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15 July 2002 Applying model abstraction techniques to the Advanced Low Altitude Radar Model (ALARM)
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Abstract
Modeling of real systems relies on the arduous task of describing the physical phenomena in terms of mathematical models, which often require excessive amounts of computation time when used in simulations. In the last few years there has been a growing acceptance of model abstraction whose emphasis rests on the development of more manageable models. Abstraction refers to the intelligent capture of the essence of the behavior of a model, without all the details. In the past, model abstraction techniques have been applied to complex models, such as Advanced Low Altitude Radar Model (ALARM) to simplify analysis. The scope of this effort is to apply model abstraction techniques to ALARM; a DoD prototype radar model for simulating the volume detection capability of low flying targets within a digitally simulated environment. Due to the complexity of these models it is difficult to capture and assess the relationship between the model parameters and the performance of the simulation. Under this effort ALARM parameters were modified and/or deleted and the impact on the simulation run time assessed. In addition, several meta-models were developed and used to assess the impact of ALARM parameters on the simulation run time. This paper establishes a baseline for ALARM from which additional meta-models can be compared and analyzed.
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Gary A. Plotz and Serena Dibble "Applying model abstraction techniques to the Advanced Low Altitude Radar Model (ALARM)", Proc. SPIE 4716, Enabling Technologies for Simulation Science VI, (15 July 2002); https://doi.org/10.1117/12.474914
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