A fire control system for a boost phase threat missile includes sensors for generating target-missile representative signals, and a multi-hypothesis track filter, which estimates the states of various target hypotheses. The estimated states are typed to generate hypotheses and their likelihoods. The states, hypotheses and likelihoods are applied to a multihypothesis track filter, and the resulting propagated states are applied to an engagement planner, together with the hypotheses and likelihoods. The engagement planner initializes the interceptor(s). Interceptor guidance uses the initialization and the propagated states and typing information to command the interceptor.

Multihypothesis threat missile propagator for boost-phase missile defense

A system providing a real-time probabilistic prediction mechanism is described herein that is adapted to the address probabilistic implementations. The described mechanism provides a better balance between the tradeoffs of accuracy versus computational resources than the prior art, which makes it suitable for real-time applications, and in some cases offers a simpler path to implementation as well. In one exemplary approach, the real-time probabilistic prediction mechanism is implemented as a system for real-time resource management.

System for real-time probablistic resource management

Boost phase intercept missile fire control system architecture

A method for engaging a target uses sensors to generate target track(s). The tracks are projected forward in time and associated with a track quality measure. The maximum seeker look angle and beamwidth, acceleration, and net radar sensitivity characteristics are listed for each type of interceptor. A plurality of target intercept times are generated for each interceptor type. The probability that the interceptor can acquire the target is determined from the projected target tracks, the quality measure, and the characteristics. The probability of hitting the target is determined from the probability of acquisition and acceleration of the interceptor type. The probabilities of acquisition and of hitting the target are aggregated, and the type of interceptor to use is the type having (a) an extreme value of the aggregation or (b) the earliest intercept time from among the interceptors having an aggregation value above a threshold value.

Sensor independent engagement decision processing

A method for engaging a hostile missile with an interceptor missile includes mathematically dividing an estimated target trajectory into portions, the junction of each portion with the next defining a possible intercept point. The engagement for each possible intercept point is modeled, to generate a probability of lethal object discrimination which is processed to generate a probability of intercept for each of the possible intercept points. The intercept point having the largest probability of intercept defines a selected intercept point from which intercept missile launch time is calculated, interceptor missile guidance is initialized, and the interceptor is launched at the calculated launch time and under the control of the interceptor missile guidance. Also, a method for estimating discrimination performance of a system of sensors includes generating sensor data signal-to-noise ratio and an aspect angle between the sensor and a lethal object. A table of probability of lethal object discrimination is generated as a function of the signal-to-noise ratio and aspect angle. The signal-to-noise ratio and the aspect angle are quantized into bins and the table with at least the signal-to-noise ratio and the aspect angle is entered to determine the probability of lethal object discrimination.

Christian E. Pedersen

Papers

Interceptor guidance for boost-phase missile defense

Multihypothesis threat missile propagator for boost-phase missile defense

Boost phase intercept missile fire control system architecture

Missile tracking with interceptor launch and control