Precise Time Delay Measurement and Compensation for Tightly Coupled Underwater SINS/piUSBL Navigation
Jin Huang, Yingqiang Wang, Haoda Li, Zichen Liu, Zhikun Wang, Ying Chen
TL;DR
This work tackles time synchronization challenges in underwater navigation by proposing a tightly coupled SINS/piUSBL/depth gauge framework that uses precise time-delay measurement to explicitly estimate acoustic propagation and processing delays. The method leverages synchronized OCXO clocks to align transmission, reception, and processing timestamps, converting the delay into estimable parameters within a 21-dimensional state that fuses slant range $r$, azimuth $\alpha$, and depth $h^n$ through carefully derived Jacobians. Both simulations and field experiments demonstrate substantial performance gains: RMSE and MAXERR are markedly reduced when delay compensation is applied, with field results showing a 40.45% improvement in RMSE and a 32.55% improvement in MAXERR. The work offers a generalizable delay-aware framework for integrating acoustic positioning with inertial navigation, paving the way for robust, low-latency underwater multi-sensor fusion in GNSS-denied environments.
Abstract
In multi-sensor systems, time synchronization between sensors is a significant challenge, and this issue is particularly pronounced in underwater integrated navigation systems incorporating acoustic positioning. Such systems are highly susceptible to time delay, which can significantly degrade accuracy when measurement and fusion moments are misaligned. To address this challenge, this paper introduces a tightly coupled navigation framework that integrates a passive inverted ultra-short baseline (piUSBL) acoustic positioning system, a strapdown inertial navigation system (SINS), and a depth gauge under precise time synchronization. The framework fuses azimuth and slant range from the piUSBL with depth data, thereby avoiding poor vertical-angle observability in planar arrays. A novel delay measurement strategy is introduced, combining synchronized timing with acoustic signal processing, which redefines delay-traditionally an unobservable error-into a quantifiable parameter, enabling explicit estimation of both acoustic propagation and system processing delays. Simulations and field experiments confirm the feasibility of the proposed method, with delay-compensated navigation reducing RMSE by 40.45% and maximum error by 32.55%. These findings show that precise delay measurement and compensation not only enhance underwater navigation accuracy but also establish a generalizable framework for acoustic positioning integration, offering valuable insights into time alignment and data fusion in latency-sensitive multi-sensor systems.