arXiv subjects

Junsu Jang

Publications and source records attributed to Junsu Jang.

6 recordsLinked to original sources

arXiv2025

Statistical Model and Estimation Method for Ranging a Moving Ship Using a Single Acoustic Receiver in Shallow Water

Passive acoustics is a versatile tool for maritime situational awareness, enabling applications such as source detection and localization, marine mammal tracking, and geoacoustic inversion. This study focuses on estimating the range between an acoustic receiver and a transiting ship in an acoustically range-independent shallow water environment. Here, acoustic propagation can be modeled by a set of modes that are determined by the shallow water waveguide and seabed characteristics. These modes are dispersive, with phase and group velocities varying with frequency, and their interference produces striation patterns that depend on range and frequency in single-hydrophone spectrograms. These striation patterns can often be characterized by the waveguide invariant (WI), a single parameter describing the waveguide's properties. This paper presents a statistical model and corresponding WI-based range estimation approach using a single hydrophone, leveraging broadband and tonal sounds from a transiting ship. Using data from the Seabed Characterization Experiment 2017 (SBCEX17), the method was evaluated on two commercial ships under different environmental conditions and frequency bands. Range estimation errors remained below 4 % up to 62 km in the best case, with robust performance demonstrated in the 40-60 Hz band.

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arXiv2025

A Landmark-Aided Navigation Approach Using Side-Scan Sonar

Cost-effective localization methods for Autonomous Underwater Vehicle (AUV) navigation are key for ocean monitoring and data collection at high resolution in time and space. Algorithmic solutions suitable for real-time processing that handle nonlinear measurement models and different forms of measurement uncertainty will accelerate the development of field-ready technology. This paper details a Bayesian estimation method for landmark-aided navigation using a Side-scan Sonar (SSS) sensor. The method bounds navigation filter error in the GPS-denied undersea environment and captures the highly nonlinear nature of slant range measurements while remaining computationally tractable. Combining a novel measurement model with the chosen statistical framework facilitates the efficient use of SSS data and, in the future, could be used in real time. The proposed filter has two primary steps: a prediction step using an unscented transform and an update step utilizing particles. The update step performs probabilistic association of sonar detections with known landmarks. We evaluate algorithm performance and tractability using synthetic data and real data collected field experiments. Field experiments were performed using two different marine robotic platforms with two different SSS and at two different sites. Finally, we discuss the computational requirements of the proposed method and how it extends to real-time applications.

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arXiv2024

A New Statistical Model for Waveguide Invariant-Based Range Estimation in Shallow Water

Navigation and source localization in the undersea environment are challenged by the absence of a ubiquitous positioning system. Passive acoustic ranging offers a valuable means of obtaining location information underwater. We present a range estimation method based on waveguide invariant (WI) theory, using ship noise recorded by a hydrophone as an acoustic source. The WI is a scalar parameter that describes the interference patterns in spectrograms caused by the interaction of acoustic wave modes propagating in a waveguide, such as shallow water. WI theory enables ranging using a single receiver without detailed knowledge of the environment. In this paper, underwater acoustic signals radiated by a moving large ship, which include broadband and tonal components, are employed for WI-based ranging in a range-independent shallow water environment. In particular, we develop a likelihood function for WI-based range estimation by introducing a statistical model for high signal-to-noise ratio scenarios. Here, the broadband component is assumed to dominate the background noise. The effectiveness of the proposed range estimation method is demonstrated using real acoustic measurements of a moving container ship recorded during the Seabed Characterization Experiment 2017 (SBCEX17).

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arXiv2023

Toward Terrain-based Navigation Using Side-scan Sonar

This paper introduces a statistical model and corresponding sequential Bayesian estimation method for terrain-based navigation using side-scan sonar (SSS) data. The presented approach relies on slant range measurements extracted from the received ping of a SSS. In particular, incorporating slant range measurements to landmarks for navigation constrains the location and altitude error of an autonomous platform in GPS-denied environments. The proposed navigation filter consists of a prediction step based on the unscented transform and an update step that relies on particle filtering. The SSS measurement model aims to capture the highly nonlinear nature of SSS data while maintaining reasonable computational requirements in the particle-based update step. For our numerical results, we assume a scenario with a surface vehicle that performs SSS and compass measurements. The simulated scenario is consistent with our current hardware platform. We also discuss how the proposed method can be extended to autonomous underwater vehicles (AUVs) in a straightforward way and why the combination of SSS sensor and compass is particularly suitable for small autonomous platforms.

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arXiv2023

Navigation in shallow water using passive acoustic ranging

Passive acoustics can provide a variety of capabilities with applications in oceanographic research and maritime situational awareness. In this paper, we develop a method for the navigation of autonomous underwater vehicles (AUVs) in shallow water. Our approach relies on passively recorded signals from acoustic sources of opportunities (SOOs). By making use of the waveguide invariant, a measurement of the range to the SOO is extracted from the spectrogram of a single hydrophone. Range extraction requires knowledge of the range rate, i.e., the radial velocity between the SOO and AUV, computed from the pressure fields at different time intervals. A particle-based navigation filter fuses the range measurements with the AUV's internal velocity and heading measurements. As a result, the position error, which would otherwise increase over time, can be bounded. The ability to compute the range rate and range measurements from the pressure field measured using a single hydrophone is demonstrated on real data from the SWellEx-96 experiment. The capability of the developed navigation filter is shown based on synthetic data generated by the normal mode program KRAKEN.

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arXiv2022

Bayesian Detection and Tracking of Odontocetes in 3-D from Their Echolocation Clicks

Localizing and tracking of marine mammals can reveal key insights into behaviors underwater that otherwise would remain unexplored. A promising nonintrusive approach to obtaining location information of marine mammals is based on recordings of bio-acoustic signals by volumetric hydrophone arrays. Time-difference-of-arrival (TDOA) measurements of echolocation clicks emitted by odontocetes can be extracted and used for detection, localization, and tracking in 3-D. We propose a data processing chain that automatically detects and tracks multiple odontocetes in 3-D from their echolocation clicks. First, TDOA measurements are extracted with a generalized cross-correlation that whitens received acoustic signals based on instrument noise statistics. Subsequently, odontocetes are tracked in the TDOA domain using a graph-based multi-target tracking (MTT) method to reject false TDOA measurements and close gaps of missed detections. The resulting TDOA estimates are then used by another graph-based MTT stage that estimates odontocete tracks in 3-D. The tracking capability of the proposed data processing chain is demonstrated on real acoustic data provided by two volumetric hydrophone arrays that recorded echolocation clicks from Cuvier's beaked whales (Ziphius cavirostris). Simulation results show that the presented 3-D MTT method can outperform an existing approach that relies on hand annotation.

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