On the basis of the extended Kalman Filter(EKF) and the decaying extended Kalman Filter,this paper makes use of the modified strong tracking filter(STF) to estimate the maneuvering target information without all measurement information.

A new tracking filter was proposed for the highly non-linear single observer passive location and tracking(SOPLAT)system,where the common tracking filters often failed to catch and kept tracking of the emitter.

But to the CW pulse signal with changing frequency, it is difficulte to realize tracking filter with common narrowband filter.

Based on the basic principle of data processing of Phased Array Radar,this paper presents the simulation structure of the data processing system of a Space Surveillance Phased Array(SSPA) radar and its key algorithms such as data association and track filter.

Identification of non-linear system parameters based on strong tracking filter;

Vehicle nonlinear state estimation based on strong tracking filter

This dissertation puts forward a method of designing the suboptimal strong tracking filter, which is based on the approximation error upper bound of nonlinear separation model and applied to design feedback corrected controller in predictive control.

In this paper,the theory of Strong tracking filtering(STF) is applied in the object prediction of autonomous robots to avoid the disadvantages of other methods by introducing fading factors.

This research paper employs the Kalman filtering and the strong tracking filtering in the optimal estimation theory to dynamically estimate Chinese listed companies permanent earnings,which are critical for stock market investment decision.