Model-based 3D micro-navigation and bathymetry estimation for interferometric synthetic aperture sonar

Sub-wavelength navigation information is vital for the formation of all synthetic aperture sonar (SAS) data products. This challenging requirement can be achieved using the redundant phase centre (RPC) or displaced phase centre antenna (DPCA) micro-navigation algorithm, which uses cross-correlation of signals with inter-ping coherence to estimate time delays and hence make navigation estimates. In this paper a new approach to micro- navigation for interferometric synthetic aperture sonar is introduced. The algorithm makes 3D vehicle position estimates for each sonar ping by making use of time delays measured between all possible pairs of redundant phase centre arrays, using both interferometric arrays on each side of the vehicle. Simultaneous estimation of coarse bathymetry allows the SAS images to be projected onto ground-range. The method is based on non-linear minimization of the difference in modelled and measured time delays and surges between redundant phase centre arrays. The approach is demonstrated using data collected by the CMRE MUSCLE AUV using its 270-330 kHz SAS during the MANEX’14 experiment. SAS images have been projected onto the coarsely estimated bathymetry, and interferograms have been formed. The coarse bathymetry estimate and vehicle navigation estimate are validated by the quality of the image focussing and the near-zero phase of the interferogram. The method has the potential to improve through-the-sensor navigation aiding and to increase the accuracy of single-pass bathymetry estimation. Future development of the algorithm for repeat-pass operation has the potential to enable repeat-pass track registration in three dimensions. The method is therefore an important step towards improved coherent change detection and high resolution bathymetry estimation

Occlusion Modeling for Coherent Echo Data Simulation:A Comparison Between Ray-Tracing and Convex-Hull Methods

The ability to simulate realistic coherent datasets for synthetic aperture imaging systems is crucial for the design, development and evaluation of the sensors and their signal processing pipelines, machine learning algorithms and autonomy systems. In the case of synthetic aperture sonar (SAS), collecting experimental data is expensive and it is rarely possible to obtain ground truth of the sensor’s path, the speed of sound in the medium, and the geometry of the imaged scene. Simulating sonar echo data allows signal processing algorithms to be tested with known ground truth, enabling rapid and inexpensive development and evaluation of signal processing algorithms. The de-facto standard for simulating conventional high-frequency (i.e., > 100 kHz) SAS echo data from an arbitrary sensor, path and scene is to use a point-based or facet-based diffraction model. A crucial part of this process is acoustic occlusion modeling. This article describes a SAS simulation pipeline and compares implementations of two occlusion methods; ray-tracing, and a newer approximate method based on finding the convex hull of a transformed point cloud. The full capability of the simulation pipeline is demonstrated using an example scene based on a high-resolution 3D model of the SS Thistlegorm shipwreck which was obtained using photogrammetry. The 3D model spans a volume of 220 × 130 × 25 m and is comprised of over 30 million facets that are decomposed into a cloud of almost 1 billion points. The convex-hull occlusion model was found to result in simulated SAS imagery that is qualitatively indistinguishable from the ray-tracing approach and quantitatively very similar, demonstrating that use of this alternative method has potential to improve speed while retaining high fidelity of simulation.The convex-hull approach was found to be up to 4 times faster in a fair speed comparison with serial and parallel CPU implementations for both methods, with the largest performance increase for wide-beam systems. The fastest occlusion modeling algorithm was found to be GPU-accelerated ray-tracing over the majority of scene scales tested, which was found to be up to 2 times faster than the parallel CPU convex-hull implementation. Although GPU implementations of convex hull algorithms are not currently readily available, future development of GPU-accelerated convex-hull finding could make the new approach much more viable. However, in the meantime, ray-tracing is still preferable, since it has higher accuracy and can leverage existing implementations for high performance computing architectures for better performance

A latest Cretaceous to earliest Paleogene dinoflagellate cyst zonation of Antarctica, and implications for phytoprovincialism in the high southern latitudes

The thickest uppermost Cretaceous to lowermost Paleogene (Maastrichtian to Danian) sedimentary succession in the world is exposed on southern Seymour Island (65° South) in the James Ross Basin, Antarctic Peninsula. This fossiliferous shallow marine sequence, which spans the Cretaceous–Paleogene boundary, has allowed a high-resolution analysis of well-preserved marine palynomorphs. Previous correlation of Cretaceous–Paleogene marine palynomorph assemblages in the south polar region relied on dinoflagellate cyst biozonations from New Zealand and southern Australia. The age model of the southern Seymour Island succession is refined and placed within the stratigraphical context of the mid to high southern palaeolatitudes. Quantitative palynological analysis of a new 1102 m continuous stratigraphical section comprising the uppermost Snow Hill Island Formation and the López de Bertodano Formation (Marambio Group) across southern Seymour Island was undertaken. We propose the first formal late Maastrichtian to early Danian dinoflagellate cyst zonation scheme for the Antarctic based on this exceptional succession. Two new late Maastrichtian zones, including three subzones, and one new early Danian zone are defined. The oldest beds correlate well with the late Maastrichtian of New Zealand. In a wider context, a new South Polar Province based on Maastrichtian to Danian dinoflagellate cysts is proposed, which excludes most southern South American marine palynofloras. This interpretation is supported by models of ocean currents around Antarctica and implies an unrestricted oceanic connection across Antarctica between southern South America and the Tasman Sea

Repeat-pass synthetic aperture sonar micro-navigation using redundant phase center arrays

In this paper, a new algorithm is introduced for high-precision underwater navigation using the coherent echo signals collected during repeat-pass synthetic aperture sonar (SAS) surveys. The algorithm is a generalization of redundant phase center (RPC) micronavigation, expanded to RPCs formed between overlapping pings in repeated passes. For each set of overlapping ping pairs (two intrapass and three interpass), five different RPC arrays can be formed to provide estimates of the vehicle's surge, sway, and yaw. These estimates are used to find a weighted least squares solution for the trajectories of the repeated passes. The algorithm can estimate the relative trajectories to subwavelength precision (on order of millimeters to hundreds of micrometers at typical SAS operating frequencies of hundreds of kilohertz) in a common coordinate frame. This will lead to improved focusing and coregistration for repeat-pass SAS interferometry and is an important step toward repeat-pass bathymetric mapping. The repeat-pass RPC micronavigation algorithm is demonstrated using data collected by the 300-kHz SAS of the NATO Center for Maritime Research and Experimentation (CMRE) Minehunting Unmanned underwater vehicle for Shallow water Covert Littoral Expeditions (MUSCLE)

Improvement of Automatic Target Recognition Through Synthetic Data Augmentation

Data sets of well­ labelled and diverse acoustic imagery of the seabed are scarce. However, a recent breakthrough in synthetic aperture sonar (SAS) image simulation has facilitated the rapid generation of realistic echo data. The synthetic data include important aspects of the acoustic wave physics, such as aspect­ dependence, layover, diffraction, speckle, focusing errors, and artefacts. Moreover, it provides high­ fidelity label information. This combination of speed, realism, and detail has enabled the use of synthetic data to improve the volume and diversity of training data for deep learning algorithms in automatic target recognition (ATR). We present an overview of the rapid simulation model, alongside an existing SAS simulation model, and demonstrate its application to ATR training for the detection and classification of underwater munitions and unexploded ordnance