A Nonlinear Transfer Alignment of Distributed POS Based on Adaptive Second-Order Divided Difference Filter

Distributed position and orientation system (POS) uses transfer alignment to accurately measure multi-node time-spatial reference information, which is urgently demanded to compensate motion error of imaging sensors for aerial survey. The lever-arm deformation in transfer alignment will result in nonlinear error and time-varying measurement noise covariance, which decreases the accuracy of real-time estimation. In order to solve this problem, a nonlinear transfer alignment method of distributed POS based on an adaptive second-order divided difference filter (ADDF2) is proposed. First, a transfer alignment model for distributed POS is established. Furthermore, an ADDF2 based on adaptive innovation estimation is proposed to solve the nonlinear problem and adaptively adjust the measurement noise covariance matrix of transfer alignment in real time. The flight experiment results show that the proposed method is effective to improve the precision of distributed POS.