Innovative Situational Awareness and Decision Making Algorithms on Open Architecture System-on-Module

Period of Performance: 05/20/2015 - 11/16/2015

$100K

Phase 1 SBIR

Recipient Firm

Black River Systems Co., Inc.
162 Genesee Street
Utica, NY 13502
Principal Investigator

Abstract

Many fielded weapon systems have legacy fire control systems using diverse and proprietary message formats necessitating interface redesign whenever new data sources are integrated. We propose a set of algorithms integrated via a System on Module to legacy fire control systems that will perform multi-sensor multi-target tracking and fusion, sending precise threat target locations to a fire control system in real time. The fusion algorithms will estimate sensor biases that if uncorrected result in triangulation errors. Out of sequence measurement processing algorithms are proposed utilizing a hybrid approach to ensure real time processing speed is maintained. Our fusion approach processes both raw sensor measurements and track level data and incorporates them into a precise fused threat target location estimate. A series of modeling and simulation analysis is proposed to measure and compare the performance of the algorithms across variations in sensor measurement accuracies as well as sensors available to the fused threat location.