UKF-based nonlinear filtering over sensor networks with wireless fading channel

Stochastic stability of UKF-based nonlinear filter for general nonlinear system over a wireless sensor network with fading channel is studied. In the process of signal transmission, sensor data may be fluctuant or even dropout due to fading channel. By considering signal fluctuation and transmission failure simultaneously, we establish sufficient conditions of statistical convergence property that ensure the stability of the unscented Kalman filter. It is shown that the mean error covariance with respect to fading process is bounded and converges to a steady state value. Moreover, for scalar measurement and Rayleigh fading channel, "explicit expressions" for sequences which can be used as upper bounds on the expected error covariance will be got. Numerical examples are given to illustrate the effectiveness of the developed techniques.

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