Adaptive matched augmented proportional navigation

Abstract

Two new adaptive homing guidance laws are developed which are variants of Augmented Proportional Navigation (PRONAV). The first guidance law commands flight path angle rate and is referred to as adaptive matched augmented PRONAV (AMAAP). The second guidance law commands linear acceleration and is referred to as adaptive matched augmented linear PRONAV (AMALP). The major attributes of these guidance laws are (1) they are the solutions of a linear quadratic control problem, (2) they do not require an estimate of time-to-go (t.sub.go), (3) they are matched to a nonlinear model of the target's motion, (4) they adapt in real time to provide optimal guidance over each small segment of the intercept trajectory, and (5) they optimally account for missile deceleration.

Description

BACKGROUND OF THE INVENTIONThe present invention relates generally to missile guidance.The traditional approach to missile guidance is to use Proportional Navigation (PRONAV). PRONAV was developed by C. Yuan at RCA Laboratories during World War II using physical intuition [1]. The resulting simplistic guidance law states that the commanded linear acceleration a.sub.c is proportional to the line-of-sight (LOS) rate .sigma..sub.T. The proportionality constant can be broken down into the product of the effective navigation ratio N times the relative missile-target closing velocity Vc,Two decades later, the quasi-optimality of PRONAV was derived [2]. The prefix quasi is used here because of all the assumptions that must be made in deriving PRONAV as a solution of a linear-quadratic optimal control problem [3]. These assumptions are as follows:1. The target has zero acceleration.2. The missile has perfect response and complete control of its acceleration vector.3. The missile is launched...

AI Technical Summary

Benefits of technology

An objective of the invention is to increase the single-shot kill probability of tactical guided weapons via a revolutionary guidance technique.

The new features of the AMAAP and AMALP guidance laws are that the algorithms (1) do not require an estimate of time-to-go t.sub.go, (2) are matched to a nonlinear model of the target's motion over associated small segments of the intercept trajectory, (3) adapt in real time to produce optimal guidance over each of those small trajectory segments, and (4) optimally account for missile slowdown. The first feature provides a significant advantage over traditional PRONAV. This is due to the fact that a consistently accurate estimate of t.sub.go cannot be obtained, since it depends on future unknown target motion. The second and third features reveal that the new guidance laws are a priori theoretically tuned to the target state estimator. This results in a significant level of system integration between the target state estimator and the guidance laws. The importance of this is that it is now possible to greatly reduce, and perhaps even totally eliminate, the ad hoc tuning that traditionally must be done in Monte Carlo 6-dof (six degrees of freedom) simulation. Finally, the last feature eliminates the need for ad hoc approximations that attempt to account for missile deceleration.

Problems solved by technology

This is due to the fact that a consistently accurate estimate of t.sub.go cannot be obtained, since it depends on future unknown target motion.

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