Title | Multi-function radar emitter modelling: a stochastic discrete event system approach |
Publication Type | Conference Paper |
Year of Publication | 2003 |
Authors | Visnevski, N., V. Krishnamurthy, S. Haykin, B. Currie, F. Dilkes, and P. Lavoie |
Conference Name | Decision and Control, 2003. Proceedings. 42nd IEEE Conference on |
Pagination | 6295 - 6300 Vol.6 |
Date Published | dec. |
Keywords | decoding, discrete event systems, discrete time filters, discrete-time hidden Markov filter, electronic warfare, hidden Markov models, military radar, multifunction radar emitter modelling, radar transmitters, semiMarkov processes, state estimation, stochastic discrete event system |
Abstract | We consider the electronic warfare problem of decoding the internal state of a multi-function radar at a given time, when provided with incomplete observations of the radar emissions and some prior knowledge of how the radar functions. The internal state of multi-function radar can provide an indication of where it stands in its target acquisition process and in how much time a weapon can be triggered. Therefore, estimation of the internal state of the radar is useful to assess how much of a threat it constitutes. In this paper a mathematical framework to model how radars function is proposed. This framework is based on the concept of generalized semi-Markov processes. In the case of radars structuring their emissions around a clock, this model reduces to a Markov-modulated Markov process. In the latter case, the problem of decoding the internal state of the radar given incomplete observations can be solved by using a discrete-time hidden Markov filter. The practicality of the proposed approach is discussed and illustrated by means of a hypothetical multifunction radar example. |
URL | http://dx.doi.org/10.1109/CDC.2003.1272306 |
DOI | 10.1109/CDC.2003.1272306 |