Design Of High Performance Node And Research On Self-Localization Algorithm Of Wireless Sensor Network

Along with the rapid development and the increasingly maturity of communications technology, embedded computer technology and sensor technology, the wireless network which is composed by many micro-sensor nodes with the capabilities of perception, computing and communication in MANET and multi-hop network manner has the ability to perceive, collect and process the perceptual object information in the network coverage area and send such information to observers. Wireless sensor network can be widely used in such area: national defense, national security, environmental monitoring, traffic management, health care, manufacturing, anti-terrorism and disaster relief, etc. It has a bright future for application.This thesis describes in detail the architecture issue on wireless sensor network. And aiming at the existing nodes'deficiencies in data processing, a node design schema using MCU as the main processor and FPGA as the coprocessor is brought forward. The nodes'processor module, wireless communication module, sensor module and power management module are also designed and implemented in detail. It is very suitable for the large computation and high real-time demand situation.As a fire-new technology, wireless sensor network has many challenging research topics, and location is one of them. Location is the base of mass application, location information is very important for the sensor network's monitoring activity. The distance based location algorithm has the advantage of high accuracy. This thesis firstly introduces in detail cross-correlation location algorithm and does the further study, and then improves the original cross-correlation algorithm effectively. The results show that the advanced algorithm can greatly reduce the computing time at the error premised range. According to the feature that the node design is equipped with FPGA coprocessor, a detailed schema of cross-correlation FPGA realization is put forward, and the complexity is reduces through the polarity cross-sorrelation.