Single Ping Research Articles

Temporal Fusion Based 1-D Sequence Semantic Segmentation Model for Automatic Precision Side Scan Sonar Bottom Tracking

Precision bottom tracking is a core step in the data processing of side scan sonar (SSS), which is of critical value for the quality of the final SSS production. Currently, the automatic precision SSS bottom tracking remains challenging due to the complex noise caused by the measuring environment, especially the existing methods did not fully exploit the temporal correlations or depended on the hand-crafted setting. Therefore, we proposed a novel temporal fusion based one-dimensional (1-D) sequence semantic segmentation model, TFSSM-1D, to fuse the temporal correlation features and perform automatic precision SSS bottom tracking. The TFSSM-1D uses the deep learning encoder-decoder model for mapping inputs to 1-D semantic label outputs, with the aid of preprocess and temporal fusion modules to improve the accuracy and robustness. Among them, preprocess module is used to introduce the prior knowledge of bilateral symmetry, which alleviates the defect of long-distance features correlation caused by the inductive bias of convolution neural network. The temporal fusion consists of the point-wise temporal fusion module (PTFM) and the bi-directional attention propagation module (BAPM) guides the model to explicitly fuse the temporal variation features on different scales. The experimental results demonstrate the effectiveness of TFSSM-1D, and its mean port offset error reaches 2.7058 on the testing set without down-sampling, which is 40% lower than the previous deep learning based model with single ping input, and other evaluation metrics have also significantly improved. The inference on unseen data shows that TFSSM-1D can achieve precision bottom tracking with good noise immunity.

Time frequency investigation and representation of acoustic backscatter signatures

Observation of an object’s structural acoustic response, considered in the aspect-dependent frequency response domain, is a data representation used for characterizing the target strength of an object. Geometric and elastic wave features in the angle-frequency domain are difficult to distinguish. Time varying characteristics such as attenuation are lost with a single frequency transform across the entire time collection of the acoustic return. Research in the aspect angle-frequency domain primarily applies the fast Fourier transform to an entire time series collection for a single ping cycle. This work aims to extend the dimensional space of analysis for the acoustic backscatter representation by investigating time-frequency resolution across aspect angle for acoustic elastic responses of an object. Empirical analysis of the data is presented with application of various time frequency transforms. These methods are assessed using time frequency localization metrics to quantify their performance with the AirSAS dataset. This exploratory work will develop the intuition regarding how the time frequency distribution can be localized, measured, and vary among objects of differing compositions. The ways in which time frequency localization can support distinguishing features of the acoustic return beyond the traditional aspect angle-frequency domain will be discussed as well.

A CFAR Detection Approach for Identifying Gas Bubble Seeps With Multibeam Echo Sounders

A cell-averaged constant false alarm rate (CFAR) detector is described and applied to data collected with a multibeam echo sounder (MBES). The CFAR detector is designed specifically for transient targets observed with MBES, and operates under the assumption that background noise, including volume and seafloor reverberation, is locally stationary in time. This assumption, and the CFAR detector performance in general, was examined for data collected by a 30-kHz MBES operating in the Gulf of Mexico where the targets of interest were methane gas bubble plumes rising up from the seabed. Results with example data suggest that the CFAR detector was able to remove 99.1% of the MBES raw data while preserving the targets of interest. False detections appear randomly distributed throughout a single MBES ping, unlike the targets, and a within-ping target clustering algorithm was able to remove many of the false detections. In a single ping, an example is shown where the combined CFAR detector and a target cluster-size rule was able to reduce the number of false detections to 99.8% of the original data. The detector and cluster-size rules were applied to a sequence of approximately 400 pings, and two additional morphological rules based on the size and aspect ratio of the resulting target clusters were then applied to the detections to isolate the MBES backscatter intensity associated with gas bubbles. This combination of CFAR detector and simple morphological classification rules provides a useful way to detect gas bubble seeps or other transient targets.

Bottom Detection from Backscatter Data of Conventional Side Scan Sonars through 1D-UNet

As widely applicated in many underwater research fields, conventional side-scan sonars require the sonar height to be at the seabed for geocoding seabed images. However, many interference factors, including compensation with unknown gains, suspended matters, etc., would bring difficulties in bottom detection. Existing methods need manual parameter setups or to use postprocessing methods, which limits automatic and real-time processing in complex situations. To solve this problem, a one-dimensional U-Net (1D-UNet) model for sea bottom detection of side-scan data and the bottom detection and tracking method based on 1D-UNet are proposed in this work. First, the basic theory of sonar bottom detection and the interference factors is introduced, which indicates that deep learning of the bottom is a feasible solution. Then, a 1D-UNet model for detecting the sea bottom position from the side-scan backscatter strength sequences is proposed, and the structure and implementation of this model are illustrated in detail. Finally, the bottom detection and tracking algorithms of a single ping and continuous pings are presented on the basis of the proposed model. The measured side-scan sonar data in Meizhou Bay and Bayuquan District were selected in the experiments to verify the model and methods. The 1D-UNet model was first trained and applied with the side-scan data in Meizhou Bay. The training and validation accuracies were 99.92% and 99.77%, respectively, and the sea bottom detection accuracy of the training survey line was 99.88%. The 1D-UNet model showed good robustness to the interference factors of bottom detection and fully real-time performance in comparison with other methods. Moreover, the trained 1D-UNet model is used to process the data in the Bayuquan District for proving model generality. The proposed 1D-UNet model for bottom detection has been proven effective for side-scan sonar data and also has great potentials in wider applications on other types of sonars.

Single Ping Filtering of Multi-Beam Sounding Data Based on Alpha Shapes

AbstractFrom the standpoint of complex marine environments relative to underwater acoustic signal propagation, the application of multi-beam systems for the filtering and processing of multi-beam sounding data is critical. However, currently existing automatic filtering methods estimate data, which involve several calculations and require the respective computer to possess significant processing capabilities. In this study, raw data are measured using an interferometer multi-beam echo sounder, and the characteristics of the noise data are analyzed. The noise data are discontinuous; however, accurate data can be approximated as a continuous distribution. Under the assumption of continuous underwater terrain, in consideration of a circle of the appropriate radius rolling on the terrain profile, the continuous underwater terrain data can be extracted from the raw data by means of the alpha-shapes algorithm. Finally, on the basis of the measured data in a sail trial, the effectiveness of the proposed algorithm is verified.

Synchronous 3-D Imaging and Velocity Estimation of Underwater Targets Using Pulse-Pair Acoustical Imaging Technique

Velocity, position, and geometry are key parameters for sonar applications in underwater target detection, classification, and tracking. Current underwater 3-D acoustical imaging techniques can provide much more geometric details of the underwater targets by high-resolution acoustic images. However, they cannot conduct target velocity estimations simultaneously. Kinematic information (i.e., Doppler shifts) of the targets has been lost during imaging since these techniques are essentially developed for obtaining static images. Therefore, this article proposes a “pulse-pair” acoustical imaging (PPAI) technique to acquire geometry, velocity, and distance information of underwater targets simultaneously in a single ping. Instead of transmitting a single pulse to collect echoes from the underwater environment like the conventional acoustical imaging techniques, a “pulse-pair” transmission scheme is proposed to realize 3-D underwater imaging in the PPAI method. The radial velocities of underwater targets are estimated in all target-existing volumetric cells by a pulse-pair autocorrelation method. Considering that a pulse-pair transmission should cause duplication and a mixture of the original image (image blurring), a deconvolution algorithm is adopted to correct the mixed image. The performance of the proposed method is evaluated with a high-resolution 3-D PPAI prototype in a simulation underwater 3-D scenario. Simulation results show that 3-D geometry and velocity features, as well as distances of underwater targets, can be effectively acquired in a single ping with the proposed method. It is significant for sonar applications to avoid possible changes in target features over time due to the relatively long propagation time of sound.

Sequential pattern analysis for event-based intrusion detection

The events in information system framework ranges from a single mouse click or a single ping to highly heterogeneous network log files and are huge in size and unusual in nature. The events are sequential in nature and the sequence of events depicts the behaviour of the system. Due to this feature event analysis became a significant technique in anomaly detection in security. Sequential pattern analysis is a new area in event-based intrusion detection where the real time event sequences are analysed to see the abnormalities in a computer system. This paper modifies the generalised sequential patterns (GSP) algorithm to identify the highly repeating pattern in an event sequence. The paper then evaluates the algorithm performance by analysing the network event sequence that is created when any two nodes in a network communicates and identifies the pattern of different denial of service (DoS) and scanning attacks in a network.

Single Ping Clutter Reduction Algorithm Using Statistical Features of Peak Signal to Improve Detection in Active Sonar System

In active sonar system, clutters degrade performance of target detection/tracking and overwhelm sonar operators in ASW (Antisubmarine Warfare). Conventional clutter reduction algorithms using consistency of local peaks are studied in multi-ping data and tracking filter research for active sonar was conducted. However these algorithms cannot classify target and clutters in single ping data. This paper suggests a single ping clutter reduction approach to reduce clutters in mid-frequency active sonar system using echo shape features. The algorithm performance test is conducted using real sea-trial data in heavy clutter density environment. It is confirmed that the number of clutters was reduced by about 80 % over the conventional algorithm while retaining the detection of target.

Searching for seafloor massive sulfides: a quantitative review of high-resolution methods in deep sea sonar bathymetry for mining applications

Seafloor massive sulphides are deep sea mineral deposits currently being examined as a potential mining resource. Conventional sonar bathymetry products gathered by sea surface platforms do not achieve adequate spatial resolution to detect these resources. High-resolution beamforming methods (such as multiple signal classification and estimation of signal parameters via rotational invariance techniques) improve the resolution of sonar bathymetry. We perform a quantitative review of these high-resolution methods using a novel simulator, showing results in the absence of platform motion for a single ping cycle. It was found that high-resolution methods achieved greater bathymetric accuracy and higher resolution than conventional beamforming and that these methods may be adequate for this style of marine exploration. These methods were also robust in the presence of unwanted persistent signals and low signal to noise ratios.

Phased Array Velocity Sensor Operational Advantages and Data Analysis

In recent years the underwater navigation industry has expanded into more diverse and unique applications requiring a greater capability from its platform sensor set. Teledyne RD Instruments has answered the demand with a new patented Phased Array technology to be used as part of the growing Doppler Velocity Log and Acoustic Doppler Current Profiler Product Lines. The new Phased Array utilizes a single array transducer composed of multiple elements where four individual acoustic beams are electronically formed at their defined angles. In contrast the existing piston transducer technology utilizes the four individual ceramics where each beam is projected at its respective mounting angle. This yields the opportunity to increase the size of the single array while reducing the overall transducer size giving way for the characteristics which provide for operational improvement.These unique advantages and benefits are outlined in a user centric focus. Through substantial research and development our engineers have designed a method through a filled array process to pressure rate the transducer to a depth of 1000 meters. In terms of the mechanical configuration the attributes are represented and shown how the single phased array contributes to the system design and integration to allow for improved platform cohesion. Furthermore the variables that affect the systems integration and data collection are presented in both a theoretical and experimental means. This is defined by bandwidth and effective speed of sound.Teledyne RD Instruments has been continuing to work towards operational improvement and as such have two products available with our Phased Array transducers, the Explorer DVL and our new PAVS150. The Explorer DVL is tested to compare the piston transducer with our Phased Array transducer option. In this comparison the data will be examined where features such as maximum bottom tracking range, maximum current profiling range, standard deviation vs. altitude and standard deviation vs. bin size. Furthermore the recently released PAVS150 which boasts a bottom tracking range in excess of 500 meters takes to the ocean to define its capabilities. The compact and powerful PAVS150 uses our proven bottom detection algorithms and single ping bottom location capability with its broadband velocity processing technology to provide high-precision velocity data for reliable navigation and position processing in a highly robust and reliable manner over any indeterminate terrain.

A waveguide invariant adaptive matched filter for active sonar target depth classification

This paper addresses depth discrimination of a water column target from bottom clutter discretes in wideband active sonar. To facilitate classification, the waveguide invariant property is used to derive multiple snapshots by uniformly sub-sampling the short-time Fourier transform (STFT) coefficients of a single ping of wideband active sonar data. The sub-sampled target snapshots are used to define a waveguide invariant spectral density matrix (WI-SDM), which allows the application of adaptive matched-filtering based approaches for target depth classification. Depth classification is achieved using a waveguide invariant minimum variance filter (WI-MVF) which matches the observed WI-SDM to depth-dependent signal replica vectors generated from a normal mode model. Robustness to environmental mismatch is achieved by adding environmental perturbation constraints (EPC) derived from signal covariance matrices averaged over the uncertain channel parameters. Simulation and real data results from the SCARAB98 and CLUTTER09 experiments in the Mediterranean Sea are presented to illustrate the approach. Receiver operating characteristics (ROC) for robust waveguide invariant depth classification approaches are presented which illustrate performance under uncertain environmental conditions.

Discriminating Multiple Nearby Targets Using Single-Ping Ultrasonic Scene Mapping

We present a software simulation and a hardware proof of concept for a compact low-power lightweight ultrasonic echolocation design that is capable of imaging a 120 field of view with a single ping. The sensor uses a single transmitter and a linear array of ten microphones, followed by a bank of eight spatiotemporal filters to determine the bearing angle of returned echoes. The sensor is capable of detecting multiple objects with a single omnidirectional ping, even if their echoes interfere with each other at the microphone array. The hardware implementation detects the bearing of nearby objects with an rms accuracy of 1.6° and can reliably detect a 70-cm-long 5-cm-diameter metal table leg at a range of 3 m. Stronger reflectors, such as building corners, can be reliably detected at a range of 9 m.

Characterizing Response to Elemental Unit of Acoustic Imaging Noise: An fMRI Study

Acoustic imaging noise produced during functional magnetic resonance imaging (fMRI) studies can hinder auditory fMRI research analysis by altering the properties of the acquired time-series data. Acoustic imaging noise can be especially confounding when estimating the time course of the hemodynamic response (HDR) in auditory event-related fMRI (fMRI) experiments. This study is motivated by the desire to establish a baseline function that can serve not only as a comparison to other quantities of acoustic imaging noise for determining how detrimental is one's experimental noise, but also as a foundation for a model that compensates for the response to acoustic imaging noise. Therefore, the amplitude and spatial extent of the HDR to the elemental unit of acoustic imaging noise (i.e., a single ping) associated with echoplanar acquisition were characterized and modeled. Results from this fMRI study at 1.5 T indicate that the group-averaged HDR in left and right auditory cortex to acoustic imaging noise (duration of 46 ms) has an estimated peak magnitude of 0.29% (right) to 0.48% (left) signal change from baseline, peaks between 3 and 5 s after stimulus presentation, and returns to baseline and remains within the noise range approximately 8 s after stimulus presentation.

Recognizing holographic perception.

Recent robotics work has demonstrated that the holographic property of synthetic aperture sonar images can be used to enable object or terrain recognition using real aperture sonars. For instance, it was shown using Gulf of Mexico data from the small synthetic aperture minehunter that terrain can be recognized using as little as a single sonar element and a single ping. Similar capabilities have been ascribed to marine mammals, raising questions about whether the techniques are similar. This paper describes the basics of holographic perception and a series of experiments, which can be used to rule out its use.

Case Study of Precision of GPS Differential Correction Strategies: Influence on aDcp Velocity and Discharge Estimates

The precision of four differential global positioning systems (DGPS) was evaluated in the context of fluvial water velocity and discharge measurement. DGPS is used to resolve water velocities measured with an acoustic Doppler current profiler (aDcp) into earth coordinates if bottom tracking is unavailable. The DGPS systems assessed were: (1) the dual frequency real time kinematic (RTKL1L2); (2) the single frequency real time kinematic (RTKL1); (3) the code-phase Canadian Coast Guard (CG); and (4) the code-phase Wide Area Augmentation System (WAAS). Repeat discharge surveys (n=22) were conducted at a transect of the Gatineau River, Canada, simultaneously collecting bottom track boat velocity ( vBT ) and boat velocity from all four DGPS ( vDGPS ) . The mean absolute single ping differences between vBT and vDGPS were 3.1 (RTKL1L2), 3.2 (RTKL1), 8.9 (CG), and 9.8 cm∕s (WAAS). Errors were observed more often near channel margins, presumably due to obstruction and multipath associated with riverbank vegetation ...

Environmentally associated signal-to-interference variability in low-frequency active sonar in Korea Strait

An analysis has been conducted of spatial and temporal variability of target echo-to-interference measurements made during Area Characterization Test III (ACT III) in 1995 in the Korea Strait. The measurements were made over a 5-day period for five fixed bistatic geometries (spatial scale of order 200 square km) using explosive sources, bottom-mounted horizontal receiving hydrophone arrays, and passive reflector targets in 100-m-depth water under downward-refracting acoustic conditions. The bottom at the ACT III site was nearly flat, of sand–silt composition. Meteorological conditions were relatively calm over the conduction of the measurements, but the main proximate oceanographic feature, the South Korean Coastal Front, did result in a relatively varied and complex sound-speed environment. The signal-to-interference fluctuation statistics associated with a single ping was determined to give a standard deviation of order 1 dB, while the observed variability of signal-to-interference over the spatial and temporal scales of the measurements gave a standard deviation of about 2 dB. The observed variability of received signal-to-interference will be discussed in terms of physical causes and measurement error. [Work supported by ONR Code OA321.]

The comb waveform as an efficient method for wideband transducer measurements

An efficient acoustic calibration technique based on a uniformly weighted comb waveform is presented. The method takes advantage of the linear, time invariant nature of the measurement configuration and the comb’s wide bandwidth to capture all spectral components of interest for a device under test in a single ping. Measured results comparing single ping comb measurements with conventionally obtained tonal measurements are presented. The examples given illustrate the accuracy and utility of this technique for the calibration of broadband systems.

Adaptive Array Processing for Wide-Band Active Sonars

A high-frequency sector scan sonar can be used to detect and classify man-made objects located on the sea floor. If the hydrophone array of the sonar is to be mounted on a miniaturized autonomous underwater vehicle, the aperture size of the array must be small enough so that it will not affect the vehicle's maneuverability. However, a small aperture size of the array results in poor angular resolution when using the conventional delay and sum beamforming technique. This paper shows that, with the aid of spatial resampling, narrow-band adaptive beamforming algorithms can be applied to improve the angular resolution of wide-band active sonars with a small aperture uniform linear hydrophone array. Owing to the motion of the vehicle and the highly nonstationary environment, only single-snapshot adaptive beamforming algorithms can be used. In this paper, spatial smoothing is used in conjunction with the minimum variance distortionless response and multiple signal classification adaptive beamforming algorithms to produce a high-resolution image using a single ping. Real sonar images generated using these two algorithms are compared with those generated using another single-snapshot adaptive beamforming algorithm, spatial processing: optimized and constrained, and the conventional delay and sum beamforming algorithm.

Displaced ping imaging autofocus for a multi-hydrophone SAS

The problems caused by random sway errors in the tow-path of a single hydrophone, synthetic aperture sonar (SAS) are well known. If these horizontal displacement errors are left uncorrected and the tow-path is assumed to be straight, they have a devastating effect on the quality of the reconstructed image. Although on-board navigation instruments can help measure the gross departures from the straight path, sub-wavelength residual sway errors still corrupt the imaging process. More recent SAS systems have an array of receiving hydrophones and are effected by both random sway and yaw errors and again navigation instruments cannot always estimate the yaw and sway to the accuracy required to remove the effects. Current autofocus (sometimes called ‘micronavigation’) techniques to estimate the sway and yaw from the raw (i.e. distorted) data rely on there being significant overlap of the hydrophone array between pings and so the SAS travels at much less than its maximum allowable speed (as determined by spatial sampling considerations). The requirement for significant overlap compromises the maximum achievable mapping rate. The authors show how the distorted raw data from a multi-hydrophone SAS can be used to estimate the sway and yaw even when the sonar is travelling at the maximum allowable speed. The mathematical framework is outlined using the wavenumber algorithm, modified for a multiple hydrophone-receiver SAS, as the final method of image reconstruction. The nub of the proposed autofocusing algorithm is the formation of individual images from each separate ping. These single-ping images from adjacent pings are then cross-correlated to determine how the sonar has moved between pings. Thus the differential yaw and differential sway can be estimated from a series of displaced single ping images and this process forms the basis of displaced ping imaging autofocus (DPIA). Using simulated, distorted SAS data as input, the proposed DPIA algorithm shows promise in that it can estimate yaw with sufficient accuracy to restore distorted SAS images close to their diffraction limit.

The comb waveform as an efficient method for wideband measurements

An efficient acoustic calibration technique based on a uniformly-weighted comb waveform is presented. The method takes advantage of the linear, time invariant nature of the measurement configuration and the comb’s wide bandwidth to capture all spectral components of interest for a device under test in a single ping. Results comparing single ping comb measurements with conventionally obtained CW measurements are presented. The examples given illustrate the accuracy and utility of this technique for the calibration of broadband systems.