Ruth D. Kreichauf

Estimation of the Roll Angle in a Spinning Guided Munition Shell

A projectile in flight follows a trajectory defined by an interaction of gravity, aerodynamics, and mechanical forces due to spin, shape and possible steering fins. The projectile’s flight phases can be described in terms of a pre-launch phase, launch phase, and ballistic phase. Generally the navigation system cannot navigate through the high-g launch phase. However, after the high-g launch phase, at the start of the ballistic phase, the navigation system has to be aligned before it can navigate. Pre-launch, parameters such as elevation angle, muzzle velocity, heading and typical spin rate for the type of shell are known. After the short launch phase these pre-launch parameters’ errors are still small enough in pitch and heading to adequately initialize the navigation system. Due to the projectiles spin, its rapidly changing roll angle is however not known. The process of estimating the roll angle in a spinning projectile is usually referred to as ‘upfinding’. Honeywell has developed innovative methods to provide solutions to the upfinding problem in spinning projectiles by using Phase-Lock Loop and correlator algorithms that can be enhanced with complementary filters to dampen aerodynamic effects. This paper presents a new upfinding solution that is simple and work by using either gyro data or a combination of both accelerometer and gyro data in the upfinding process. This solution establishes the roll angle to a degree that is sufficient for a successful subsequent fine alignment and navigation phase. This algorithm can be applied to gun-launched guidance and navigation systems in ballistic trajectories to align the inertial navigation system.

Simulation and modeling for military air operations

The Joint Forces Air Component Commander (JFACC) in military air operations controls the allocation of resources (wings, squadrons, air defense systems, AWACS) to different geographical locations in the theater of operations. The JFACC mission is to define a sequence of tasks for the aerospace systems at each location, and providing feedback control for the execution of these tasks in the presence of uncertainties and a hostile enemy. Honeywell Labs has been developing an innovative method for control of military air operations. The novel model predictive control (MPC) method extends the models and optimization algorithms utilized in traditional model predictive control systems. The enhancements include a tasking controller and, in a joint effort with USC, a probabilistic threat/survival map indicating high threat regions for aircraft and suggesting optimal routes to avoid these regions. A simulation/modeling environment using object-oriented methodologies has been developed to serve as an aide to demonstrate the value of MPC and facilitate its development. The simulation/modeling environment is based on an open architecture that enables the integration, evaluation, and implementation of different control approaches. The simulation offers a graphical user interface displaying the battlefield, the control performance, and a probability map displaying high threat regions. This paper describes the features of the different control approaches and their integration into the simulation environment.