P. K. Menon

Optimal Strategies for Free-Flight Air Traffic Conflict Resolution

Recent advances in navigation and data communication technologies make it feasible for individual aircraft to plan and fly their trajectories in the presence of other aircraft in the airspace. This way, individual aircraft can take advantage of the atmospheric and traffic conditions to optimally plan their paths. This capability is termed as the free flight concept. While the free flight concept provides new degrees of freedom to the aircraft operators, it also brings-in complexities not present in the current air traffic control system. In the free flight concept, each aircraft has the responsibility for navigating around other aircraft in the airspace. While this is not a difficult task under low speed, low traffic density conditions, the complexities of dealing with potential conflict with multiple aircraft can significantly increase the pilot’s work load. This paper presents the development of a conflict resolution algorithm based on the quasilinearization method to enable the practical implementation of the free flight concept. The algorithm development uses nonlinear point-mass aircraft models, and incorporates realistic operational constraints on individual aircraft. The analytical framework can also incorporate information about ambient atmospheric conditions. Realistic conflict resolution scenarios are illustrated. Due to their speed of execution, these conflict resolution algorithms are suitable for implementation on-board aircraft.

New Approach for Modeling, Analysis, and Control of Air Traffic Flow

An Eulerian approach to modeling air traffic flow is advanced. This modeling technique spatially aggregates air traffic to generate models of air traffic flow in a network of interconnected, one-dimensional control volumes. The approach simplifies the problem of characterizing the air traffic flow because the order of the corresponding airspace model depends only on the number of spatial control volumes used to represent the air traffic environment and not on the number of aircraft operating in it. Under a quasi-steady-state assumption, this process results in linear models of the air traffic environment. It is shown that analysis and design methods from linear control theory can be applied to this model to yield useful approaches for characterizing and controlling the air traffic flow.

Integrated Guidance and Control of Moving Mass Actuated Kinetic Warheads

Abstract : Modeling, simulation, and integrated guidance-control of a kinetic warhead utilizing moving- mass actuators are discussed. Moving masses can be used in any speed range both in the atmosphere as well as outside it, as long as there is a force, either aerodynamic or propulsive, acting on the vehicle. Since they are contained entirely within the airframe geometric envelope, and because no mass expulsion is involved, moving-mass actuation technique offers significant advantages over conventional aerodynamic control surfaces and reaction control systems. The present research developed a high fidelity, nine degree-of-freedom simulation model of a kinetic warhead with three moving-mass actuators. This simulation model is used for actuator sizing and in the development of flight control systems. A software package for performing numerical feedback linearization technique is employed for the design of nonlinear flight control systems. Interception of non-maneuvering and weaving targets in both atmospheric and exo-atmospheric conditions are demonstrated.

Numerical State-Dependent Riccati Equation Approach for Missile Integrated Guidance Control

A x , B x = state-dependent system matrices of size n n and n m Q x , R x = state-dependent weighting matrices of sizes n n and m m r, _ r = range and range rate of the target with respect to the missile S = solution to the Riccati equation T = rocket motor thrust per unit mass acting along the longitudinal axis of the missile u = control vector of size m 1 upert = control perturbation vector of size m 1 x = state vector of size n 1 xpert = state perturbation vector of size n 1 X, Y, Z = relative position components of the target with respect to the missile y, z = position of the moving masses along the pitch and yaw axes with respect to the body yc, zc = moving-mass position commands , = pitch and yaw Euler angles of the missile y, z = line-of-sight angles

Computer-Aided Eulerian Air Traffic Flow Modeling and Predictive Control

Eulerian models are used to represent the air traffic environment as traffic flows between interconnected control volumes representing the airspace system. While these models can be manually derived for simple air traffic patterns, computer-based approaches are essential for modeling realistic airspaces involving multiple traffic streams. A computer- aided methodology for deriving large-dimensional Eulerian models of air traffic flow is described here. Starting from the specification of a few airspace parameters, and traffic data, the modeling technique can automatically construct Eulerian models of the airspace. The synthesis of air traffic flow control algorithms using the model predictive control technique in conjunction with these models is given. It is shown that the flow control logic synthesis can be cast as a linear programming problem. The flow control methodology is illustrated using air traffic data over two regions in U.S. airspace.

GPS/machine vision navigation system for aircraft

A Kalman filter based multiple sensor fusion method for determining the position of a general aviation aircraft with respect to the runway during night landing and takeoff is discussed. Known structure of the airport lights, video images acquired by an onboard video camera, position estimates from an onboard Global Positioning System (GPS), and data from an attitude indicator are integrated in a Kalman filtering algorithm. Simulation results are presented to demonstrate the feasibility of the proposed concept.

OPTIMAL FIXED-INTERVAL INTEGRATED GUIDANCE-CONTROL LAWS FOR HIT-TO-KILL MISSILES

Due to their potential for reducing the weapon size and efficiency, design methods for realizing hitto-kill capabilities in missile systems are of significant research interest in the missile flight control community. As defined in this paper, hit-tokill capability requires the missile to consistently achieve point-mass miss distances less than half the minimum dimension of the target. It has been noted in the literature that the chief contributors to the miss distance in homing missiles are the seeker errors, autopilot lag, target maneuvers, and target state estimation lag. Guidance laws for ameliorating the effects of each of these miss distance components have been discussed in several recent publications. The present research addresses the hit-to-kill missile flight control problem by casting it as an integrated guidance-control problem. By including the complete dynamics of the missile, the integrated guidance-control formulation automatically compensates for the impact of the autopilot lag on the miss distance. The resulting finite-interval control problem is then solved using a transformation approach. Interception by a kinetic warhead is used as an example to illustrate the performance of the integrated guidance-control law.

Vision-Based Position and Attitude Determination for Aircraft Night Landing

Animage-based method forthedetermination ofaircraft position andyawand pitch orientationswithrespect to therunway during night landing is described. Information derived from a modelof the airport lights together with video images acquired by an onboard video camera and roll attitude angle sensed with a roll sensor are integrated in a Kalman e ltering algorithm. Simulation results are presented to demonstrate the feasibility of the proposed concept.

Comparison Between Nonlinear Filtering Techniques for Spiraling Ballistic Missile State Estimation

During the reentry to the atmosphere, certain ballistic missiles are known to undergo violent spiraling motions induced by aerodynamic resonance between roll and yaw/pitch modes. Successful interception of such spiraling targets is critically dependent on the performance of the target state estimator. Strong nonlinearities involved in the system dynamics and measurement equations together with sensor noise make this a challenging estimation task. The performance of an extended Kalman filter (EKF), an unscented Kalman filter (UKF), and a particle filter (PF) designed for this estimation problem is compared in this paper. Additionally, a hybrid Rao-Blackwellized PF (RBPF) approach combining the EKF and the PF is also considered. Simulation results are provided to support the conclusions from the present study.

Particle Filter for Ballistic Target Tracking with Glint Noise

The performance of ballistic target interception is critically dependent on the performance of the target state estimation. The estimation performance then strongly depends on the accuracy of the measurement model. The Gaussian uncertainty distribution has commonly been used for representing the statistical properties of sensor noise, due to its mathematical simplicity and effectiveness. However, seeker sensor measurements are often corrupted by glint noise which is highly non-Gaussian, and conventional Gaussian filtering algorithms are known to show unsatisfactory performance in the presence of glint noise. This research proposes the use of a particle filter for ballistic target tracking in a glint noise environment. The target tracking performance of the particle filter is compared with that of the extended Kalman filter.