Underwater Localization based on Robust Privacy-Preserving and Intelligent Correction of Sound Velocity

The privacy-preserving localization of hydroacoustic sensor networks plays a critical role in the communication and control of marine environments. The performance of underwater location varies with constrained the complex underwater environment, such as openness, inhomogeneity, temperature, press, and so on, which make it much more challenging to ensure privacy preserving methods and obtain accurate acoustic speed used for localization computation. To address the above issues, this paper innovatively constructs Privacy-preservation Three-dimensional Underwater Location (PTUL). Firstly, the maximum distance separable coding algorithm which is designed one-time aggregated mask reconstruction by mask coding of online beacon node signals to ensure privacy-preserving and robustness is introduced into this localization model. Secondly, it relies on the sound speed modified model to compensate for the error of acoustic speed, through which an iterative regression strategy is used to deal with the change of acoustic speed. Finally, the experiments are provided to illustrate the feasibility of the proposed model. The proposed localization algorithm can efficiently improve the localization accuracy and ensure the privacy of the localization data compared with the other localization algorithms.