Effective operation of autonomous maritime systems requires sensor architectures tailored to mission-specific requirements, as key performance criteria like accuracy and energy consumption vary significantly by operational context. Against this background, this
study develops a dual-stage, multi-criteria procedure to evaluate and assess individual sensors accounting for scenario-based requirements, using the TOPSIS algorithm as its core method. The first stage individually assesses sensors against scenario-specific requirements to generate context-aware weighting factors (α_i^(s)). In the second stage, these factors are used to evaluate the overall performance of seven predefined sensor suites across five distinct operational scenarios (e.g., ‘Coastal Surveillance’ or ‘Protection of Critical Infrastructure’). The procedure is complemented by an architectural robustness assessment that systematically captures the impact of component failures. This flexible approach serves as a generic decision framework for designing unmanned maritime systems across different mission profiles. By integrating key performance metrics and failure scenarios within a context of prioritized operational requirements, the dual-stage multi-criteria procedure enables more than just selecting an optimal configuration. It reveals the fundamental architectural design principles. Our results demonstrate that for precision-focused tasks such as ‘Coastal Surveillance’, specialized sensor suites combining electro-optical and laser rangefinder achieves the highest performance score (0.84). Conversely, for scenarios with balanced requirements like ‘Protection of Critical Infrastructure’, architectures based on functional complementarity (e.g., electro-optical and Radar, score (0.64)) prove most effective. A key finding is that maximizing sensor quantity does not guarantee optimal performance, as targeted, mission-specific configurations often outperform fully integrated systems. The significance of this study lies in providing a systematic framework that shifts the design paradigm from a ‘more is better’ approach to an intelligent, context-aware composition, enabling the development of truly robust and efficient sensor architectures for autonomous maritime systems.