Bae Systems Information and Electronic Systems Integration Inc.

Other

Philip J Haney

Eldon M Sutphin

Paul David Fiore

Edward C Real

George P Succi

Geoffrey S Edelson

William O Devine

John E Hilliard, Jr

A correlation and track system identifies whether a Radar warning (RW) Track contains one or more emitters by receiving a set of initial Short and Long Baseline Interferometer (SBI) (LBI) detections; receiving inertial navigational data; receiving subsequent LBI detections; determining whether the LBI detections represent one or multiple emitter(s) by designating an initial SBI conic with a multiple of its one sigma conic Direction Finding (DF) accuracy window as containing the emitter; laying down a set of grid points within the SBI conic window as possible emitters' locations; summing real and imaginary values of a residual phase in the form of a unit vector at each grid point for each LBI update; identifying whether there are one or more emitters in RW track based on whether the magnitude of a peak vector is above or below a defined threshold; and invoking geolocation algorithms based on the vector's magnitude.

Cluster track identification

A system and method for detecting the trajectory of a projectile is presented. One system includes a flash detection sensor, an acoustic sensor, an optical sensor and a processor logic mounted on a vehicle. The flash detection sensor detects a flash of a projectile being launched. The acoustic sensor detects when a blast wave associated with the firing of the projectile reaches the vehicle. The optical sensor takes two or more images of the same projectile. The images are typically not in the visible light spectrum. The processor logic calculates a trajectory of the projectile based on the images and data collected by the acoustic sensor associated with the blast wave. The processor logic may generate a warning signal to warn an operator of the vehicle about the projectile.

Acoustic hostile fire indicator

A method for parameterization of data distributions for efficient information sharing in distributed sensor networks including a plurality of sensors, comprising the steps of performing Bayesian multi-source data fusion and sharing probalistic data information.

Parameterization of non-linear/non-Gaussian data distributions for efficient information sharing in distributed sensor networks

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Merrimack, NH, United States of America

Philip J Haney