**:** ..
**:**
**:** 99
**:**
**:** 2022
**:** .. // . 99. .: , 2022. .36-56. DOI: https://doi.org/10.25728/ubs.2022.99.2

** :** , , ,

** (.):** anisotropy-based theory, sensors network, multiplicative noise system, estimation

**:** , , . , . , , , , , -- , . . , , , .

** (.):** In this paper, the linear discrete time-varying system of sensors network is considered. Each sensor has appropriate dropout probability with Bernoulli distribution. The dropout occurs if measurement output contains only noise term. The external disturbance belongs to sequences of random vectors with bounded anisotropy of extended vector. The estimation model of the system is given, for the model an adjacency matrix set up is suggested based on anisotropic criterion. The input-to-estimation error system is derived, it has the multiplicative noise system form. The estimation problem is reduced to convex optimization one. The suggested method of optimization is based on applying bounded real lemma with anisotropic norm boundedness sufficient condition. The solution of considered problem allows to decrease anisotropic norm of the input-to-estimation error system, it yields to better performance in estimation problem.

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