Deterministic sampling filters, including Unscented Kalman filter(UKF), central difference Kalman filter(CDKF)
and cubature Kalman filter(CKF), are a class of nonlinear suboptimal Gaussian filtering algorithms based on deterministic
and analytical sampling approximation, which have advantages of high precision and simple implementation, and have been
received wide attention from scholars. The basic principle of deterministic sampling filter is described, and its research
situation is summarized in detail, including various improved methods and applications in different areas. Then the problems
of deterministic sampling filter at present are analyzed and presented. Finally, its development tendency and research
orientation are prospected.