Statistical modeling of interferometric signals in underwater applications

Current sonar and radar applications use interferometry to estimate the arrival angles of backscattered signals at time-sampling rate. This direction-finding method is based on a phase-difference measurement between two close receivers. To quantify the associated bathymetric measurement quality, it is necessary to model the statistical properties of the interferometric-phase estimator. Thus, this paper investigates the received signal structure, decomposing it into three different terms: a part correlated on the two receivers, an uncorrelated part and an ambient noise term. This paper shows that the uncorrelated part and the noise term can be merged into a unique, random term damaging the measurement performance. Concerning the correlated part, its modulus can be modeled either as a random or a constant variable according to the type of underwater acoustic application. The existence of these two statistical behaviors is verified on real data collected from different underwater scenarios such as a horizontal emitter-receiver communication and a bathymetric seafloor survey. The physical understood of the resulting phase distributions makes it possible to model and simulate the interferometric-signal variance (associated with the measurement accuracy) according to the underwater applications through simple hypotheses.