Sonar Processing Research Articles

Constant rank factorisations of smooth maps, with applications to sonar

AbstractSonar systems are frequently used to classify objects at a distance by using the structure of the echoes of acoustic waves as a proxy for the object’s shape and composition. Traditional synthetic aperture processing is highly effective in solving classification problems when the conditions are favourable but relies on accurate knowledge of the sensor’s trajectory relative to the object being measured. This article provides several new theoretical tools that decouple object classification performance from trajectory estimation in synthetic aperture sonar processing. The key insight is that decoupling the trajectory from classification-relevant information involves factoring a function into the composition of two functions. The article presents several new general topological invariants for smooth functions based on their factorisations over function composition. These invariants specialise to the case when a sonar platform trajectory is deformed by a non-small perturbation. The mathematical results exhibited in this article apply well beyond sonar classification problems. This article is written in a way that supports full mathematical generality.

Lisa Zurk’s contributions to striation-based signal processing for active sonar

Strong multipath propagation adds considerable complication to acoustic signal processing in the ocean. When mapped in range-frequency space, the acoustic field exhibits striations, alternating bands of high and low intensity due to constructive and destructive interference between the paths. Nearly forty years ago, Russian scientists showed how this striation pattern could be described by a single scalar parameter, the so-called waveguide invariant that subsequently became a staple of their passive sonar signal processing methods. Lisa Zurk’s contribution was to show how a striation-based approach could be adapted to active sonar processing. Together with her students, she did tank experiments and analysis for monostatic and bistatic configurations. For a horizontal array, she developed a beamformer featuring a linear frequency shift across the array designed to align with high-intensity striations. The result was improved performance in noisy environments. She showed how the waveguide invariant can improve tracking accuracy by providing a constraint on possible tracks. She and her students demonstrated the improved tracking with continuous active sonar data. Lisa Zurk’s innovative work on these topics continues to inspire present day research.

Automatic Tracking of Weak Acoustic Targets within Jamming Environment by Using Image Processing Methods

Bear time records, which are the accumulations of spatial spectrum estimates on the time axis, are often employed for passive sonar information processing. Multi-target jamming is a common difficulty in this approach due to the constraints of Rayleigh limit, and neither the conventional beamforming (CBF) nor minimum variance distortionless response (MVDR) technique can handle it well. This work presents a post-processing tracking framework based on visual pattern recognition algorithms to track weak acoustic targets within jamming environments, which includes target motion analysis, matched filtering, and principal component analysis-based denoising, and we call this ‘P-Gabor’ algorithm. The simulations and sea-trial experiments show that the proposed method can track a weak target successfully under −23 dB (signal-to-interference ratio) SIR, which is more effective than the references, especially in terms of using real-world data from sea trials. We further demonstrate that the method also has stable tracking performance at even −25 dB SNR (signal-to-noise ratio) circumstances.

Extraction of seabed properties in mid-frequency range using waveguide invariant applied to broadband signals

One of the fundamental problems in shallow water environments is to assess the seabed properties. The waveguide invariant can be used in both passive and active sonar processing, source ranging, time reversal focusing, and in geoacoustic inversion processes. In Pekeris waveguide, the waveguide invariant value is approximately 1 and the slope of the interfering acoustic intensity fringes relates to the bottom sound speed. Using the slope of the striations as a variable, the spacing of the interference in range (or frequency) can be related to the penetration of energy into the bottom. The depth given by spacing of real arrivals has an effective depth of penetration which depends on the geoacoustic properties of the bottom sediments. Here, we study the frequency dependence of the waveguide invariant due to sediment layer structure and physical properties and provide a detailed data/model comparison for a shallow water range independent waveguide and extract the seabed properties for the frequency band 1.5 to 4.0 kHz using recent data obtained in shallow water environments. [Work supported by ONR 321OA.]

An Enhanced Data-Driven Array Shape Estimation Method Using Passive Underwater Acoustic Data

Beamforming-based signal enhancement technologies in passive sonar array processing often have poor performance due to array distortion caused by rapid tactical maneuvers of the towed platform, oceanic currents, hydrodynamic effects, etc. In this paper, an enhanced data-driven shape array estimation formulation is proposed using passive underwater acoustic data. Beamforming based on a hypothetically ideal array is firstly employed to perform the detection of narrow-band components from sources of opportunity, and the corresponding phases of these detected narrow-band components are subsequently extracted to acquire time-delay differences. Then, a weighted outlier-robust Kalman smoother is proposed to acquire enhanced estimates of the time-delay differences, since the underlying properties of slowly changing time-delay differences in the hydrophone array and diverse signal to interference and noise ratios in multiple narrow-band components are explored; and its Cramer–Rao Lower Bound is also provided. Finally, the hydrophone array shape is estimated based on the estimated time delay differences. The proposed formulation fully exploits directional radiated noise signals from distant underwater acoustic targets as sources of opportunity for real-time array shape estimation, and thus it requires neither the number nor direction of sources to be known in advance. The effectiveness of the proposed method is validated in simulations and real experimental data.

Late return focusing algorithm for circular synthetic aperture sonar data.

Synthetic aperture sonar processing is used to generate imagery for remote sensing applications such as environmental characterization and object detection. Images primarily represent the initial geometric response of acoustic scattering, but there are additional information embedded in the raw data that are not well-represented in images. For example, responses such as internal multiple scattering or elastic scattering are delayed in time, and they appear defocused in imagery. A complementary processing algorithm is presented that improves the focus of late acoustic scattering responses, which can potentially provide additional information about the object and aid data interpretability.

Radar and Sonar Imaging and Processing

The 21 papers (from 61 submitted) published in the Special Issue “Radar and Sonar Imaging Processing” highlighted a variety of topics related to remote sensing with radar and sonar sensors. The sequence of articles included in the SI dealt with a broad profile of aspects of the use of radar and sonar images in line with the latest scientific trends. The latest developments in science, including artificial intelligence, were used.

BATHYMETRIC SURVEYING IN LAKE SUPERIOR: 3D MODELING AND SONAR EQUIPMENTS COMPARING

Abstract. This paper represents the overview of hydrographic surveying and different types of modern and traditional surveying equipment, and data acquisition using the traditional single beam sonar system and a modern fully autonomous underwater vehicle (AUV) IVER3. During the study, the data sets were collected using the vehicles of the Great Lake Research Center at Michigan Technological University. This paper presents how to process and edit the bathymetric data on SonarWiz5. Lastly, it compares the accuracy of the two different sonar systems in the different missions and creates 3D models to display and understand the elevations changes. Moreover, the 3D models were created after importing the data sets in the same coordinate system. In this study, the data sets were recorded by two different sensors in the two study locations in the Keweenaw Waterway in Michigan, U.S. between the cities of Houghton and Hancock. The first one equipment is the Lowrance HDS-7 sonar on the surveying boat, and other one is the EdgeTech 2205 sonar on the fully AUV of IVER3. One of the purposes of this study is to explore the sonar post processing programs, which are very important to interpret sonar and bathymetric data, and obtained the same coordinate system of the study areas. During the project, three main processing programs were used. The first one is UnderSee Explorer 2.6, which has been used to process the data sets of Polar SV boat. Secondly, EdgeTech Discover 4600 bathymetric software used EdgeTech 2205 sonar data sets to create bathymetric files that were used in SonarWiz5. Lastly, SonarWiz5 sonar processing software can be used to process the data sets. After the data acquisition and the data process, six profiles from the first study area and the five profiles from the second study are created to compare the data sets and elevations difference. It is shown that single beam sonar might miss some details, such as pipeline and quick elevation changes on seabed when we compare to the side scan sonar of IVER3 because the single side scan sonar can acquire better resolutions to understand the 3D features, such as pipelines, reliefs etc.

Fast Denoising of Sonar Image Based on Saliency Detection

Sonar image is inevitably contaminated by noise during the acquisition process, while the noise reduction algorithms with good performance are usually of high time complexity. The human visual attention mechanism usually guides the eyes to salient region and gives priority to those visual information. In view of this, saliency detection based on manifold ranking was introduced into sonar image processing, to divide the image into two parts:salient region and non-significant region. For the salient region with small proportion, block-matching and 3-D filtering (BM3D) algorithm was adopted to reduce noise and protect the main information of the image; for the non-significant background which was not very concerned, high efficiency mean filtering was used. On the collected sonar image data set, the present algorithm was compared with the classic MF and BM3D algorithms through the subjective and 2 objective evaluation indexes. The experimental results show that the efficiency of the present algorithm is much higher than that of BM3D, while the image visual effect is guaranteed, which is satisfied with the real-time application requirement of autonomous underwater vehicles.

Towards Advancing Diver-Robot Interaction Capabilities

The underwater environment is hazardous for humans since they are dependent on technical equipment for life support, have limited navigation and communication capabilities with the surface, and the underwater environment is under the constant influence of external environmental disturbances. The paper presents the effort during the initial six months of the “Advancing Diver-Robot Interaction Capabilities (ADRIATIC)” project. This project builds upon recent research accomplishments in the area of underwater human-robot interaction. Main efforts are geared towards developing sonar processing algorithms for improved diver recognition and tracking, creating new wearable sensors for increasing diver safety and robust gesture recognition, and developing collaborative motion strategies for improved diver-robot interaction.

Shared autonomy for low‐cost underwater vehicles

AbstractThis field report presents an overview of the development and testing of a semi‐autonomous underwater vehicle (sAUV). The work presented here is aimed at bridging the gap between current remotely operated vehicles and autonomous research platforms by developing shared autonomy capabilities for low‐cost underwater vehicles. We use commercially available components and open‐source software interfaces to provide a wider range of capabilities for underwater autonomy research at a lower cost than previously available systems. We describe the overall structure of the system, discuss its capabilities, and provide results demonstrating system performance. We place particular emphasis on shared autonomy, where a human operator is assisted in controlling an underwater tethered vehicle. We present three capabilities developed for the sAUV: (a) an assisted control mode that provides a variable level of assistance using an on‐line estimate of user skill level, (b) a planner to generate paths that avoid tether entanglement, and (c) a sonar processing algorithm that identifies informative sonar images for selecting features for 3D scene reconstruction. The vehicle has been deployed on five off‐shore and near‐shore marine field deployments since 2015, and this report includes selected results from four of those trials to demonstrate the capabilities and limitations of the sAUV system.

Analysis and comparison of spatial correlation and intensity distribution statistics

Active sonar processing systems operating in shallow-water littoral environments are often plagued with excessive false alarms, generally referred to as sonar clutter. At times the effects of these clutter events can be mitigated through repeated measurements and/or careful sonar operator examination; however, this process can be time consuming and even experienced sonar operators may have difficulty identifying targets in cluttered environments. Additionally, increasing interest in autonomous vehicle platforms and the push for real-time decision and performance management introduces further requirements on sonar systems. This work provides an empirical analysis of the potential in using spatial correlation of the backscattered wavefront as a classification metric, and compares this metric to a commonly used probability density function (PDF) processing method. The shape of the PDF of the backscattered acoustic intensity is often used in sonar processing systems such as constant false alarm rate (CFAR) detectors. These PDFs generally provide an estimate of the Rayleigh-like (random phase scattering) or non-Rayleigh-like (generally finite bright scatterers) nature of temporal variations in acoustic returns. This talk will outline information that may be available about clutter events based on measurements of spatial correlation. [Work supported by Office of Naval Research.]

Sonar processing by the spectrogram correlation and transformation model of biosonar

Echolocating big brown bats emit frequency-modulated (FM) biosonar sounds and perceive target range from echo delays through spectrogram correlation (SC) and target shape from interference nulls in echo spectra through spectrogram transformation (ST). Combined, the SCAT model is a computationally unified auditory description of biosonar as a real-time process. We developed a Matlab implementation of SCAT and tested it with a succession of simulated bat-like FM signals (chirps), each followed by one or more FM echoes that have realistic delay and spectral characteristics. The model simulates neural response latencies in frequency-tuned delay-lines that use coincidence detections for target ranging by SC. For ST, a novel, deconvolution-like network transforms echo spectra into images of the target’s glints by detecting coincidences between spikes that represent spectral nulls in parallel channels tuned to null frequencies. Experiments show that dolphins likely separate ST into two operations—MaPS for short glint separations (macro power spectral features, 80 µs). The ST deconvolution network models MiPS. The highly distributed character of the model favors real-time operation, an important goal for bioinspired sonar development. [Work supported by ONR.]

Acoustic intensity fluctuation studies in shallow water over the past quarter century

One of Ira Dyer’s seminal contributions to underwater acoustics was in the understanding of acoustic intensity fluctuations. In particular, the 5.6 dB intensity fluctuation of a large number of interfering narrowband multipaths, which is often informally referred to as “the Dyer number”, is a robust and well know effect. In shallow water, a number of physical effects can modify this basic number. These effects have been measured in various experiments over the years, and we will show a subset of these results. The physics of the effects, the measurement techniques, and the implications of this work for sonar processing will all be discussed. Work supported by ONR.

The contributions of Nathaniel (Nat) Durlach to binaural hearing research

The important and extensive work of Nat Durlach in the area of binaural hearing will be reviewed. Nat started working on this topic in the context of work on bat sonar processing at Lincoln Laboratories, with an early publication on his hearing modeling in 1960. Nat's thinking about the sonar problem and signal processing in noise led to his long-term interest and work in human hearing, and he joined the Sensory Communications group at MIT in 1963. In addition to his well-known work on the Equalization-Cancellation (EC) model, his important contributions to other binaural hearing models and experiments will be discussed, including work in detection, discrimination, and estimation. Nat's binaural work also allows a consideration of his deep thinking about problems, his approach to modeling in general, and his distinctive style of interacting with other scientists, both young and old. The ongoing impact of Nat's binaural hearing work, his personal example for approaching research, and his deep influence on ...

Bistatic continuous active sonar processing using arrays towed from unmanned underwater vehicles

Continuous active sonar (CAS) offers the possibility to continuously illuminate targets in underwater detection scenarios. The Cooperative Antisubmarine Programme at the Centre for Maritime Research and Experimentation has developed a real-time continuous active sonar signal processing algorithm and tested it at sea during two recent sea trials. These sea trials, undertaken with partners of the Littoral Continuous Active Sonar multinational project, were conducted in littoral environments for the purpose of evaluating the effectiveness of CAS against a traditional pulse active sonar benchmark. Data collected during these sea trials have been collected on both ship-towed triplet arrays and smaller arrays deployed from AUVs. Some details of the algorithm are given and results at the beamforming, detection and tracking level are presented for both CAS and PAS for an echo repeater target. [This work was made possible by the LCAS Multi-National Joint Research Project (MN-JRP), including as Participants CMRE (NATO), DSTG (AUS), DRDC (CAN), Dstl (GBR), CSSN (ITA), FFI (NOR), DTA (NZL), and ONR (USA). Funding for CMRE was provided by the NATO Allied Command Transformation.]

Signal processing trade-offs for the representation and quality assessment of acoustic color signatures

Acoustic color is a representation of an object, typically 2-D, which is constructed to show the evolution of the spectral response over the aspect of the object. The two natural axes for this representation are frequency and the aspect to the object. It is intuitive to assume finer resolution in both dimensions would lead to more information extractable for improved quality. However, with conventional linear track data collection methods, there is an inherent trade-off between signal processing decisions and the amount of information that can be utilized without loss of quality. In this work, this trade-off is investigated for an object with a simple geometry, and various quality metrics are discussed. For objects with spectral response that changes slowly over aspect, quality can be improved with methods such as synthetic aperture sonar processing. However, the effect of these processing decisions can depend on the type of object being represented. Other representation approaches as extensions of acoustic color will also be explored, such as time-evolving acoustic color that shows how the spectral response changes within a ping cycle.

Increasing circular synthetic aperture sonar resolution via adapted wave atoms deconvolution.

Circular Synthetic Aperture Sonar (CSAS) processing computes coherently Synthetic Aperture Sonar (SAS) data acquired along a circular trajectory. This approach has a number of advantages, in particular it maximises the aperture length of a SAS system, producing very high resolution sonar images. CSAS image reconstruction using back-projection algorithms, however, introduces a dissymmetry in the impulse response, as the imaged point moves away from the centre of the acquisition circle. This paper proposes a sampling scheme for the CSAS image reconstruction which allows every point, within the full field of view of the system, to be considered as the centre of a virtual CSAS acquisition scheme. As a direct consequence of using the proposed resampling scheme, the point spread function (PSF) is uniform for the full CSAS image. Closed form solutions for the CSAS PSF are derived analytically, both in the image and the Fourier domain. The thorough knowledge of the PSF leads naturally to the proposed adapted atom waves basis for CSAS image decomposition. The atom wave deconvolution is successfully applied to simulated data, increasing the image resolution by reducing the PSF energy leakage.

Striation Processing of Data From the 2013 Target and Reverberation Experiment (TREX13)

In active sonar processing, the discrimination of the target versus clutter can be a significant challenge. Whereas conventional processing often uses target kinematics to limit the possible target tracks, it has recently been shown that frequency domain information (based on the waveguide invariant principle) can also be incorporated to further limit the possible target tracks in an environmentally robust fashion. This paper presents physics-based signal processing methods to extract information about the target track from striations in a target spectrogram formed from the echo spectra at each active sonar pulse repetition interval. The target tracking information is formulated as a post-track likeliness statistic that is extracted from the sonar data with image processing techniques. Results are demonstrated with shallow water sonar data collected during the 2013 Target and Reverberation Experiment (TREX13). It is expected that the physics-based signal processing algorithms discussed here will provide enhanced clutter rejection and improve tracking performance.

IRAP: An integrated, real-time, autonomous passive acoustic monitoring system for beaked whale detection, localization, and tracking

The integration and demonstration of passive sonar hydrophone arrays into autonomous undersea platforms for acoustic marine mammal monitoring has witnessed significant advances in the last few years due to the availability and scalability of low-cost, low-power commercial technology for acoustic remote sensing. In this paper, we will review the at-sea performance of a nine-element Mills Cross high frequency hydrophone array (HFA) integrated into an autonomous undersea vehicle (AUV) for the detection, classification, localization, and tracking (DCLT) of beaked whales during a deployment conducted off leeward Kauai in February, 2016. Using passive sonar equation analysis, we will review the design rationale of the HFA, and quantify system performance using standard signal processing metrics such as measured array gain, tracking accuracy, and detection range on a calibrated high-frequency source transmitting replica beaked whale click trains at a de minimus source level. A candidate autonomous real-time passive sonar processing architecture that combines an adaptive beamformer/matched filter front-end with a false alarm mitigation back-end to balance detection sensitivity, classifier robustness, and processing throughput will also be presented. We conclude with a cost/power/persistence trade-off for some commercially available autonomous platforms. [This work was supported by NAVFAC Living Marine Resources Program.]