Wireless sensor network is composed of many sensor nodes which arranged by random. Each node has the capacity of environmental sensing, data processing capability, communications capability, as well as the signal self-organizing capacity of the network. Wireless sensor network technology known as the 21 most important emerging technologies, has been widely used in many occasions, such as military applications, the industrial production of security and counter-terrorism, the environment and monitoring of residential areas.In this paper, We use periodogram and AR-Burg maximum entropy power spectrum estimation method for spectral feature extraction, and use support vector machines for accurate classification of the types of vehicles. The experimental results show that The result shows that, under a certain classification precision premise, low compute complexity less generated-data volume can be obtained by the method of this paper.
