Signal Processing for Synthetic Aperture Sonar Image Enhancement

This thesis contains a description of SAS processing algorithms, offering improvements in Fourier-based reconstruction, motion-compensation, and autofocus. Fourier-based image reconstruction is reviewed and improvements shown as the result of improved system modelling. A number of new algorithms based on the wavenumber algorithm for correcting second order effects are proposed. In addition, a new framework for describing multiple-receiver reconstruction in terms of the bistatic geometry is presented and is a useful aid to understanding. Motion-compensation techniques for allowing Fourier-based reconstruction in widebeam geometries suffering large-motion errors are discussed. A motion-compensation algorithm exploiting multiple receiver geometries is suggested and shown to provide substantial improvement in image quality. New motion compensation techniques for yaw correction using the wavenumber algorithm are discussed. A common framework for describing phase estimation is presented and techniques from a number of fields are reviewed within this framework. In addition a new proof is provided outlining the relationship between eigenvector-based autofocus phase estimation kernels and the phase-closure techniques used astronomical imaging. Micronavigation techniques are reviewed and extensions to the shear average single-receiver micronavigation technique result in a 3 - 4 fold performance improvement when operating on high-contrast images. The stripmap phase gradient autofocus (SPGA) algorithm is developed and extends spotlight SAR PGA to the wide-beam, wide-band stripmap geometries common in SAS imaging. SPGA supersedes traditional PGA-based stripmap autofocus algorithms such as mPGA and PCA - the relationships between SPGA and these algorithms is discussed. SPGA's operation is verified on simulated and field-collected data where it provides significant image improvement. SPGA with phase-curvature based estimation is shown and found to perform poorly compared with phase-gradient techniques. The operation of SPGA on data collected from Sydney Harbour is shown with SPGA able to improve resolution to near the diffraction-limit. Additional analysis of practical stripmap autofocus operation in presence of undersampling and space-invariant blurring is presented with significant comment regarding the difficulties inherent in autofocusing field-collected data. Field-collected data from trials in Sydney Harbour is presented along with associated autofocus results from a number of algorithms

Synthetic Aperture Techniques for Sonar Systems

Today a good percentage of our planet is known and well mapped. Synthetic aperture techniques used in space and airborne systems has greatly aided to obtain this information. Nevertheless our planet is mostly covered by water and the level of detail of knowledge about this segment is still very far away from that of the land segment

Acoustic classification of buried objects with mobile sonar platforms

Thesis (Ph. D. in Ocean Engineering)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Includes bibliographical references (p. 229-237).In this thesis, the use of highly mobile sonar platforms is investigated for the purpose of acoustically classifying compact objects on or below the seabed. The extension of existing strategies, including synthetic aperture sonar and conventional imaging, are explored within the context of the buried object problem. In particular, the need to employ low frequencies for seabed penetration is shown to have a significant impact both due to the relative length of the characteristic scattering mechanisms and due to the interface effects on the target scattering. New sonar strategies are also shown that exploit incoherent wide apertures that are created by multiple sonar platforms. For example, target shape can be inverted by mapping the scattered field from the target with a team of receiver vehicles. A single sonar-adaptive sonar platform is shown to have the ability to perform hunting and classification tasks more efficiently than its pre-programmed counterpart. While the monostatic sonar platform is often dominated by the source component, the bistatic or passive receiver platform behavior is controlled by the target response. The sonar-adaptive platform trajectory, however, can result in the platform finishing its classification effort out of position to complete further tasks.(cont.) Within the context of a larger mission, the use of predetermined adaptive behaviors is shown to provide improved detection and classification performance while minimizing the risk to the overall mission. Finally, it is shown that multiple sonar-adaptive platforms can be used to create new sonar strategies for hunting and classifying objects by shape and content. The ability to sample the scattered field from the target across a wide variety of positions allows an analysis of the aspect-dependent behavior of the target. The aspect-dependence of the specular returns indicate the shape of the target, while the secondary returns from an elastic target are also strongly aspect-dependent. These features are exploited for improved classification performance in the buried object hunting mission.by Joseph R. Edwards.Ph.D.in Ocean Engineerin

compressive synthetic aperture sonar imaging with distributed optimization

Synthetic aperture sonar (SAS) provides high-resolution acoustic imaging by processing coherently the backscattered acoustic signal recorded over consecutive pings. Traditionally, object detection and classification tasks rely on high-resolution seafloor mapping achieved with widebeam, broadband SAS systems. However, aspect- or frequency-specific information is crucial for improving the performance of automatic target recognition algorithms. For example, low frequencies can be partly transmitted through objects or penetrate the seafloor providing information about internal structure and buried objects, while multiple views provide information about the object's shape and dimensions. Sub-band and limited-view processing, though, degrades the SAS resolution. In this paper, SAS imaging is formulated as an l1-norm regularized least-squares optimization problem which improves the resolution by promoting a parsimonious representation of the data. The optimization problem is solved in a distributed and computationally efficient way with an algorithm based on the alternating direction method of multipliers. The resulting SAS image is the consensus outcome of collaborative filtering of the data from each ping. The potential of the proposed method for high-resolution, narrowband, and limited-aspect SAS imaging is demonstrated with simulated and experimental data.Synthetic aperture sonar (SAS) provides high-resolution acoustic imaging by processing coherently the backscattered acoustic signal recorded over consecutive pings. Traditionally, object detection and classification tasks rely on high-resolution seafloor mapping achieved with widebeam, broadband SAS systems. However, aspect- or frequency-specific information is crucial for improving the performance of automatic target recognition algorithms. For example, low frequencies can be partly transmitted through objects or penetrate the seafloor providing information about internal structure and buried objects, while multiple views provide information about the object's shape and dimensions. Sub-band and limited-view processing, though, degrades the SAS resolution. In this paper, SAS imaging is formulated as an l1-norm regularized least-squares optimization problem which improves the resolution by promoting a parsimonious representation of the data. The optimization problem is solved in a distributed and computati..

AUV-enabled adaptive underwater surveying for optimal data collection

A new adaptive strategy for performing data collection with a sonar-equipped autonomous underwater vehicle (AUV) is proposed. The approach is general in the sense that it is applicable to a wide range of underwater tasks that rely on subsequent processing of side-looking sonar imagery. By intelligently allocating resources and immediately reacting to the data collected in-mission, the proposed approach simultaneously maximizes the information content in the data and decreases overall survey time. These improvements are achieved by adapting the AUV route to prevent portions of the mission area from being either characterized by poor image quality or obscured by shadows caused by sand ripples. The peak correlation of consecutive sonar returns is used as a measure for image quality. To detect the presence of and estimate the orientation of sand ripples, a new innovative algorithm is developed. The components of the overall data-driven path-planning algorithm are purposely constructed to permit fast real-time execution with only minimal AUV onboard processing capabilities. Experimental results based on real sonar data collected at sea are used to demonstrate the promise of the proposed approach

Interferometric Synthetic Aperture Sonar Signal Processing for Autonomous Underwater Vehicles Operating Shallow Water

The goal of the research was to develop best practices for image signal processing method for InSAS systems for bathymetric height determination. Improvements over existing techniques comes from the fusion of Chirp-Scaling a phase preserving beamforming techniques to form a SAS image, an interferometric Vernier method to unwrap the phase; and confirming the direction of arrival with the MUltiple SIgnal Channel (MUSIC) estimation technique. The fusion of Chirp-Scaling, Vernier, and MUSIC lead to the stability in the bathymetric height measurement, and improvements in resolution. This method is computationally faster, and used less memory then existing techniques