Higher Degree Cubature Quadrature Kalman Filter for Randomly Delayed Measurements

In this work, it has been assumed that the state estimators are located remotely and measurements are received through a common unreliable network. In such scenario, due to limited communication capacity, measurements are generally delayed in a random manner. In this correspondence, the authors developed a higher degree cubature quadrature Kalman filter (HDCQKF) for a nonlinear system with arbitrary step randomly delayed measurements. With the help of two examples, it has been shown that the randomly delayed HDCQKF provides more accurate estimation compared with randomly delayed cubature Kalman filter (CKF).