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Advanced Data Association Algorithms to Address Emerging Threats

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0860-20-C-7056
Agency Tracking Number: B19C-001-0044
Amount: $124,924.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: MDA19-T001
Solicitation Number: 19.C
Timeline
Solicitation Year: 2019
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-04-06
Award End Date (Contract End Date): 2021-10-05
Small Business Information
303 Williams Avenue Suite 131/132
Huntsville, AL 35801
United States
DUNS: 078491477
HUBZone Owned: Yes
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Mark Lambrecht
 Chief Scientist
 (256) 763-8769
 mark.lambrecht@archarithms.com
Business Contact
 Randy Riley
Phone: (256) 763-8781
Email: randy.riley@archarithms.com
Research Institution
 University of Alabama Huntsville
 Laurie Joiner Laurie Joiner
 
301 Sparkman Dr NW
Huntsville, AL 35899
United States

 (256) 824-6126
 Nonprofit College or University
Abstract

The proposed approach provides innovative sensor data association algorithms capable of performing correct data association in multi-target tracking environments with one or more sensors. Current air and missile threats have the ability to fly non-ballistic, highly maneuvering hypersonic trajectories, and the ability to maintain closely spaced trajectories. Improved detection/track association is an enabling technology for enhancing tracking and object identification. Data association is a critical precursor to the track filtering process. If data association is not performed correctly, it becomes problematic to create an accurate track on the correct target of interest. This could potentially lead to track swaps, track drops, or the creation of dual tracks. The data association process is highly coupled to the tracking process. However, there are separate and unique algorithms that perform the data association function, as many track filters are designed assuming perfect data association (which is not a valid assumption for a real-world application). Approved for Public Release | 20-MDA-10398 (2 Mar 20)

* Information listed above is at the time of submission. *

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