Abstract:
Currently, a number of systems exist for the purpose of electromagnetic countermeasure strategy optimisation. However, these systems simply allocate jamming resources as a whole, rather than specific jamming techniques. Further, these systems do not account for important interactions in the electromagnetic spectrum (EMS) such as the constructive and destructive interactions between different countermeasures. The future effects of countermeasure actions are also not taken into account, along with their interactions with the radar modes of threats as they progress from search stages through to guidance. Lastly, and importantly, these systems do not generate an optimal cartridge load-out for a platform.
In this work, a high-level decision-support system is proposed that aims at addressing these shortcomings. This is achieved using a process of threat evaluation and countermeasure allocation that is run prior to mission commencement based on available intelligence information. On a time-interval-by-time-interval basis, threats are first prioritised according to their characteristics and overall level of danger they present to the platform, before countermeasures are allocated so as to minimise this danger. Competing strategies are compared and optimised using a genetic algorithm according to various metrics such as risk, cost and levels of emission control (EMCON). The developed strategy can then be used in a decision-support role to inform, guide, and train mission planners. Alternatively, the strategy can also be used to directly program the electromagnetic countermeasure system of the platform, and load the platform with the optimal cartridge load-out.
The major contribution of this work is that it determines an optimal cartridge load-out for a platform prior to mission commencement by taking into account the strong interaction between the use of expendables and active jamming techniques over the course of an entire mission. Due to the limited cartridge capacity of a platform, these are rationed throughout the mission so as to balance the competing objectives of cost and safety, without expending these resources prematurely and leaving the platform defenceless in the latter parts of the mission. Further, this mission-level optimisation allows for the prioritisation of different overall countermeasure strategy characteristics such as cost, safety, and levels of EMCON. This is achieved while taking into account the effects of, and interactions between, different countermeasures depending on technique, relative operating frequencies and bandwidths, antenna gain patterns, and the radar cross section of the platform. The effects of radar modes and their progression, as well as threat uncertainties are also accounted for. Importantly, this is all achieved in a high-level model that is simple and computationally efficient enough to allow for the rapid solution of the problem.
