Kalman Filtering With Its Application To Communication And Signal Processing

In 1960, R. E. Kalman proposed the Kalman filtering. The Kalman filter is a time domain filter, which describes the system by the state space method. It adopts the recursive form and the data memory space needed is small. It can be used not only in stationary random process but also in multidimensional and nonstationary random process. With the development and application of the electronic computer, significant attention has been paid to the Kalman filtering in the engineering practice and it has become the subject of extensive research and application due to its simple design, small memory space and dynamic real-time processing. As the most important optimal estimation theory, the Kalman filtering has been widely used in many fields, such as the communication engineering, the system engineering, the industrial process control, the remote sensing and so on. The Kalman filtering has becoming the hotspot of the current international research.Based on the basic theories of the Kalman filtering, this dissertation studies its application in communication and signal processing. The main contributions of this dissertation are as follows:Firstly, the adaptive image restoration is discussed based on the Kalman filtering and the genetic algorithm (GA). We use the GA to estimate the relationship between pixels from the observed image so as to provide the best system model for the Kalman filter. The experimental results show that this method has good properties in parameter adaptivity and the quality of the restoration image is improved.Secondly, the application of the Kalman filter in the wireless location is researched. On the one hand, the location of the mobile station is realized based on the Kalman filtering, including the single location methods and the hybrid location methods. And on the other, three methods through the modification on the standard Kalman iterative process are discussed in order to mitigate the NLOS error.In addition, some systematic research work on the optimal filtering and the navigation system is done. Firstly, a brief introduction of the GPS and the SINS is given. Secondly, the Kalman filtering is used to data processing of the GPS and the initial alignment problem for SINS on stationary base. Thirdly, the application of the Kalman filtering in the GPS/SINS integrated navigation system is also discussed. A velocity and position integrated mode Kalman filter is designed and the simulation study on the integrated navigation system is given in this paper. Finally, the application of the Kalman filtering in node location of wireless sensor networks is discussed. A general overview of the node localization of the wireless sensor network is introduced and the technique of the TDOA reconstruction based on Kalman filtering is studied.With the development of the science and technology, the theories of the Kalman filtering will be more and more perfect and the application areas will be more and more extensive.