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Proceedings Paper

High-level multifunction radar simulation for studying the performance of multisensor data fusion systems
Author(s): Albert G. Huizing; Eloi Bosse
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Paper Abstract

This paper presents the basic requirements for a simulation of the main capabilities of a shipborne MultiFunction Radar (MFR) that can be used in conjunction with other sensor simulations in scenarios for studying Multi Sensor Data Fusion (MSDF) systems. This simulation is being used to support an ongoing joint effort (Canada - The Netherlands) in the development of MSDF testbeds. This joint effort is referred as Joint-FACET (Fusion Algorithms & Concepts Exploration Testbed), a highly modular and flexible series of applications that is capable of processing both real and synthetic input data. The question raised here is how realistic should the sensor simulations be to trust the MSDF performance assessment? A partial answer to this question is that at least, the dominant perturbing effects on sensor detection (true or false) are sufficiently represented. Following this philosophy, the MFR model, presented here, takes into account sensor's design parameters and external environmental effects such as clutter, propagation and jamming. Previous radar simulations capture most of these dominant effects. In this paper the emphasis is on an MFR scheduler which is the key element that needs to be added to the previous simulations to represent the MFR capability to search and track a large number of targets and at the same time support a large number of (semi-active) surface-to-air missiles (SAM) for the engagement of multiple hostile targets.

Paper Details

Date Published: 17 July 1998
PDF: 10 pages
Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); doi: 10.1117/12.327128
Show Author Affiliations
Albert G. Huizing, TNO Physics and Electronics Lab. (Netherlands)
Eloi Bosse, Defence Research Establishment Valcartier (Canada)


Published in SPIE Proceedings Vol. 3374:
Signal Processing, Sensor Fusion, and Target Recognition VII
Ivan Kadar, Editor(s)

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