It is becoming more important for the designer of radar (and other military sensing) systems to be able to provide military commanders and procurement decision makers with a concept of how a new system can enhance warfighting capability. Showing enhanced sensor performance is no longer sufficient to sell a new system. In order to better understand issues relating to sensor employment, we develop a top-level functional architecture of the kill chain for Air-to-Ground targeting. A companion paper constructs an executable model in the form of a Colored Petri Net (CPN) from the architecture. The focus on architecture that we present here aligns well with the new Department of Defense guidance, which requires new acquisition programs to be structured around system architectures. This should provide a common reference system for communication among warfighters, planners, and technologists. The translation to an executable model should allow identification of technology insertion points.
KEYWORDS: Sensors, Monte Carlo methods, Systems modeling, Stochastic processes, Complex systems, Target detection, Computer programming, Telecommunications, Mathematical modeling, Data modeling
Air-to-Ground targeting in a kill chain requires timely information flow and coordination of a large number of complex and disparate systems and events that are distributed in space and time. Modeling and simulation of such complex systems poses a considerable challenge to the system developers. Colored Petri Nets (CPN) provide a well-established graphically-oriented simulation tool with the capability to incorporate design and performance specifications and operational requirements of complex discrete-event systems for verification and validation under a variety of input stimuli. In this paper, we present the results of a preliminary study of implementing rudimentary, yet realistic, kill chain modules for Air-to-Ground combat using CPN tools. We have developed top-level functional kill chain modules incorporating its primary functions. It is expected that the modularity of the CPN-based simulation framework will enable us to incorporate further details and breadth in system complexities in order to study real world kill-chain simulation environment as an integral part of DOD's C4ISR architecture.
The Air Force Research Laboratory develops the Advanced IR Countermeasures Assessment Model (AIAM), an in-house analysis tool for the National Air Intelligence Center (NAIC). AIAM allows NAIC analysts to predict the most effective countermeasure response by a foreign aircraft when engaged by IR missiles. This paper discusses enhancements to AIAM. These enhancements include the addition of IRCM decoys with lift and thrust forces and IRCMs with large spatial extent. A model is added which represents the IR emission form aircraft engines as an extended plume in addition to a point source. A Flare Toolkit is included, allowing the analyst to create a custom flare based on whatever information is available for use in the engagement simulation. A model for the trajectory followed by an IRCM attached to a flexible tether is added.
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