Application of Transformed Cubature Quadrature Information Filtering in Distributed POS

For aerial earth observation system, the accuracy of motion parameters provided by airborne distributed position and orientation system (POS) is crucial to the observation load imaging quality. According to the working principle, slave systems of distributed POS rely on the master node information to realize error estimation and correction, and then to achieve multiple node high accuracy measurement. Due to the nonlinearity of the error model, nonlinear filtering algorithm is used to the estimation process. Then in order to achieve higher estimation performance, a transformed cubature quadrature information filtering algorithm is developed for distributed POS estimation. In this method, the contributions are located that: (1) spherical radial cubature rule and Gauss-Laguerre quadrature rule are used to generate sigma points; (2) orthogonal transformation is conducted on the sampling points to deal with nonlocal sampling; (3) information filtering framework is adopted to simplify filtering update process, then the algorithm is applied in distributed POS nonlinear transfer alignment estimation. By the flight test validation, the outcomes are found that the developed algorithm can enhance the distributed POS estimation accuracy effectively, including attitude, velocity, position accuracy, then can be used to loads imaging quality improvement.