Development Of Netwoked Multi-Sensor System And Research On Information Fusion Algorithm

With the development and popularity of Internet, wired or wireless sensor network technology based on the Internet has becomed an important means of romote monitoring and control in industrial and domestic field. The existing RS232/RS485 protocol and industrial field bus for the main transmission of multisensor system cannot satisfy modern industrial monitoring and control requirements.At present,the demond for the technology of multi-sensor network based on Internet for monitoring and control shows an upword trend.Therefore the research and development of the technology of multi-sensor network based on Internet for monitoring and control is urgent.Secondly,for the purpose of easing the load of network, it is necessary to intergrate the multi-sensor data before making the network transmission for a complex multi-sensor system.For vehicle tracking system based on mutli-sensor system,the traditional methord of information fusion is Kalman filter.But for more complex systems, the computation of Kalman filter will increase exponentially with the increase of the dimention of state variables.Based on the discussion of above, this project provides the corresponding solutions. This project includes the following:(1) The embedded Internet implementations are learned and the method of'microprocessor plus Ethernet controller'is choosed.This project relized the design of Data conversion board in which ATmeaga128 is the control core and RTL8019AS is the Ethernet controller.Learned and compared some popular Embedded operating systems and choosed NUT/OS operating system as the Development Platform.Developed the data conversion programs which meet the engineering requriements based on the operating system. Users can use this system to achieve on-site monitoring through Internet.(2) For a complex multi-sensor system, in order to ease the load on the network system,it is necessary to make data fusion.The centralized Kalman Filter(CKF) algorithm can result in a high computional load and a low levelel of fault-tolerance.We do some research on Federal Kalman Filter(FKF) algorithm which can used to integrate the information from multi-sensor systmes.The Federal Kalman Filter(FKF) algorithm is used on the model of INS/GPS/SS intergrated navigation sysytem to integrate the data from this three different sensors.Finally,some simulatios are done to prove that the Federal Kalman Filter(FKF) algorithm is effective.(3) Secondly, the computional burden increase sharply when Federal Kalman Filter(FKF) algorithm is used to deal with high-dimentional state variables in loacl filters.So we propose using an EM algorithm to improve Federal Kalman Filter(FKF) algorithm performance.More precisely,the common states of local filters are estimated in the E-step.The own unique sensor bias states of local filters are updated in the M-step and the M-step is performed with the fusion of common states in the master filter simultaneously.Finally,some simulatios are done to prove that the computational burden is reduced.