Modified guidance laws for escaping a microburst with turbulence

Abstract

This paper introduces Modified Altitude-and Dive-Guidance laws for escaping a microburst with turbulence. First, a new safety metric is constructed that quantifies the aircraft upward force capability in a microburst encounter. In the absence of turbulence, the safety factor is shown to be a decreasing function of altitude. This suggests that descending to a low altitude may improve safety in the sense that the aircraft will have more upward force capability to maintain its altitude. In the presence of stochastic turbulence, the safety factor is treated as a random variable and its probability distribution function is analytically approximated as a function of altitude. This approximation allows us to determine the highest safe altitude at which the aircraft may descend, hence avoiding to descend too low. This highest safe altitude is used as the commanded altitude in Modified Altitude-and Dive-Guidance. Monte Carlo simulations show that these Modified Altitude-and Dive-Guidance strategies can decrease the probability of minimum altitude being less than a given value without compromising the probability of crash. That is, an aircraft with Modified Altitude-or Dive-Guidance can have a higher recovery altitude without increasing the risk of ground contact or stall. 1

Wind Field Estimation and Its Utilization in Trajectory Prediction

“…Several research studies have developed wind field models specific to different types of wind such as wind over ocean surface 68 or mountainous terrain, 69,70,71,72 wind in urban area, 73 tornadoes 74 and microburst. 21,75 This section presents various wind models that give the three components of the wind vector in inertial frame as functions of time and position. Prevailing wind in this research is considered to be a spatially and temporally varying vector field.…”

“…Ref. 21 and 22 model wind as spatially varying functions. There are other papers that consider prevailing wind only as random variables.…”

Aircraft Input Prediction in the Presence of Spatially Varying Wind Field

“…Several research studies have developed wind field models specific to different types of wind such as wind over ocean surface 27 or mountainous terrain, 28,29,30,31 wind in urban area, 32 tornadoes 33 and microburst. 10,34 This section presents various wind models that give the three components of the wind vector in inertial frame as functions of time and position. Prevailing wind in this research is considered to be a spatially and temporally varying vector field.…”

“…Ref. 10 and 11 model wind as spatially varying functions. There are other papers that consider prevailing wind only as random variables.…”

Model-based microburst identification using a hybridized extended Kalman filter with genetic algorithm

“…In this respect, there are different studies that span over actions and strategies to analyze pilots' behavior deciding to continue the flight through MB or abort. 6,7 On the other hand, some researches have focused on MB prediction and identification, [8][9][10][11][12] monitoring by ground-based 3D Lidar, 13 aerodynamic effects, 14,15 controller design, and guidance schemes [16][17][18][19][20][21] via numerical simulation. 22 While there are some studies on wind and MB estimation, they differ in various aspects from the present study that include the type of wind model utilized, the type of filtering process, and also the type of aircraft equations of motion used to perform their respective subjects.…”