A mission engineering method for maritime combat system-of-systems simulation based on temporal logic and dynamic criteria reconstruction

With the profound transformation of systems engineering towards the Digital Mission Engineering (DME) paradigm, maritime combat system-of-systems (SoS) simulation faces systematic challenges in transitioning from equipment-driven to mission-driven approaches. Existing micro-implementation methods for DME suffer from shallow logical constraints, static evaluation criteria, and fragmented engineering processes, which hinder the efficient exploration of complex maritime kill webs. To address these issues, this paper proposes a novel maritime combat SoS simulation mission engineering method based on temporal logic and dynamic criteria reconstruction. Firstly, a three-layer closed-loop mission engineering framework is constructed, integrating semantic normalization, formalization dimensionality reduction, and situational awareness evaluation. Specifically, the conceptual layer utilizes ontology and domain-specific language (DSL) to build structured knowledge graphs. The framework explicitly bridges the semantic gap between operational concepts and engineering implementation, achieving full-chain systematic collaboration with bidirectional feedback links among the layers. Secondly, Allen’s Interval Algebra (AIA) is systematically introduced to establish a rigorous temporal constraint mapping. AIA accurately encodes complex tactical doctrines, including strict sequential actions, overlapping windows, and resource mutual exclusion constraints. By combining this with a Constraint Satisfaction Problem solver to construct a simulation front-end logical filter, this method fundamentally breaks through the combinatorial explosion and tactical infeasibility dilemmas faced by traditional heuristic optimization algorithms. It proactively filters out logically infeasible plans before high-cost simulations, thereby significantly reducing the design space and improving computational efficiency. Furthermore, an innovative multi-dimensional mutual mapping function is proposed, encompassing belief-utility, decision-criterion, and evaluation-model mappings. A data-and-model dual-driven dynamic evaluation reconstruction mechanism is introduced, utilizing combat network analysis and kernel density estimation to dynamically adjust weights and thresholds. The mutual mapping functions effectively couple cognitive states, operational decisions, and evaluation results. This enables the deep integration of effectiveness evaluation with the OODA loop, ensuring that evaluation criteria adapt seamlessly to real-time battlefield situations. Simulation and scenario-based demonstrations of typical maritime combat operations, such as ship-aircraft cooperative anti-ship warfare, demonstrate that this method effectively overcomes the challenges of combinatorial explosion and rigid criteria. It significantly enhances the design efficiency of simulation solutions and the operational credibility of assessment conclusions by providing interpretable, context-aware rankings of alternatives. These experiments validate the method's capability in managing combinatorial complexity, eliminating logically infeasible schemes, and providing explainable, situational-aware decision support. Ultimately, this research provides a comprehensive digital mission engineering methodology for simulating complex maritime kill webs, offering robust theoretical and practical support for the intelligent simulation and evaluation of future maritime operational systems.