Structural identification of pseudorandom sequences based on using the nonlinear Kalman filter
This study has shown the relevancy of investigating new techniques for notation and processing of signals built on pseudorandom sequences (PRS) of the maximum period. For the first time an arbitrary PRS was represented in the form of a multidimensional nonlinear finite-difference structure. On the basis of the above representation it was proposed to use a nonlinear suboptimal discrete algorithm of Kalman filtration for the problem of structural identification of received PRS. A numerical example of filtration of the sequence generated in accordance with the specified recurrent rule was considered and its efficiency was also shown.
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