| Target tracking based on Underwater Sensor Networks which integrates the technologies like target detection, localization and tracking, and underwater acoustic communication, has become one of the most significant applications of the underwater distributed sensor network. In this paper, we propose an underwater target tracking technology that utilizes the energy localization method and Bayesian filter tracking algorithm. The details of our work could be summarized as:1. An underwater acoustic attenuation model is derived to match the acoustic propagation of the shallow water environment in Zhoushan. We set up a simulation environment where a distributed sensor network is built on the sea floor with a moving source in a constant depth. A 100-1000Hz broadband signal is transmitted to obtain the acoustic attenuation pattern.2. Once the signal is received, the node starts an energy detection process. The detail processing methods are as followed. Firstly, the random Gauss signal buried in Gauss white noise is detected, where signal and noise are modeled as Gauss process. Then, the test statistics for likelihood ratio method is derived and the performance is analyzed. Further, a counting detector is added after the energy ratio detector to form a dual-threshold energy detector, which helps to reduce the false alarm probability.3. After sampling the acoustic signal in each node to build the energy-ratio data, the localization of an underwater moving target could be realized with the least-square method. Other factors which may influence the localization accuracy are discussed in simulation, such as the number of sensors in the network, deployed environment and energy ration to the location.4. We derive the nonlinear observation equations with the energy-ratio data as observations, and build a state-space model after linearizing the observation equations. Finally, a better localization result is achieved using Extended Kalman Filter to the tracking of moving objects with uniform velocity. |
PDF Full Text Request