Nonlinear filtering for a new nimble jammer

In this paper nonlinear filtering results of an underwater jammer application are presented. These results have been obtained after a previous theoretical study on nonlinear identification. The main results presented on real underwater acoustical jammer signals are: (1) a Volterra model is not rich enough for identification of the jammer system, (2) the NARMAX model with an OLS algorithm identification, gives satisfactory results for detection and estimation of the unknown tone SOI, (3) better results (estimation and detection) are obtained with a BPSK sequence in comparison with a RMS sequence usually used for nonlinear identification.