High-precision array element localization for bottom-mounted horizontal line arrays in the deep oceana)

High-precision array element localization (AEL) is essential for bottom-mounted horizontal line arrays, as deployment uncertainties can degrade array-processing performance. In deep-ocean environments, long-range acoustic propagation and sound-speed profile variability introduce non-negligible travel-time errors in the linear propagation model (LPM), limiting localization accuracy. This study formulates the AEL problem as a simultaneous localization and mapping task within a Bayesian framework, incorporating a ray propagation model (RPM) to exploit both direct and surface-reflected acoustic paths while accounting for sound-speed profile variability. An extended Kalman filter is used to jointly estimate the array geometry, source trajectory, emission time, and sound-speed bias, while incorporating prior information and uncertainty. Simulation and experimental results show that, compared with the LPM-based approach, the RPM-based method achieves comparable horizontal localization accuracy while significantly improving vertical localization performance and source-timing estimation. Sensitivity and consistency analyses indicate robustness to sound-speed profile uncertainty. In bearing estimation, array calibration reduces the root mean square error from 4.36° to 0.29° and improved the beamforming gain by 2.1 dB, confirming its effectiveness in practical applications.