default Results of environmentally-conditioned network node range estimation algorithm integration tests in CASW project 1 experimental campaign

By In Memorandum Reports

Results of environmentally-conditioned network node range estimation algorithm integration tests in CASW project 1 experimental campaign. Fabbri, Tommaso ;  Ferri,  Gabriele ;  Vicen-Bueno, Raul ; Tesei, Alessandra. CMRE-MR-2019-026. March 2020.

The research activities covered by this memorandum report (MR) investigate how robot navigation strategies can improve the communication performance among the nodes of a deployed underwater autonomous network (UAN). To this aim, an algorithm that evaluates the impact of environmental conditions and network configurations on the connectivity performance of the UAN, is presented. More precisely the algorithm exploits acoustic propagation models, such as Bellhop, and data from experimental campaigns for the definition of the communication performance function (CPF). The CPF estimates the probability of successful packet delivery by correlating the environmental conditions and the data produced by acoustic propagation models with past communication data. Once created the CPF can be used by a robot during its missions to adapt its navigation and achieve the desired communication performance with the other nodes of an UAN. Granting a proper level of communication performance is crucial during any underwater mission performed by an UAN. Reliable communications increase the overall capability of the UAN with improved situational awareness for cooperative decision-making, and the navigation performance. In this MR, the environmental and communication data from the littoral continuous active sonar (LCAS18) trial are analyzed for the definition and tuning o f t he CPF. Finally, the resulting CPF shows its coherence with the training data extrapolated from LCAS18 dataset. This research activity has been conducted by the cooperative anti-submarine warfare (CASW) and the environmental knowledge operational effectiveness (EKOE) programmes.