Object identification by bistatic acoustic scattering

An inversion technique is described for remote estimation of parameters of submerged or buried objects using a ROV-mounted directive acoustic source and a separately located vertical receiver array. The transmitter emits a train of pulses towards the object, and the scattered echoes are recorded at the receivers for subsequent parameter estimation. Parameters of the object are estimated by nonlinear global minimization of the misfit between the experimentally observed and model-predicted time-series. Two global minimization methods, a genetic algorithm (GA) and a differential evolution algorithm (DE), are considered. A fast approximative technique for computing the scattered field, the RK (Ray-Kirchoff) method, is described and used as forward model at the parameter search. The accuracy of the transient scattered field predicted by the RK method is assessed in a model case, using an accurate full-field boundary integral equation (BIE) method as reference. Experimental data are presented from a sea trial within the EU SITAR project in the Stockholm archipelago in September 2003. In the trial, a semi-buried box-shaped object was investigated using a ROV-mounted TOPAS 120 parametric sonar as source. A fitness function suitable for the characteristics of the experimental data and the accuracy properties of the RK method is formulated, and the inversion methods are applied on the data to estimate, in a step-wise manner, seven physical parameters of the object; range, depth, roll, yaw, pitch, density and soundspeed. The estimated parameter values are shown to reduce the model-data misfit significantly compared with those based on prior information only.