Path Planning for Sound Speed Profile Estimation

TL;DR

This paper presents a method for underwater sound speed profile estimation using an AUV with sensor fusion and path planning, improving accuracy and reducing uncertainty in SSP reconstruction.

Contribution

It introduces a joint estimation approach combining CTD and TL measurements with a receding-horizon path planning scheme for enhanced SSP estimation.

Findings

CTD measurements accurately estimate local SSP variations.

TL measurements effectively capture global SSP characteristics.

Path planning reduces estimation uncertainty compared to constant-velocity motion.

Abstract

Accurate estimation of the sound speed profile (SSP) is essential for underwater acoustic communication, sonar performance, and navigation, as the acoustic wave propagation depends strongly on the SSP. This work considers SSP estimation in a region of interest using an autonomous underwater vehicle (AUV) equipped with a conductivity-temperature-depth (CTD) sensor and an acoustic receiver measuring transmission loss (TL) from a sonar transmitter. The SSP is modeled using a linear basis-function expansion and is sequentially estimated with an unscented Kalman filter that fuses local CTD measurements with TL measurements. A receding-horizon path planning scheme is also employed to select future AUV positions by minimizing the predicted total sound speed variance. Simulations using the Bellhop acoustic wave propagation solver show that CTD measurements provide accurate local SSP estimates, whereas TL measurements are seen to capture the global characteristics of the SSP, with their joint use improving the reconstruction of both local variations and large-scale SSP behavior. The results also indicate that the proposed path planning strategy reduces the estimation uncertainty compared to constant-velocity motion, thereby enabling improved environmental characterization for underwater acoustic systems.