Peter T. Gough

Synthetic Aperture Sonar: A Review of Current Status

This is a review paper that surveys past work in, and the recent status of, active synthetic aperture sonar (SAS). It covers the early historical development of SAS with its provenance in synthetic aperture radar (SAR) and flows through into what work has been published in the open literature up to early 2007. The list of references is sufficiently complete to include most past and recent SAS publications in the open refereed literature.

Broad-band synthetic aperture sonar

The effects of a broadband signal on the performance of a side-scan synthetic aperture sonar, including detail on the necessary spatial sampling and resolution tradeoffs, are discussed. The mathematical description of the echo signals and the consequent image reconstruction algorithms are shown for a step-and-go scenario that ignores the Doppler effect. Extra modifications for the Doppler effects are introduced with some discussion of their probable impact. Simulated echoes and image reconstructions on hypothetical targets show the limiting performance and some of the effects of narrowband reconstruction approximations on broadband signals. For comparison, images taken from a CTFM 15-30 kHz sonar especially designed as a synthetic aperture sonar are presented. >

Stripmap phase gradient autofocus

Current sonar autofocus techniques for blur removal originate in the radar community but have not provided a complete solution for Synthetic Aperture Sonar (SAS) imagery. The wide-beam, wide-band nature of SAS imagery makes implementation of Synthetic Aperture Radar (SAR) autofocus techniques difficult. This paper describes a generalisation of the standard Phase Gradient Autofocus (PGA) algorithm used in spotlight SAR that allows operation with stripmap SAS geometries. PGA uses prominent points within the target scene to estimate image blurring and phase errors. We show how PGA can be generalised to work with wide-band, wide-beam stripmap geometries. The SPGA method works by employing wave number domain 2D phase estimation techniques. The 2D phase errors are related to aperture position errors using the wave number transform. Robust sway estimates are obtained by using redundancy over a number of target points. We also present an improved Phase Curvature Autofocus (PCA) algorithm using the wave number transform. Preliminary results from the two algorithms (both on field-collected and simulated data sets) are presented and related to those obtained using previous methods. A discussion of SPGAs benefits over traditional algorithms and the limitations of the SPGA algorithm is presented. The SPGA algorithm was found to perform better than 2-D PCA on both simulated and field-collected data sets. Further testing on a variety of target scenes and imagery is required to investigate avenues of autofocus improvement.

A short history of synthetic aperture sonar

The fundamental theory that underpins any synthetic aperture sonar (SAS) is the same as that developed for synthetic aperture radar (SAR). However, the slow speed of propagation and higher attenuation of acoustic waves in water provides for some significant practical differences. The most important of these differences is that the aperture is often undersampled giving rise to grating-lobe artifacts in the image. Also since the aperture takes some time to traverse, motion compensation and medium turbulence have a significant effect. This paper highlights some key advances in SAS.

Motion-Compensation Improvement for Widebeam, Multiple-Receiver SAS Systems

The effect that uncompensated motion errors have on synthetic aperture sonar (SAS) imagery can be severe. Time-domain beamforming SAS reconstruction is able to compensate arbitrary track errors, but the more efficient frequency-domain reconstruction algorithms, such as the range-Doppler, chirp-scaling, and wave number (aka range migration or Stolt-mapping) algorithms do not allow for simple compensation, especially for widebeam sonars. Data processed via these block algorithms is usually compensated before azimuth compression in a computationally inexpensive preprocessing step. Unfortunately, this compensation assumes a narrowbeam geometry, causing blurring in high-resolution images collected with widebeam sonars. In this paper, we demonstrate a new technique for compensation of large, but known, motion errors in data collected with widebeam geometry sonars. The technique relies on obtaining angle-of-arrival information from the multiple-receiver array configuration typical in high-resolution SAS systems. The new method of compensating for motion errors was found to significantly outperform the previous techniques in a simulation of point-reflector imagery.

Simulation of multiple-receiver, broadband interferometric SAS imagery

Interferometric synthetic aperture sonar (InSAS) is a technique for high-resolution, 3-dimensional underwater imaging. A significant problem in developing and testing InSAS algorithms is the difficulty in obtaining ground-truth data to compare with the reconstructed imagery/bathymetry. Thus, a reliable simulation model is a useful aid. Most SAS simulation models are based on a point-scatterer representation of the underwater scene. The point-scatterer model is computationally inefficient for simulating large, realistic scenes. Furthermore, effects such as aspect-dependent scattering, speckle, shadowing, and multiple-scattering are not replicated easily. In this paper we present an efficient model for the realistic simulation of multiple-receiver InSAS imagery. The model is based on a facet representation of the underwater scene. The field scattered by each facet is realised using statistics determined by the Kirchoff method and occlusions and multiple-scattering are resolved by ray-tracing. The simulation of InSAS imagery is demonstrated using the parameters of our Kiwi-SAS system. The simulated imagery is shown to include the characteristic effects of aspect-dependent scattering, speckle, and shadowing.

Autofocus of multi-band, shallow-water synthetic aperture sonar imagery using shear-averaging

A significant problem with Synthetic Aperture Sonar (SAS) imaging is the compensation of compensating for unknown errors in the sonar path trajectory. Unknown path errors in SAS have the effect of blurring and smearing the sea-floor image. Inertial navigation systems as used in Synthetic Aperture Radar (SAR), are not accurate enough for use in SAS. To deal with this problem, techniques for estimating and compensating the path errors from the gathered data (autofocus algorithms) have been developed. In this paper we present enhancements to an existing sonar autofocus algorithm presented in 1995 by Johnston et al. These enhancements help prevent the autofocus being biased by strong targets. Improvement in autofocus is significant and more apparent whenever an extended prominent target is far stronger than the surrounding seafloor clutter signal. We have tested both algorithms using and simulated data and the results are presented in this paper. In addition, we demonstrate the advantage of using single pass multiband imagery to improve the autofocus result.

Noncoherent autofocus of single-receiver broad-band synthetic aperture sonar imagery

A significant problem in Synthetic Aperture Sonar (SAS) imaging is compensating for unknown errors in the sonar path trajectory. Unknown deviations from the ideal sonar trajectory have the effect of blurring and smearing the sea-floor image. In typical operating conditions, the blurring can completely obscure details in the imaged scene. Techniques for estimating path deviations from the recorded data have been developed. Once estimated, the effects of deviations are compensated for and the blurring reduced. The process of estimating path-deviations and removing image blurring is called autofocus. We present a broad-band scheme for a bulk-motion estimation in the absence of inertial navigation system (INS) data. Once the effect of bulk-motion error is removed, alternate autofocus methods may be used to yield diffraction-limited imagery. In addition, the bulk autofocus allows a check on the validity of the motion measured by any inertial systems installed on the sonar tow-fish. The noncoherent autofocus operates by exploiting the envelope correlation between adjacent sonar echos to provide path deviation information. This puts the method into the same class of algorithm as the well-known shear-average autofocus, which exploits ping-to-ping phase correlation for its operation. The algorithm differs from shear-average by using only the base-band envelope of the echo data and not phase information. The algorithm has been tested on both real and simulated data and has some promise as a first step in any autofocusing system. In particular, the system should provide good starting information for any image quality based autofocus methods. The accuracy of the method is limited by biasing caused by strong target scatterers. Noncoherent autofocus also performs better than coherent shear-average autofocus for the very large path perturbations investigated.

Image reconstruction from pairs of Fourier-transform magnitude

The retrieval of phase information from only the magnitude of the Fourier transform of a signal remains an important problem for many applications. We present an algorithm for phase retrieval when there exist two related sets of Fourier-transform magnitude data. The data are assumed to come from a single object observed in two different polarizations through a distorting medium, so the phase component of the Fourier transform of the object is corrupted. Phase retrieval is accomplished by minimization of a suitable criterion function, which can take three different forms.

Autofocus of stripmap SAS data using the range-variant SPGA algorithm

This paper presents an extension of the Stripmap Phase Gradient Autofocus (SPGA) algorithm to allow operation in environments where the grazing angle varies with range. SPGA is designed for stripmap autofocus in a low-grazing angle scenario. Autofocus performance is degraded when imagery that has varying grazing angles is autofocused using SPGA. The SPGA extension presented here models the combined effect of slant-plane towfish sway and heave on the data. This enhanced modeling allows the algorithm to operate in situations where the grazing angle to the scene varies with range. Results from the application of the new algorithm to field-collected and simulated data sets are demonstrated. The range-variance SPGA extensions improve autofocus performance on simulation data that has varying grazing-angle. The field-collected dataset shown has little range variance and shows only minor improvement. We also present a short summary of simulation approximations giving consideration to quantitative autofocus testing.