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Path Planning for Sound Speed Profile Estimation

Ludvig Lindström, Tadas Paskevicius, Andreas Jakobsson, Isaac Skog

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.

Path Planning for Sound Speed Profile Estimation

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.
Paper Structure (8 sections, 20 equations, 4 figures, 2 tables, 2 algorithms)

This paper contains 8 sections, 20 equations, 4 figures, 2 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Signal Model
  3. Sound Speed Profile Estimation
  4. Path Planning
  5. Efficient Prediction of State Covariance
  6. Path Constraints From AUV Motion Model
  7. Numerical examples
  8. Conclusions

Figures (4)

  • Figure 1: The studied system with an underwater transmitter and receiver at the boat and AUV, respectively. The SSP within the water volume is unknown and spatially varying (red lines).
  • Figure 2: The RRMSE versus the number of measurements.
  • Figure 3: An example of the sound speed estimated after 100 measurements using TL, CTD, as well as with CTD and TL jointly, as well as each of the selected AUV paths using the proposed scheme.
  • Figure 4: The average structural similarity index metric versus the number of measurements.