Stochastic prediction techniques for wind shear hazard assessment

The threat of low-altitude wind shear has prompted development of aircraft-based sensors that measure winds directly on an aircraft's intended flight path. Measurements from these devices are subject to turbulence inputs and measurement error, as well as to the underlying wind profile. In this paper stochastic estimators are developed to process onboard Doppler sensor measurements, producing optimal estimates of the winds. A stochastic prediction technique determines the level of aircraft energy performance from the wind estimates. Aircraft performance degradation algorithms presented are based on optimal estimation techniques. The prediction algorithm must balance wind shear detection performance and turbulence rejection capability, as illustrated in simulations of microburst wind shear and severe turbulence environments.