Surface-to-air Missiles Research Articles

Simulated A-10 Combat Environment

The purpose of this study was to test the feasibility of using the Advanced Simulator for Pilot Training (ASPT) in training pilots for combat in a simulated hostile environment. A combat environment was developed in which the A-10 aircraft was flown. The environment included mountaineous terrain, enemy surface-to-air missiles (SAM) and anti aircraft artillery (AAA). The offensive target was a tank located at random along the roadway. The pilots flew the mission in real time and were scored on offensive and defensive procedures. They showed clear learning for those procedures in the simulator.

The tactical air-to-ground systems effectiveness model

This paper presents an overview of a computer model currently being used to determine the relative merits of prospective tactical air-to-ground systems. The model is a deterministic representation of the interactions of air-to-ground warfare. Flights of manned aircraft, RPVs and/or standoff weapons, along with their support aircraft, are engaged against a variety of tactical ground targets and ground-to-air defences. The model utilizes offline derived data from scenario descriptions, airframe/engine performance, payload capabilities, one-on-one system survivability against anti-aircraft artillery (AAA), and surface-to-air missiles (SAMs), navigation and target acquisition capabilities, weapon lethalities, aircraft sortie rates, aircraft damages and downtimes, and defense ammunition or missile supplies. These are used to evaluate overall system effectiveness. The model is fast running so that many system options can be investigated quickly.

The role of electronics in national survival

This paper presents an adaptive path planner for unmanned aerial vehicles (UAVs) to adapt a real-time path search procedure to variations and fluctuations of UAVs’ relevant performances, with respect to sensory capability, maneuverability, and flight velocity limit. On the basis of a novel adaptability-involved problem statement, bi-level programming (BLP) and variable planning step techniques are introduced to model the necessary path planning components and then an adaptive path planner is developed for the purpose of adaptation and optimization. Additionally, both probabilistic-risk-based obstacle avoidance and performance limits are described as path search constraints to guarantee path safety and navigability. A discrete-search-based path planning solution, embedded with four optimization strategies, is especially designed for the planner to efficiently generate optimal flight paths in complex operational spaces, within which different surface-to-air missiles (SAMs) are deployed. Simulation results in challenging and stochastic scenarios firstly demonstrate the effectiveness and efficiency of the proposed planner, and then verify its great adaptability and relative stability when planning optimal paths for a UAV with changing or fluctuating performances.