Synthetic Aperture Sonar (SAS) is a technique to improve the spatial resolution from a moving set of receivers by extending the array in time, increasing the effective array length and aperture. This technique is limited by the accuracy of the receiver position estimates, necessitating highly accurate, typically expensive aided-inertial navigation systems for submerged platforms. We leverage simultaneous localization and mapping to fuse acoustic and navigational measurements and obtain accurate pose estimates even without the benefit of absolute positioning for lengthy underwater missions. We demonstrate a method of formulating the well-known SAS problem in a SLAM framework, using acoustic data from hydrophones to simultaneously estimate platform and beacon position. An empirical probability distribution is computed from a conventional beamformer to correctly account for uncertainty in the acoustic measurements. The non-parametric method relieves the familiar Gaussian-only assumption currently used in the localization and mapping discipline and fits effectively into a factor graph formulation with conventional factors such as ground-truth priors and odometry. We present results from field experiments performed on the Charles River with an autonomous surface vehicle which demonstrate simultaneous localization of an unknown acoustic beacon and vehicle positioning, and provide comparison to GPS ground truths.

The underwater environment poses significant challenges for accurate autonomous underwater vehicle (AUV) navigation. Electromagnetic (EM) waves rapidly attenuate due to absorption by water, thereby preventing the use of traditional EM -based positioning methods such as Global Positioning System (GPS) or visible -light cameras. Consequently, underwater positioning is often performed using systems that operate in the hydro -acoustic frequency range (<; 10 MHz). Recent work has demonstrated the efficacy of a novel acoustic positioning approach for multi-AUV operations called passive inverted ultra -short baseline (piUSBL) localization - with each vehicle equipped with a time -synchronized USBL array, oneway travel -time (OWTT) range and angle between the AUV and a single acoustic beacon enables multi-AUV navigation relative to the beacon. In this work, a piUSBL system using a fi ve-hydrophone pyramidal array implemented on a WAM-V autonomous surface vehicle (ASV) was used to experimentally gather acoustic measurements and to compare the accuracy of piUSBL localization against ground -truth from a differential GPS unit. This paper provides a comprehensive analysis of the positioning accuracy of the system in a real -world environment, both prior to and after Bayesian fi ltering, using two independent acoustic beacons for validation. We demonstrate that piUSBL provides acoustic range and angle measurements with errors of about p, ± cr = 0.03 ± 1.49 m and p, ± cr = -0.11 ± 3.16 ° respectively. These experimental results suggest that piUSBL localization can provide a highly accurate, inexpensive, and low power navigation solution for the next generation of miniature, low-cost underwater vehicle.

Autonomous underwater vehicles (AUVs) pose significant communication challenges: vehicles are submerged for periods of time in which speed-of-light communication is impossible. This is a particular problem on low-cost AUV platforms, on which acoustic modems are not available to get vehicle state or provide re-deploy commands. We investigate one possible method of providing operators with a communication line to these vehicles by using noise underwater to both classify behavior of submerged vehicles and to command them. In this scheme, processing of data from hydrophone arrays provide operators with AUV mode estimates and AUVs with surface vehicle behavior updates. Simulation studies were used to characterize trajectories for simple transect versus loiter behaviors based on the bearing and time to intercept (TTI). A classifier based on K-nearest-neighbor with dynamic time warping as a distance metric was used to classify simulation data. The simulation-based classifier was then applied to classify bearing tracking data from passive tracking of a loitering AUV and bearing and TTI data from passive tracking of a transecting boat based on field array data. Experiment data was classified with 76 % accuracy using bearing-only data, 96% accuracy for TTI -only data and 99 % accuracy for combined classification. The techniques developed here could be used for AUV cuing by surface vessels and monitoring of AUV behavior.

Accurate localization is critical for a robotic vehicle to navigate autonomously. Conventional autonomous underwater vehicles (AUV s) typically rely on an inertial navigation system (INS) aided by a Doppler velocity log (DVL) in order to reduce the rate of positional error growth of dead-reckoning to a level suitable for reliable navigation underwater. The size, cost, and power requirements of these systems result in vehicles that are prohibitively large and expensive for multi-AUV operations. In this work we present the first results of closed-loop experiments using a miniature, low-cost SandShark AUV and a custom-designed, inexpensive acoustic system first described in our previous work. Results are validated using an independent LBL system, and indicate that our approach is suitably accurate to enable the self-localization of such AUVs without the use of an expensive DVL-aided INS. Self-localization is performed by obtaining acoustic range and angle measurements from the AUV to a single acoustic beacon using a vehicle-mounted passive hydrophone receiver-array, and fusing these measurements using a particle filter. A critical aspect of our approach that allows for real-time, closed-loop operation is the close coupling of conventional phased-array beamforming and particle filtering - this implementation detail reduces the computational complexity associated with our previously described two-stage beamforming plus particle filtering process, and consequently also enables an increase in particle count and an improvement in navigational accuracy. Experimental results are provided for two cases: first, absolute navigation in the case where the beacon is fixed at a known position; and second, relative navigation with a moving beacon, a novel operating paradigm for AUVs which promises to enable multi-AUV operations while maintaining bounded navigation error.

This paper presents an acoustic localization system for small and low-cost autonomous underwater vehicles (AUVs). Accurate and robust localization for low-cost AUVs would lower the barrier toward multi-AUV research in river and ocean environments. However, these AUVs introduce size, power, and cost constraints that prevent the use of conventional AUV sensors and acoustic positioning systems, adding great difficulty to the problem of underwater localization. Our system uses a single acoustic transmitter placed at a reference point and is acoustically passive on the AUV, reducing cost and power use, and enabling multi-AUV localization. The AUV has an ultra-short baseline (USBL) receiver array that uses one-way travel-time (OWTT) and phased-array beamforming to calculate range, azimuth, and inclination to the transmitter, providing an instantaneous estimate of the vehicle location. This estimate is fed to a particle filter and graph-based smoothing algorithm to generate a consistent AUV trajectory. We describe the complete processing pipeline of our system, and present results based on experiments using a low-cost AUV. To the authors' knowledge, this work constitutes the first practical demonstration of the feasibility of OWTT inverted USBL navigation for AUVs.

Characterization of seabed targets using networks of Autonomous Underwater Vehicles (AUVs) is of great interest for harbor security. The imaging sensors generally used for target localization and classification are expensive for outfitting multiple AUVs and produce data that is difficult to use for real-time onboard classification. An approach to this problem has been developed in which an acoustic source insonifies targets and AUVs with inexpensive hydrophone nose arrays are used to sample the resulting scattered fields. These scattered fields consist of distinctive radiation patterns, where the amplitude sampled by a receiving AUV for a particular target is determined by source frequency, aspect angle between source and target, and bistatic angle between source and receiver. AUV behaviors were developed to control the bistatic angles relative to a localized target between source and receiver vehicles and aspect angle between a target and the source. Two configurations were explored: bistatic, where the source is fixed and receiver moving, and multistatic, where both source and receiver are located on mobile autonomous vehicles. Design considerations for behaviors to sample different combinations of bistatic angle and aspect angle included keeping receiving arrays broadside to a target for uniform-quality data collection and obeying vehicle dynamics constraints. Behaviors for the bistatic configuration were demonstrated in AUV experiments, and behaviors for the multistatic case were demonstrated in simulation, including collaboration between source and receiver vehicles for controlling bistatic versus aspect angle.