Robust recursive filter for multi-sensor nonlinear stochastic system with random uncertainties and missing measurements

This paper is concerned with the robust recursive filtering problem for multi-sensor nonlinear stochastic system with random uncertainties and missing measurements. The phenomenon of random uncertainties or multiplicative noises is included in the system model, measurement model and the filter parameters. The missing measurements of multi-sensor are assumed to be independent of each other with different sensor failure rates. Then, a robust recursive filter is designed in the minimum-variance sense at each sampling instant against the random uncertainties and missing measurements. A simulation example is employed to demonstrate the effectiveness of the proposed method.