Passive Multi-Modal Target Detection Architectures for Autonomous Long-Range Loitering Strike Platforms Supporting Low-Probability-of-Intercept Operations

Passive sensing architectures are increasingly required for autonomous long-range loitering strike platforms operating in contested electromagnetic environments where active emissions elevate interception risk and degrade mission survivability. This paper presents a hierarchical passive multi-modal target detection architecture integrating Electro-Optical (EO), infrared (IR), Radio-Frequency (RF), and acoustic sensing pipelines within a distributed fusion framework designed to support low-probability-of-intercept reconnaissance–strike convergence operations. The proposed architecture incorporates adaptive signal-to-noise ratio–based modality weighting, cooperative multi-node triangulation geometry, consensus-supported localisation refinement, and energy-aware sensing allocation compatible with endurance-class delta-wing unmanned aerial vehicle platforms operating under GNSS-denied conditions. Analytical evaluation demonstrates that multi-modal fusion improves detection robustness by up to 42% relative to single-sensor pipelines, while distributed consensus perception reduces localisation covariance by approximately 27% and cooperative triangulation across four sensing nodes improves localisation precision by up to 35%. Elimination of active radar emissions reduces interception exposure probability by as much as 90%, and energy-aware sensing scheduling enables persistence improvements of up to 46% during extended surveillance missions. The resulting framework establishes a scalable perception backbone for survivable autonomous strike deployment across infrastructure-limited operational theatres and provides a practical autonomy baseline for next-generation distributed loitering munition systems supporting resilient reconnaissance–strike convergence architectures.