A Monte Carlo approach for predicting aircraft detection by MANPADS

Abstract

The uprising threat and employment of man-portable air-defense systems (MANPADS) demand a robust planning for air missions, which can enhance the probability of survival of the aircraft and the mission’s accomplishment. In an effort to deliver an auxiliary tool for mission planning, an algorithm was developed to deal with the uncertainties in this type of scenario entitled surface-to-air infrared threat modulus (MAISA), based on the Monte Carlo method. This algorithm considers factors such as the MANPADS’s position, the aircraft’s position, atmospheric transmittance and factors related to MANPADS’s infrared detector.