Chance-Constrained Stochastic MPC to Deterministic Second-Order Cone Programming Equivalents for Lossy Satellite Links

Unmanned aerial vehicle navigation under lossy satellite backhauls demands robust probabilistic safety guarantees. This paper introduces a rigorous chance-constrained Model Predictive Control (MPC) framework that reformulates stochastic collision avoidance into deterministic Second-Order Cone Programming (SOCP) equivalents. By integrating satellite-terrestrial telemetry via NigComSat-1R parameters, the proposed architecture guarantees recursive feasibility and robust collision avoidance within 4D Cylindrical Volume Exclusion (CVE) models under packet jitter, Age-of-Information (AoI) degradation, and telemetry latency. Comprehensive MATLAB numerical simulations validate that the derived SOCP formulation maintains strict spatial safety margins under severe packet dropout rates while satisfying real-time onboard solver execution limits. Ultimately, this approach provides a reliable paradigm shift for sub-national Unmanned Traffic Management (UTM) airspace integration.