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Modern military aircraft are complex with increasingly integrated sensing functionality. As mission system capability is increasingly implemented in software rather than hardware — particularly with the development of electronically steered antennas and increasing processing power for software implementations of former hardware components — the scope for specific data requirements and software loads that are tailored for missions is increasing. As the complexity of these loads increases, the operational effectiveness of each aircraft is increasingly dependent on each mission data load. Put simply: an aircraft with ten million lines of software, much of which is configurable by input data, has a significant part of its capability defined by that data. How do we ensure that the aircraft mission systems perform as required in a complex operational environment? Further, how do we provide Operations Research (OR) to support experimental testing results? A task often given to OR personnel is to construct scenarios that provide context for all levels of experimental work, both hardware lab testing, and to support any OR experimentation that builds on these results. Any scenarios developed in this process need to provide both operational realism and sufficient levels of complexity to suit a testing program. This is problematic in that large scenarios that are generated by the selection of “important” features are by their very nature biased towards particular solutions. How do we avoid bias in the scenario generation? A specific problem area is defined, namely testing the application of Intelligence Mission Data (IMD) to aircraft operations. How do you decide, with (1) a particular set of mission system hardware in a lab and a (2) reprogrammed mission data file set (MDFS) that provides the IMD in an operational form, that a fighter aircraft will be effective and survivable in a specific operational context. In testing IMD there is a need to consider all levels of the operational context as defined by a scenario: • the strategic context gives purpose and the broader physical and electromagnetic environment via the specification of an area of operation, • the operational context gives the goals or missions to be pursued, and • the tactical flow can affect the specific mission performance as this describes the specific interplay of actors. A scenario development process is defined. We use the term scenario to refer to the entire context description, including the strategic, operational and tactical levels. Strategic statements give the broader context of actors and reasoning as to the conflict, the operational level relates to the specific mission, and the tactical level refers to potential decision making within the mission. At any stage, there may be limitations on the scenario development: for example verification and validation (V&V) testing may prioritise particular threats, a time frame, the location of the operation, and so on. Design of Experiments (DOE) approaches are employed to within experimental testing and supporting OR to ensure that the IMD process meet operational needs, dependent on the scenario context. We believe that a similar DOE approach should be employed to V&V the scenarios. This can provide a rigorously verifiable method for determining the extent of scenario coverage but, furthermore, techniques from the DOE literature might be applied to the task of generating scenarios in an effort to trade-off and estimate V&V effort against scenario requirement coverage. This could be combined in future with the experimental design process, but more attractively the development of an independent scenario design method that provides some level of orthogonality within the scenario construction could greatly expand the applicability of all levels of testing, and provide a more comprehensive coverage of the potential scenario space.

Scenario design for verification and validation, hardware testing and operations research