A bias-allowable estimator for continuous-time system
连续系统下的一种容偏估计策略

In an object-tracking system, the order of system model is often chosen as low as possible for reducing the computational complexity and ensuring the estimation smoothness. If the object makes a higher order maneuvering, the tracking system may lose the object. By assuming that the intensity and duration of the target maneuver are finite, we introduce the idea of bias-allowable estimation. The purpose is to find an estimator that makes the steady error coefficient as small as possible for minimizing the tracking system bias, under the constraints of regional poles and the upper bound of the error variance, along with the constraint of steady error coefficient index. The constraint index set is transformed to a set of bilinear matrix inequalities(BMIs). The expected bias-allowable estimator is obtained by iteratively solving linear matrix inequalities(LMIs) to approximate the solutions of BMIs. The proposed bias-allowable estimator ensures the accuracy and smoothness of the estimation output and guarantees the tracking system bias to be small as possible, when the target is maneuvering. Finally, a numerical example is given to illustrate the design of the bias-allowable estimation.