cs.ROSep 23, 2026

Wave-Robust Passive AUV Localization Using FP-MUSIC

Authors: Usama Saqib, Ola Rønning, Andrzej Wąsowski

Organizations: Software Quality Research Group, IT University of Copenhagen, Denmark

Abstract

Localizing an autonomous underwater vehicle without pre-deployed seabed transponders, or direct access to onboard vehicle sensors remains a core challenge. We present a receiver-passive 3-D localization and spatial mapping system utilizing a single floating surface buoy equipped with a hydrophone array and an inertial measurement unit (IMU). The central difficulty is that surface wave motion induces six-degree-of-freedom (6-DOF) perturbations that rotate the array between snapshots, degrading conventional subspace processing. We resolve this by introducing a fixed-point iterative MUltiple SIgnal Classification algorithm (FP-MUSIC) that uses IMU measurements to de-warp snapshot covariances prior to direction-of-arrival estimation. Furthermore, we employ a subspace-projected wideband matched filter to resolve beacon ranges and use power asymmetry for independent front-back identification. Evaluations across simulated sea states demonstrate that FP-MUSIC substantially reduces localization error relative to uncompensated methods and sustains robust 3-D tracking and vehicle orientation estimation under wave-induced motion. At moderate sea state, FP-MUSIC increases the 2-m beacon-separation accuracy from approximately 45% to 75%.

Figures & tables

Explore similar work

CardsList
  1. BIND-USBL: Bounding IMU Navigation Drift using USBL in Heterogeneous ASV-AUV Teams

    Apr 13, 2026Pranav Kedia, Rajini Makam, Heiko Hamann +1Autonomous Underwater NavigationCooperative Localization

  2. Multi-AUV Marine Life Tracking with Single Hydrophone Payloads via a Hidden Markov Model Equipped Particle Filter

    Jun 21, 2026Christopher Herrera, Kehlani Fay, Christopher Clark +3Particle FilteringUnderwater Robotics

  3. Predictive Modeling in AUV Navigation: A Perspective from Kalman Filtering

    Mar 28, 2026Zizhan Tang, Yao Liu, Jessica LiuAutonomous Underwater NavigationRobot State Estimation