Joint time synchronization and tracking for mobile underwater systems

Abstract

Time synchronization and localization are key requirements for distributed underwater systems consisting of numerous low-cost submersibles. In these systems, submersibles are highly resource constrained and typically have limited acoustic communication capability. We investigate the problem of time synchronization and tracking for submersibles that only have the capability to receive acoustic signals. Traditional Long Base Line (LBL) systems track the location of submersibles by providing a GPSlike infrastructure that consists of a few reference beacons at known locations. In these systems the unknown positions of submersibles are estimated from beacon transmissions using timedifference-of-arrival (TDoA) based localization. As such TDoA makes the key assumption that beacon transmissions occur nearly concurrently in time. While this assumption is ensured in small LBL deployments it does not hold as the size of the system scales up. In this paper we identify scenarios where signals from multiple beacons are significantly lagged in time. We further identify the motion of the submersible between signal arrivals as a key factor that deteriorates the performance of TDoA, when transmissions are not concurrent. To address this problem we propose to track the submersible while performing timesynchronization. Our proposed technique, called Time of Arrival based Tracked Synchronization (ToA-TS) essentially extends GPS like localization for scenarios where beacon transmissions are not concurrent and submersibles are not capable of two-way communication.

ToA-TS: Time of arrival based joint time synchronization and tracking for mobile underwater systems

“…In addition to the results provided in this section, we have provided extensive simulation results in the conference version of the paper [2]. In this section we validated of our proposed technique with experimental data to further support our evaluatios in simulation.…”

“…In this paper we extend on our previous work in [2], where we proposed a joint approach to time synchronization and localization using the framework of factor-graphs. In particular, we improve the run-time of our original factorgraph based algorithm by bootstrapping from an analytically obtained initial solution.…”

A TDoA Localization Scheme for Underwater Sensor Networks with Use of Multilinear Chirp Signals

“…In [9], a different system where transmissions from multiple reference nodes have to be sufficiently lagged over a time epoch to avoid collisions was presented, but it needs a lot of time to localize the target sensor. In [10], the authors introduced a method for designing localization signal based on Code Division Multiple Access (CDMA), and the modulation mode is ASK; but as described in [11] about the physical layer of underwater channel, ASK modulation is not suitable for underwater channel because of high attenuation.…”

“…In [10], the authors introduced a method for designing localization signal based on Code Division Multiple Access (CDMA), and the modulation mode is ASK; but as described in [11] about the physical layer of underwater channel, ASK modulation is not suitable for underwater channel because of high attenuation. What is more, the location signals are transmitted that are sufficiently lagged, which is the same as [9]. In [8], to avoid collisions and meet the signal concurrency requirement of traditional LBL systems simultaneously, a TDoA location scheme for the orthogonal frequency division multiplexing (OFDM) was presented; this outperforms the location schemes with traditional TDoA estimations.…”

Combined UAMP and MF Message Passing Algorithm for Multi-Target Wideband DOA Estimation with Dirichlet Process Prior

“…In this paper, we address the challenges of representing the Bayesian model for wideband DOA estimation by introducing the factor graph approach, which offers a more effective representation compared to the Bayesian network model [48,49] . We recognize that the complexity arises from the direct relationship between the received signals and the DP prior in the probability model.…”