Resolution improvement of dipole source localization for artificial lateral lines based on multiple signal classification

The lateral line is a critical mechanosensory organ that enables fish to perceive the surroundings accurately and rapidly. Massive efforts have been made to build an artificial lateral line system rivaling that of fish for underwater vehicles. Dipole source localization has become a standard problem for evaluating the sensing capabilities of the developed systems. In this paper we propose, for the first time, the multiple signal classification (MUSIC) method in order to achieve high-resolution dipole source localization based on spatial spectrum estimation. We also present the minimum variance distortionless response (MVDR) by making an improvement to the previous Capon's method. Experiments are conducted on a linear prototype of lateral line canal and the localization performance of these two methods are compared. The results show that the MUSIC method provides an overall localization resolution improvement of 10.4% and maintains a similar level of localization accuracy compared with the MVDR method. Further studies show that the MUSIC method has the potential of localizing two closer incoherent dipole sources with a minimum lateral separation of 20 mm, versus 70 mm for the MVDR method, at a dipole-array distance of half the array length. Both localization methods have strong robustness to the vibrational state of the dipole source. Our work provides a promising and robust way to meet the high-resolution and multi-source sensing requirements of underwater vehicles.