Optimizing Signal Interference in Airborne Radar Systems: A Systems-of-Systems Analysis

This paper explores the theory of systems of systems, presenting a practical application in the context of airborne radar interference. Utilizing principles from control theory, assume-guarantee contracts, and game theory, we describe several interconnected techniques and theory to manage the complexities inherent in such systems. In systems of systems, where multiple systems are interconnected, the output of one system can influence another, leading to intricate feedback loops that may impair individual system performance, especially in adaptive control systems. Thus, effective denoising becomes crucial. Through a detailed analysis of radar interference scenarios, we propose a method for isolating an agent’s own signal amidst the operation of multiple cognitive radars in close proximity. Additionally, we highlight the importance of each system to minimize interference with others, thereby reducing the need for costly denoising procedures or relying solely on classic frequency-based procedures. Rather than complete decoupling, we propose a decentralized approach applicable to all cooperative agents, ensuring minimal disturbance to other systems. In the radar context, this is exemplified through a time-staggering control protocol that mitigates signal interference among radars. Furthermore, we explain the importance of maintaining overall system performance, particularly convergence, in scenarios where disturbances are inevitable. To address this, we introduce a method for cooperative systems operating in environments where not all agents are fully cooperative, balancing multiple objectives while still achieving convergence toward an optimized solution. In the radar example, cooperative cognitive radars can establish priority contracts to ensure system convergence towards a consensus on objectives. Finally, we validate the practical performance of the proposed control protocol through randomized simulations, providing empirical evidence of its effectiveness. This paper is of importance to the theoretical and applications system of system analysis, multi-agent control, as well as radar inference mitigation.