Multi-platform Multi-target GMTI Tracking with Out-of-sequence Measurements

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: F33615-01-M-1919
Agency Tracking Number: 011SN-0637
Amount: $99,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2001
Solitcitation Year: N/A
Solitcitation Topic Code: N/A
Solitcitation Number: N/A
Small Business Information
ALPHATECH, INC.
50 Mall Road, Burlington, MA, 01803
Duns: 094841665
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Mahendra Mallick
 Principal Engineer
 (781) 273-3388
 mahendra.mallick@alphatech.com
Business Contact
 Andrew Mullin
Title: Gen Counsel & Dir of Cont
Phone: (781) 273-3388
Email: andy.mullin@alphatech.com
Research Institution
N/A
Abstract
Sensor platforms transmit data to a central tracker using communication networks in a multi-platform network-centric tracking system. Measurements can arrive out-of-sequence (OOS) at the central tracker due to varying data preprocessing times at theplatforms, delays in transmission initiation, and communication network execution. The central tracker can also receive data out-of-sequence from a single sensor, if the sensor operates in multiple modes such as wide area surveillance and sector searchmodes. Previous researchers have addressed the OOS measurement (OOSM) filtering problem for a single target with one kinematic model, when the OOSM lies between the last two measurements (one-lag problem). We have developed and tested a new algorithm forthe OOSM filtering problem, which handles multiple-lags using a single kinematic model. We propose to develop additional algorithms to handle multiple lags and multiple kinematic models. Previous efforts have used data reprocessing and buffering formulti-target multi-sensor tracking problems. These approaches are undesirable due to the high storage and CPU requirements. No algorithm exists at present that addresses the multi-target multi-sensor OOSM problem. We propose to develop new algorithmsfor data association and likelihood computations for OOSM multi-target multi-sensor tracking using our multiple-lag and multiple-model OOSM filtering algorithms.This research will benefit surveillance of the battlespace where out-of-sequence measurementscan occur due to the use of multiple platforms to obtain a coherent and integrated picture of the battlespace. This effort will directly benefit a number of government funded programs such as MPTE, AMSTE, CAESAR, and DDB where real data collection andresearch include out-of-sequence GMTI sensor measurements. Commercial applications of the research include air traffic surveillance, border surveillance by the Drug Enforcement Agency and the Immigration and Naturalization Service.

* information listed above is at the time of submission.

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