Ann Elisabeth Albright Blomberg

Improving Sonar Performance in Shallow Water Using Adaptive Beamforming

Multipath propagation degrades the performance of active, bottom-imaging sonars in shallow-water environments. One way to avoid multipath interference is to use a vertical array with a narrow enough angular response to separate the direct bottom return from the multipath. However, this requires a large array and is often infeasible for practical reasons. In this study, we focus on the use of adaptive beamforming on the receiver side to reduce multipath interference and hence improve the signal-to-noise ratio (SNR). Using a small, dense receiver array, we apply classical and adaptive beamformers to real data collected by the NATO Undersea Research Centre in a shallow-water environment. Our results show that the adaptive minimum variance distortionless response (MVDR) beamformer offers an improvement in the estimated SNR compared to a conventional beamformer in most cases. However, the MVDR beamformer is suboptimal when the receiver consists of only a few elements. We propose using the low complexity adaptive (LCA) beamformer, which is based on the same optimization criteria as the MVDR beamformer, but is robust in a coherent environment without the need for spatial smoothing. For two to 4-element receivers, we observe an improvement of about 0.5-2.5 dB in the estimated SNR when using the LCA beamformer. In cases where the model indicates that the direct bottom return and the dominating multipath arrive from nearly the same angle, little or no improvement is observed. This is typically the case for first- or second-order multipaths reflected off the seafloor toward the receiver. The results from this study also show that with a small vertical array, a narrow mainlobe width is more important than low sidelobe levels, in terms of maximizing the SNR. Consequently, an unweighted conventional beamformer performs better than a conventional beamformer with a Hanning window applied for sidelobe suppression.

Adaptive Beamforming Applied to a Cylindrical Sonar Array Using an Interpolated Array Transformation

In applications such as fishery sonar and navigation, cylindrical or spherical arrays are often used because of the need for a 360° field of view. However, adaptive beamforming methods, known for their high angular resolution and interference rejection capabilities, often rely on a Vandermonde structure of the steering vectors. This is generally not the case for nonlinear arrays. In this paper, we use an interpolated array transformation to map the data to a virtual linear array before adaptive beamforming. We evaluate the performance of two different adaptive beam- formers using simulations as well as experimental data from the SX90 fish finding sonar. We show that the adaptive minimum variance (MV) and amplitude and phase estimation of a sinusoid (APES) beamformers offer a significant improvement in azimuth resolution compared to the conventional delay-and-sum (DAS) beamformer. The APES beamformer offers slightly more reliable amplitude estimates in the direction of interest compared to the MV beamformer, at the cost of a somewhat lower azimuth resolution. When applied to data from the SX90 fish finding sonar, the MV beamformer offers a 40%-50% improvement in resolution, while the APES beamformer offers an improvement of 20%-30%.

APES beamforming applied to medical ultrasound imaging

Recently, adaptive beamformers have been introduced to medical ultrasound imaging. The primary focus has been on the minimum variance (MV) (or Capon) beamformer. This work investigates an alternative but closely related beamformer, the Amplitude and Phase Estimation (APES) beamformer. APES offers added robustness at the expense of a slightly lower resolution. The purpose of this study was to evaluate the performance of the APES beamformer on medical imaging data, since correct amplitude estimation often is just as important as spatial resolution. In our simulations we have used a 3.5 MHz, 96 element linear transducer array. When imaging two closely spaced point targets, APES displays nearly the same resolution as the MV, and at the same time improved amplitude control. When imaging cysts in speckle, APES offers speckle statistics similar to that of the DAS, without the need for temporal averaging.

Automatic Detection of Marine Gas Seeps Using an Interferometric Sidescan Sonar

There is a significant need for reliable, cost-effective, and preferably automatic methods for detecting and monitoring marine gas seeps. Seeps at the seafloor may originate from natural sources including sediments releasing biogenic methane and volcanoes releasing CO2, or from man-made constructions such as pipelines or well heads, and potentially also from subseafloor CO2 storage sites. Improved seep detection makes it possible to estimate the amount of greenhouse gases entering the oceans, and to promptly detect and address potential leaks to reduce environmental and economical consequences. Sonar is an excellent tool for seep detection due to the strong acoustic backscatter properties of gas-filled bubbles in water. Existing methods for acoustic seep detection include multibeam and sidescan surveying, as well as active and passive sensors mounted on a stationary platform. In this work, we develop a new method for automatic seep detection using an interferometric sidescan sonar. We apply signal processing techniques combined with knowledge about acoustical and spatial properties of seeps for improved detectability. The proposed method fills an important gap in existing technology—the ability to automatically detect a seep during a single pass with an autonomous underwater vehicle (AUV) equipped with an interferometric sidescan sonar. Results from simulations as well as field data from two leaking abandoned wells in the North Sea indicate that small seeps are consistently detected on a sandy seafloor even when the observation time is limited (a single pass with the AUV). We explore the detection capability for different seafloor types ranging from silt to gravel.

Adaptive Sonar Imaging Using Aperture Coherence

A class of computationally efficient adaptive imaging methods originating from the coherence factor (CF) has been proposed for improved medical ultrasound imaging. These methods are based on the idea that when steering the receiver toward a point of interest, the backscattered energy from this point exhibits a high degree of aperture coherence, while random noise, multipath interference, and sidelobe energy do not. Aperture coherence can be understood as a normalized measure of the degree of signal variability across the receiver array. This paper presents a study of the use of aperture-coherence-based methods for improved sonar imaging, with particular emphasis on a recently introduced robust implementation known as the scaled Wiener postfilter (SWiP). We show that while the CF has strong noise suppression capabilities and performs well on point targets, it lacks robustness in low signal-to-noise ratio (SNR) scenarios and introduces undesirable artifacts in speckle scenes. The SWiP is closely related to the CF, but contains a single-user-defined parameter, which allows the method to be tuned to suit the application needs. The SWiP can be tuned to offer robustness in a speckle environment such as when imaging the seafloor, or for strong noise suppression capabilities. This makes it a promising method for a wide range of sonar applications. We base our conclusions on simulated data from a constructed speckle scene as well as experimental data from the SX90 fish-finding sonar and sidescan data from the HISAS 1030 sonar. Our results show that the SWiP offers improved edge and shadow definitions and reduced sidelobe levels when compared to the conventional delay-and-sum (DAS) beamformer. These improvements do not compromise the image resolution, and they come at a low computational cost.

Multipath reduction for bathymetry using adaptive beamforming

In this paper we consider adaptive beamforming techniques to suppress the dominant multipath for a multielement interferometric synthetic aperture sonar. We use a broadband variant of the minimum variance (MV) beamformer and apply it to reconstruct bathymetry using data from the KiwiSAS-4 sonar. This has three vertically displaced hydrophone arrays. The MV beamformer is used to estimate the angle of arrival of the backscattered echo from the sea floor, and from that the height of the sea floor. The conventional delay-and-sum (DAS) beamformer is used for comparison.

Improved Visualization of Hydroacoustic Plumes Using the Split-Beam Aperture Coherence

Natural seepage of methane into the oceans is considerable, and plays a role in the global carbon cycle. Estimating the amount of this greenhouse gas entering the water column is important in order to understand their environmental impact. In addition, leakage from man-made structures such as gas pipelines may have environmental and economical consequences and should be promptly detected. Split beam echo sounders (SBES) detect hydroacoustic plumes due to the significant contrast in acoustic impedance between water and free gas. SBES are also powerful tools for plume characterization, with the ability to provide absolute acoustic measurements, estimate bubble trajectories, and capture the frequency dependent response of bubbles. However, under challenging conditions such as deep water and considerable background noise, it can be difficult to detect the presence of gas seepage from the acoustic imagery alone. The spatial coherence of the wavefield measured across the split beam sectors, quantified by the coherence factor (CF), is a computationally simple, easily available quantity which complements the acoustic imagery and may ease the ability to automatically or visually detect bubbles in the water column. We demonstrate the benefits of CF processing using SBES data from the Hudson Canyon, acquired using the Simrad EK80 SBES. We observe that hydroacoustic plumes appear more clearly defined and are easier to detect in the CF imagery than in the acoustic backscatter images.