extends detection range
Modern air defense systems leverage advanced technologies to deploy a network of sensors across air, sea, ground, and space over vast geographic areas. These sensors employ state-of-the-art capabilities to detect weapon intrusions through both passive and active sensing, using multiple modalities such as SIGNT, Radar, infrared, and optical.
The new reality is that air attack weapons—and their launch platforms—will be detected and challenged by countermeasures much earlier. Consequently, the highly contested engagement zone will expand, requiring weapon and platform communication systems to remain resilient throughout the entire mission, even across significantly longer link distances that used to be non-contested.
Covers and decoys to conceal and confuse
As seen in the ongoing war in Ukraine, concealment and decoys have become routine tactics. To overcome these, weapon systems must employ real-time sensor data fusion through networked communications for data sharing, especially during the final approach to the target where enemy countermeasures are most intense. Differentiating real targets from decoys before executing the terminal strike is critical. Resilient, low-latency communication in the face of aggressive jamming is imperative to complete the kill chain successfully.
AI aided adaptive countermeasure
Integrating AI into modern air defense systems accelerates sensor data analysis and decision-making for countermeasure deployment. AI can detect weapon intrusions and identify attack tactics that human operators might miss in complex, fast-paced scenarios. Furthermore, AI can devise, organize, and deploy novel countermeasures beyond conventional strategies.
This evolution demands that air attack operations remain nimble, agile, and adaptive to outmaneuver AI-enabled defenses. Real-time collaborative decision-making among weapons enroute to their targets and their launch platforms will be essential. Achieving this requires a resilient, networked communication system capable of transmitting coordinated operational data seamlessly and with minimal latency across the entire weapon network.
Facing these challenges, advancement in persistent, stealthy, and adaptive communications across multiple domains is needed to protect sensitive information from exploitation by adversaries. These links must resist interception and sustain continuity even under direct attack. Without them, suppression efforts risk collapse, as the loss of secure communications can lead to compromised missions, strategic setbacks, and potential loss of life.
Communication Technology purpose built to these challenges in MDO and SEAD missions
Three areas will be critical in shaping the future of secure communication to continue for SEAD operations: Advanced Tactical Waveforms, Mesh Networking, AI-Driven Network Resilience.
Advanced Tactical Waveforms
The foundation of resilient communications lies in advanced waveform design. Legacy waveforms, even when modified, often carry inherent limitations that compromise Low Probability of Exploitation (LPX) and Anti-Jam (AJ) performance. Field exercises with red teams have revealed that many existing waveforms fail to meet resiliency requirements despite design modifications to be LPX/AJ.
An advanced waveform must be designed from the ground up for today’s highly contested operational environment, with LPX/AJ performance approaching physical limits. Table 1 summarizes the desired characteristics.
Table 1 Advanced Waveform Desired Characteristics and their benefits
A robust LPX/AJ waveform should maximize these characteristics while considering operational practicality. Not all waveform LPW/AJ claims are the same and understanding the details is critical to place the most effective weapons in the hands of our warfighters and decision makers.
Mesh networking
In addition to advanced physical layer waveform, a robust network datalink must include a networking layer that is agile and resilient. Mesh networking offers superior resilience against jamming and other countermeasures while providing scalability from a handful to hundreds of nodes, ideal for SEAD operation.
To some, mesh may mean every node is connect to every other node, but actual “mesh” networks most time fall far short due to node location distributions and diverse link distances. Instead, large networks may consist of a few smaller interconnected subnetworks, some of which may be full meshes, some may be a hub-spoke, and others may be sparsely connected nodes via multiple hop relays. The key in mesh network is about diverse routing paths and distributed network management that avoid single point of failure. AI and ML aided network topology management and routing optimization will shape the future for mesh network advancement.
AI-Driven Network Resilience
Defeating sophisticated air defense systems requires collaborative operations among swarms of weapons and their launch platforms. Large-scale networks with high node count face challenges in adapting rapidly to dynamic environments—platform movement, platform attrition, and jamming-induced link disruptions.
Fixed, deterministic algorithms must be augmented or replaced with AI and ML solutions that can self-optimize and self-generate to overmatch enemy AI-enabled defenses. Key capabilities include:
- Dynamic topology management for efficient routing under changing traffic patterns and priorities
- Local AI engines on weapon platforms to reduce backhaul traffic and maintain LPX/AJ performance in contested environments
Network topology management—determining which nodes are connected to which other nodes—is critical for achieving efficient data routing under changing traffic patterns and priorities. AI and ML can analyze and evaluate a vast number of parameters against numerous possible topology scenarios to generate optimal solutions far faster and more effectively than traditional algorithms.
Compact AI engines running locally on weapon platforms—rather than remotely on launch platforms or ground stations—would significantly reduce backhaul traffic and improves resilience. In highly contested environments, long-distance backhauls become extremely difficult when platforms must maintain LPX/AJ.
In summary, to defeat an AI and ML driven integrated air defense system employing multi-domain sensing, target deception, and electronic warfare, SEAD must adapt AI and ML with advanced communication network to increase effectiveness and lethality. In a future war with a near-peer adversary that can deploy large swarms of sensors, decoys, and jammers in land, sea and air to detect, deceive, and defeat the incoming weapons, a successful SEAD system must rely on a stealthy and robust communication network for supporting collaborative team operation through sensor data fusion, distributed decision making, and target identification and kill decision making. AI and ML will be at the heart of a successful SEAD systems.
Conclusion
In an era defined by contested multi-domain operations, the integration of advanced tactical waveforms, mesh networking, and AI-driven network resilience is transforming SEAD missions and elevating operational effectiveness. These innovations enable secure, adaptive, and collaborative communications that are essential for overcoming sophisticated enemy air defenses and ensuring mission success. By leveraging AI and ML, SEAD teams can outmaneuver adversaries, maintain real-time coordination, and make informed decisions even in the most challenging environments. The evolution of resilient communications not only protects critical information but also empowers warfighters to operate with confidence and agility. Ultimately, these advancements reinforce the mission’s positive impact by safeguarding lives, enhancing lethality, and securing freedom of action for joint operations in the cyber age.
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