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Arta process model of maritime clutter and targets

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dc.contributor.author McDonald, Andre M
dc.contributor.author Cilliers, Jacques E
dc.date.accessioned 2013-06-18T11:05:12Z
dc.date.available 2013-06-18T11:05:12Z
dc.date.issued 2012-10
dc.identifier.citation McDonald, A and Cilliers, J. 2012. Arta process model of maritime clutter and targets. In: IET Radar 2012, International conference on radar systems, Glasgow, United Kingdom, 22-25 October 2012 en_US
dc.identifier.uri http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6494827
dc.identifier.uri http://hdl.handle.net/10204/6802
dc.description IET Radar 2012, International conference on radar systems, Glasgow, United Kingdom, 22-25 October 2012. Published in IEEE Xplore en_US
dc.description.abstract A coherent autoregressive–to–anything (ARTA) stationary stochastic process for modelling maritime clutter and targets is presented in this paper. The ARTA stochastic process model is an improvement over previous models in the sense that it is complex–valued, has a magnitude with an arbitrary, nonnegative distribution and an arbitrary autocorrelation function. A rapidly converging algorithm for finding appropriate filter coefficients to realize a specified autocorrelation function is presented. The validity and practicality of the ARTA process model is demonstrated by deriving models for a maritime target and for sea clutter, both from measurements and without any prior assumption regarding the distribution of measurements. This ability to generate additional data samples with the same statistics as a set of measurements is a prerequisite for the verification of system specifications in situations where only a few data measurements are available for each mode of operation and / or environmental condition. en_US
dc.language.iso en en_US
dc.publisher IEEE Xplore en_US
dc.relation.ispartofseries Workflow;10820
dc.subject Autoregressive–to–anything en_US
dc.subject ARTA en_US
dc.subject Monte–Carlo en_US
dc.subject Autoregressive en_US
dc.subject Simulation en_US
dc.title Arta process model of maritime clutter and targets en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation McDonald, A., & Cilliers, J. E. (2012). Arta process model of maritime clutter and targets. IEEE Xplore. http://hdl.handle.net/10204/6802 en_ZA
dc.identifier.chicagocitation McDonald, A, and Jacques E Cilliers. "Arta process model of maritime clutter and targets." (2012): http://hdl.handle.net/10204/6802 en_ZA
dc.identifier.vancouvercitation McDonald A, Cilliers JE, Arta process model of maritime clutter and targets; IEEE Xplore; 2012. http://hdl.handle.net/10204/6802 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - McDonald, A AU - Cilliers, Jacques E AB - A coherent autoregressive–to–anything (ARTA) stationary stochastic process for modelling maritime clutter and targets is presented in this paper. The ARTA stochastic process model is an improvement over previous models in the sense that it is complex–valued, has a magnitude with an arbitrary, nonnegative distribution and an arbitrary autocorrelation function. A rapidly converging algorithm for finding appropriate filter coefficients to realize a specified autocorrelation function is presented. The validity and practicality of the ARTA process model is demonstrated by deriving models for a maritime target and for sea clutter, both from measurements and without any prior assumption regarding the distribution of measurements. This ability to generate additional data samples with the same statistics as a set of measurements is a prerequisite for the verification of system specifications in situations where only a few data measurements are available for each mode of operation and / or environmental condition. DA - 2012-10 DB - ResearchSpace DP - CSIR KW - Autoregressive–to–anything KW - ARTA KW - Monte–Carlo KW - Autoregressive KW - Simulation LK - https://researchspace.csir.co.za PY - 2012 T1 - Arta process model of maritime clutter and targets TI - Arta process model of maritime clutter and targets UR - http://hdl.handle.net/10204/6802 ER - en_ZA


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