High-Precision and Practical Localization Using Seawater Movement Pattern and Filters in Underwater Wireless Networks

Localization in underwater is challenging due to harsh communication channel. Although a number of researches have proposed localization for underwater environment, they did not fully consider practical issues affecting the localization accuracy. In particular, our research focus on the unreliable reference location caused by mobility of underwater sensor nodes and unpredicted time measurement error in TDoA(Time Difference of Arrival) calculation. Unfortunately, none of related papers dealing with those factors, they significantly reduce the localization performance though. For the more accurate and practical localization, we suggest a protocol called Localization with Seawater Movement Pattern and Filter (LSMF), for underwater sensor networks. Especially, LSMF utilizes feature of seawater movement and node deployment. Also, LSMF more accurately estimates the location with iterative data processing using Kalman filter or Averaging filter. Furthermore, Adopting of INS (Inertial Navigation System) relieves localization error caused by node mobility. As a result, the localization accuracy will be improved and error propagation problem in the multi-hop networks is naturally weaken. Finally, simulation results show that LSMF reduced localization error by 44.73% compared with previous multilateration in the same simulation environment.