High-resolution Synthetic Aperture Sonar Research Articles

Frequency‐domain multireceiver synthetic aperture sonar imagery with Chebyshev polynomials

Based on Chebyshev polynomials, the two-way slant range is first approximated by the fourth-order polynomial approximation. With the series reversion method, the point target reference spectrum (PTRS) which is further used for the development of imaging algorithm in this letter is obtained. The presented method processes the echoed signal corresponding to each transmitter/receiver pair. And then a high-resolution synthetic aperture sonar (SAS) image is obtained by coherently superposing all coarse-resolution images. Comparing the peak sidelobe ratio (PSLR) and integration sidelobe ratio (ISLR), the performance of the presented method is superior to that of the traditional method. Simulations are further validated by the presented method.

New insights into the formation of submarine glacial landforms from high-resolution Autonomous Underwater Vehicle data

Autonomous Underwater Vehicles (AUVs) deployed close to the seafloor can acquire high-resolution geophysical data about the topography and shallow stratigraphy of the seabed, yet have had limited application within the fields of glacial geomorphology and ice sheet reconstruction. Here, we present multibeam echo-sounding, side-scan sonar, sub-bottom profiler and High-Resolution Synthetic Aperture Sonar (HISAS) data acquired during three AUV dives on the northeast Antarctic Peninsula continental shelf. These data enable glacial landforms, including mega-scale glacial lineations (MSGLs), grounding-zone wedges (GZWs) and iceberg ploughmarks, to be imaged at a horizontal resolution of a few tens of centimetres, allowing for the identification of subtle morphological features. We map tidal ridges that are interpreted as having been formed 1) along the ice-sheet grounding line by the squeezing up of soft seafloor sediments by vertical motion of the grounding line during tidal cycles, and 2) by the tidally driven motion of grounded or near-grounded icebergs. These data also enable the mapping of small GZWs that show the location of short-term still-stands or re-advances of the ice-sheet grounding zone. No meltwater channels are identified from our data, suggesting that free-flowing meltwater may not be essential for the formation of GZWs or MSGLs. The examples presented here show how high-resolution AUV-derived geophysical data provide a step-change in our ability to image seafloor glacial landforms, enabling new interpretations about past ice dynamics and glacial sedimentation at fine temporal and spatial scales.

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.

Interpolation Kernels for Synthetic Aperture Sonar Along-Track Motion Estimation

The formation of high-resolution synthetic aperture sonar (SAS) imagery requires accurate estimates of the sensor's trajectory. This is frequently accomplished using the displaced phase center antenna technique, which utilizes cross correlation of the signals received on successive pings. Accurate estimates of the sensor's ping-to-ping advance are then made by measuring the along-track spatial coherence of the scattered field. Unbiased advance-per-ping estimates require an accurate model for the spatial coherence of the scattered field. This model may be found by the application of the van Cittert-Zernike theorem to the problem of pulsed active sonar systems. In this paper, it is shown that the spatial coherence for a typical high-frequency SAS collection geometry is well approximated by a Gaussian whose width is proportional to the sensor's element size. Gaussian and quadratic along-track interpolation kernel performances are compared for a pair of at sea data collections. A relative image quality metric, based on image contrast, is defined to quantitatively assess the performance of the pair of interpolation kernels. In both tests, the use of an along-track estimator is shown to provide improved image quality. Also in both tests, the performance of the Gaussian kernel exceeds that of the quadratic kernel.

An Indirect Range-Doppler Algorithm for Multireceiver Synthetic Aperture Sonar Based on Lagrange Inversion Theorem

This paper presents a novel imaging algorithm which has the capacity of processing multireceiver synthetic aperture sonar (SAS) data based on Vu’s spectrum. There are two important issues when developing the fast Fourier-based imaging algorithms. One is the point target reference spectrum (PTRS) with analytical expression in the 2-D frequency domain; the other is the space variance of the PTRS. Vu has solved the first issue based on the Lagrange inversion theorem. However, the second issue has not been solved yet. Our approach in this paper is to apply Vu’s spectral result in an indirect range-Doppler (R-D) imaging algorithm. For each transmitter/receiver pair, the close-form azimuth modulation is derived first, and then, range/azimuth coupling can be obtained via the difference between the PTRS and the azimuth modulation. Unlike traditional R-D algorithm, which utilizes the interpolation operation to eliminate the range cell migration (RCM), the RCM correction (RCMC) in this paper is carried out through two steps, i.e., bulk RCMC and differential RCMC. Bulk RCMC accounts for the RCMC in one reference range. Differential RCMC accomplished with a range-dependent subblock postprocessing method is used to compensate for the space variant deviation phase error. Via the proposed method, the echoed signal corresponding to each transmitter/receiver pair is processed first. Following which, a high-resolution SAS complex image is obtained by coherent superposition of all the coarse subimages. Numerical simulations and real data processing results show that the proposed method has the similar focusing capabilities with the accurate back projection algorithm across the whole swath. Although the presented method has the disadvantage of latency, it is very easy to make a complete phase center approximation correction, allowing for the tandem nature of the collected data. Besides, the proposed algorithm can handle general case with explicit point of stationary phase (PSP) no matter how complicated the PSP is, and it is also suitable for the imagery of tandem synthetic aperture radar.

Improving Automatic Target Recognition with Forward Looking Sonar Mosaics

Automatic Target Recognition (ATR) is a key element needed to make Mine Countermeasure missions using robots entirely autonomous. While there has been much progress in applying ATR algorithms on high-resolution Synthetic Aperture Sonar (SAS) and sidescan sonar data, performing ATR with a low cost Forward Looking Sonar (FLS) is much more challenging. An algorithm for the detection of underwater man-made objects in FLS previously developed can work in real-time although it suffers considerably from typical noise in sonar images and false alarms. The work presented here shows that ATR algorithms can be exercised on sonar mosaics built also in real-time instead of raw data coming from the FLS. The use of mosaics can help the detection of the targets by reducing some noise (including harmonics from other acoustic devices mounted on the robot) and giving a better contrast to the images to be processed. Moreover, mosaic images can be useful for post-processing and data analysis. The mosaicking algorithm also runs in real-time to maintain the performance of the system and to be useful in real missions. It was tested both on data previously collected and in real experiments with different set-ups and with different sonars. The wide range of results obtained with different surface vehicles and in different situations demonstrate the usefulness of the method.

中国水声信号处理30年

The advances of new technology and theoretical development in 30 years of underwater acoustic signal processing and its applications in sonar design are presented in this paper. The topics include the research work in the field of underwater acoustic signal modeling, acoustic field matching, ocean waveguide and internal wave, the exaction and processing technique of acoustic vector signal information, space/time correlation characteristics of low frequency acoustic channel, the invariant feature of underwater target radiated noise, the transmission technology of underwater voice/image data, and its anti-interference technique. Some frontier technologies in sonar design are also discussed, including large aperture towed line array sonar, high resolution synthetic aperture sonar, deep sea siren and deep sea manned subsea vehicle, diver detection sonar and demonstration projector of national ocean monitoring system in China, etc.

Characterization and scattering measurements from rock seafloors using high-resolution synthetic aperture sonar

Automated target detection systems are known to perform poorly in shallow water environments having high levels of reverberation and strongly varying scattering, such as rock outcroppings. Prediction of the scattering statistics is difficult because scattering from rock seafloors is not well understood. There is a lack of characterization methods, scattering strength measurements, and accurate approximate models for such interfaces. This research aims to measure the scattering strength of rock seafloors using an uncalibrated synthetic aperture sonar (SAS). An effective calibration has been made using a seafloor with a known scattering response. Scattering strength measurements will be used in conjunction with local slope information provided by interferometric SAS to characterize the rough interface.

A Parametric Model for Characterizing Seabed Textures in Synthetic Aperture Sonar Images

High-resolution synthetic aperture sonar (SAS) systems yield finely detailed images of sea bottom environments. SAS image texture models must be capable of representing a wide variety of sea bottom environments including sand ripples, coral or rock formations, and flat hardpack. In this paper, a parameterized model for SAS image textures is derived from the autocorrelation functions (ACFs) of the SAS imaging point spread function (PSF) and the ACF of the seabed texture sonar cross section (SCS). The proposed texture mixture model is analytically tractable and parameterized by component mixing parameters, mixture component correlation lengths, the single-point intensity image statistical shape parameter, and the rotation of the ACF mixture components in the 2-D imaging plane. An iterative parameter estimation algorithm based on the expectation-maximization (EM) algorithm for truncated data is presented and tested against various synthetic and real SAS image textures. The performance of the algorithm is compared and discussed for synthetically generated data across various image sizes and texture characteristics. The model fit is also compared against a small set of real SAS survey images and is shown to accurately fit the imaging PSF and seabed SCS ACF for these textures of interest.

Model-based sea mine classification with synthetic aperture sonar

The quality and effectiveness of sensor information provided by mine-hunting autonomous underwater vehicles (AUVs) equipped with high-resolution sonars has improved drastically in recent years. In parallel, data rates have significantly increased resulting in information overload. Automatic target recognition (ATR) is regarded as a solution for this problem. This study describes a specific ATR technique based on model matching for application to high-resolution data. A sonar model for generation of high-resolution synthetic aperture sonar (SAS) images is described and applied both as database generator and classification. The performance of the model matching, which is attained by correlation and stochastically, is evaluated using a large data set covering the variety expected in mine-hunting operations. The model-based features generated in this way are able to reach an acceptable classification performance. The article is concluded with one real data example, which is easily classified when training with the simulated database. Further work is next aimed to confirm performance on real data.

The Impact of Multipath on High-Resolution SAS Image Statistics

As with traditional sonar, synthetic aperture sonar (SAS) is susceptible to multipath contamination, reducing the quality and also modifying the statistics of the image. Such multipath contaminants may either be environmentally induced, as is often the case when attempting to image ranges greater than the water depth resulting in returns from the boundaries, or may be induced by the system's supporting structure itself. A clear understanding of such statistical impact is necessary to advance synthetic aperture formation algorithms and for predicting system performance. Broadband acoustic data suitable for SAS processing collected with a rail-mounted mobile-tower as part of the U.S. Office of Naval Research (ONR)-funded Sediment Acoustics eXperiment 2004 (SAX04) are analyzed in this paper. Analysis focused on both system structure and environmentally induced multipath using the K -distribution shape parameter as a metric. High-resolution sonar imagery often exhibited significantly non-Rayleigh, heavy-tailed envelope statistics, characterized by a low equivalent K-distribution shape parameter. Analysis showed a clear and significant increase in the estimated shape parameter in the presence of multipath, representing a trend toward a Rayleigh-distributed envelope. A model for reverberation is presented to provide bounds of the statistical impact using observable image intensity level increases in synthetic-aperture-formed images caused by multipath contamination. This model further shows potential for statistical impact when multipath arrivals are of similar level as the direct path even when not observable in the image (e.g., within 10 dB).

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.

Interferometric height estimation of the seafloor via synthetic aperture sonar in the presence of motion errors

An end-to-end simulated processing chain related to an existing synthetic aperture sonar (SAS) system is developed and described, including motion compensation, efficient image formation and autofocus procedures. The processing is extended to include interferometric height estimation capability. It is the goal of the paper to study the application of interferometry to SAS systems in the presence of motion errors. The system is analysed with respect to motion errors and the subsequent damaging effects to both imaging and height estimation. Results using both measured and simulated data are presented. The problem is addressed with respect to both one-pass and two-pass imaging geometries, and it is hypothesised that for slowly varying target height, one-pass SAS interferometry may be a more robust imaging tool than conventional SAS alone. The simulated results suggest that height information is recoverable even in some situations in which the conventional SAS reflectivity image is completely ruined by phase error induced blur. High-resolution SAS imaging coupled with interferometric height estimation for seafloor imaging has military applicability in mine detection or classification and in topographic mapping in preparation for an amphibious assault. Civilian uses would include surveying of objects such as oil pipelines and seabed mapping.

Compensation of medium-induced fluctuations for synthetic aperture sonar

There are two primary obstacles to achieving aperture coherence in synthetic aperture sonar (SAS); motion compensation (MOCOMP) accuracy, and medium fluctuations along the acoustic propagation paths. The feasibility of MOCOMP for high-resolution SAS using a combination of commercial MOCOMP sensor components with existing autofocus processing algorithms has been previously assessed. This paper discusses the experimental measurement of acoustic fluctuations induced by inhomogeneities in sea water, their impact on SAS imagery, and whether autofocusing algorithms can compensate for medium-induced fluctuations. Spatial as well as temporal fluctuations over propagation path lengths of 1000 ft and frequencies of 100 kHz are relevant to high resolution SAS. A historical survey discovered no data in this parameter regime. Therefore, a joint IR&D effort, the Acoustic Medium Stability Experiment (AMSE), was conducted to collect appropriate data. AMSE’s unique data set provides space-time statistical descriptions of the medium-induced phase fluctuations. Using the AMSE data and an end-to-end SAS simulation capability, it was found that medium-induced fluctuations do degrade SAS imagery significantly. However, available autofocusing algorithms are capable of estimating and compensating the medium-induced phase errors (in addition to MOCOMP errors), allowing fully focused imagery to be obtained.