A multi-objective programming model of state estimation is proposed

which is taking the evaluation index based on the uncertainty measure and the deviation considering the normal rate of measure point as the criterion function. In order to solve this model

the multi-objective programming problem is transformed into a single objective programming problem by the objective programming method. The hyperbolic tangent rectangular pulse and the improved cohesive function are used to approximate infinite norm functions. Consequently

the model is transfered into a single objective programming problem and the objective and constraints in the model are continuous and derivable everywhere. Finally

the Lagrangian multiplier method is used to solve the model. The proposed method has the advantages of adapting to small sample estimation

high normal rate of estimating measure point

small deviation and good robust performance.