Target localization based on two-stage instrument variable estimator

In the target localization, reducing the estimation error which is caused by the bias is big issue. This paper addresses the instrumental variable (IV) method for decreasing the estimation error under assumption that the bias is a constant but unknown. It is proved that the proposed bias augmented IV estimator and two-stage IV estimator algorithms produce the same estimation results. In addition, the proposed two-stage IV estimator provides improved performance comparing with the two-stage Kalman estimator.