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Proceedings Paper

Design And Implementation Of A Multi-Sensor Fusion Algorithm On A Hypercube Computer Architecture
Author(s): Charles W. Glover
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Paper Abstract

A multi-sensor integration (MSI) algorithm written for sequential single processor computer architecture has been transformed into a concurrent algorithm and implemented in parallel on a multi-processor hypercube computer architecture. This paper will present the philosophy and methodologies used in the decomposition of the sequential MSI algorithm, and its transformation into a parallel MSI algorithm. The parallel MSI algorithm was implemented on a NCUBETM hypercube computer. The performance of the parallel MSI algorithm has been measured and compared against its sequential counterpart by running test case scenarios through a simulation program. The simulation program allows the user to define the trajectories of all players in the scenario, and to pick the sensor suites of the players and their operating characteristics. For example, an air-to-air engagement scenario was used as one of the test cases. In this scenario, two friend aircrafts were being attacked by six foe aircraft in a pincer maneuver. Both the friend and foe aircrafts launch missiles at several different time points in the engagement. The sensor suites on each aircraft are dual mode RADAR, dual mode IRST, and ESM sensors. The modes of the sensors are switched as needed throughout the scenario. The RADAR sensor is used only intermittently, thus most of the MSI information is obtained from passive sensing. The maneuvers in this scenario caused aircraft and missile to constantly fly in and out of sensors field-of-view (F0V). This resulted in the MSI algorithm to constantly reacquire, initiate, and delete new tracks as it tracked all objects in the scenario. The objective was to determine performance of the parallel MSI algorithm in such a complex environment, and to determine how many multi-processors (nodes) of the hypercube could be effectively used by an aircraft in such an environment. For the scenario just discussed, a 4-node hypercube was found to be the optimal size and a factor two in speedup was obtained. This paper will also discuss the design of a completely parallel MSI algorithm.

Paper Details

Date Published: 1 March 1990
PDF: 15 pages
Proc. SPIE 1198, Sensor Fusion II: Human and Machine Strategies, (1 March 1990); doi: 10.1117/12.969983
Show Author Affiliations
Charles W. Glover, Oak Ridge National Laboratory (United States)

Published in SPIE Proceedings Vol. 1198:
Sensor Fusion II: Human and Machine Strategies
Paul S. Schenker, Editor(s)

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