Performance evaluation and analysis for dipole source localization with lateral line sensor arrays

Abstract

The unique mechanosensory lateral line system of fish inspires a novel and promising sensing scheme in dealing with the challenges that autonomous underwater vehicles (AUVs) face in underwater localization and navigation. In this paper, the quantitative and method-independent Cramer–Rao lower bound (CRLB) model is established to evaluate the practical performance of a lateral line sensor array (LLSA) for dipole source localization by considering the excitation pattern mismatches and the measurement noises. The effective localization area of the LLSA is studied under varying array lengths and sensor densities. Localizations for the LS (least squares) method and the MUSIC (multiple signal classification) method are compared in simulations. It is shown that the longer and denser the LLSA, the larger the effective localization area. Typically, the too separated sensor-to-sensor spacing deteriorates the near-body localization performance. The effective localization area obtained by employing the LS method matches the CRLB analysis, which also proves the validity of the analytical CRLB model. Besides, the MUSIC method presents smaller effective localization areas than the LS method. Physical experiments are also conducted and agree well with the CRLB analysis. Further study shows that the measurement noises have an equivalent effect on the excitation pattern mismatches, and can be effectively suppressed by choosing a large number of snapshots. In addition, the CRLB gives the perceptual distance that is consistent with the observation. At last, guidance on the design of a simplified LLSA with the least number of sensors and an optimal sensor-to-sensor spacing is provided for AUVs.