Fast and precise underwater transducer characterisation utilising adaptive system identification - Bastian Kaulen; Gerhard Schmidt (IET Radar, Sonar & Navigation, 2023)
Abstract Characterising underwater acoustic transducers is essential to optimal signal processing in sound navigation and ranging systems. Precise characterisation allows for equalisation of the input and output hardware, resulting in improved performance of the overall system. A critical quantity of the characterisation is the impulse response of the underwater transducers, which are usually measured in a special low‐noise water tank. An established method in other fields to estimate impulse responses of unknown systems is using adaptive filters and include an inherent quality measure. Such approaches allow for very fast and very reliable measurements. However, when using fixed control parameters, a trade‐off between convergence speed and final mismatch needs to be found, which can be eliminated using variable control parameters. In this article, a method for determining an optimal step size for adaptive algorithms based on the normalised least mean square method is derived based on a theoretical analysis of the convergence process by taking the reverberation parameters of such measurement tanks into account. The new method is specialised on the application of underwater transducer characterisation and allows a very reliable approximation of the optimal step size and thus a maximally fast adaption behaviour—leading to a very short measurement time. This is firstly shown in simulations and afterwards demonstrated in a real measurement with unknown transducers in a measurement water tank.