Ambiguity Surface Research Articles

Reformulation of frequency-difference matched-field processor for high-frequency known-source localization.

Frequency-difference matched-field processing is a high-frequency source localization technique formulated by matching the frequency-difference autoproduct of the measured field and replicas at the difference-frequency. Although it successfully localizes sound sources by sparse vertical array in shallow or deep ocean with an environmental mismatch, there is still some ambiguity in replica modeling and signal processing. Here, the existing conventional processor is modified to match the bandwidth-averaged autoproduct of the measured field with replicas of the bandwidth-averaged autoproduct, or approximately its self-term for the expected source locations. The proposed processor is consistent with the perspective of matched-field processing and can naturally relieve some drawbacks of the existing one, such as low peak or low dynamic range on the ambiguity surface. Numerical tests are carried out in several shallow ocean environments and the source localization using experimental data are performed to confirm the properties of the proposed processor. It is found that the high-frequency diffracted field always leaves traces on its bandwidth-averaged autoproduct field. These high-frequency marks cause a bias in source localization in the presence of a sound speed mismatch even in low difference-frequencies.

Correlation-based passive localization: Linear system modeling and sparsity-aware optimization.

In underwater passive localization, matched field processing has faced mismatch challenges for many years. To overcome the mismatch, data-derived replicas have gained increasing popularity due to their better localization performance than parameter-based ones, among which the cross correlation-based replicas showed enhanced robustness against the spectral differences between the library and target vessels. However, cross correlation-based matching localizations result in high sidelobes and require enough frequency samples to eliminate grating lobes. This issue has been widely reported in the previous literature but has yet to be theoretically analyzed. In this work, we revisit the conventional correlation-based matching procedures and formulate the ambiguity surface as a least-norm solution of an underdetermined linear system. This formulation permits understanding the sidelobes from an optimization perspective. Based on this view, the high sidelobe challenge and requirement of measurements are systematically tackled by recasting the matching problem as a sparsity-aware optimization problem. The superiority of the proposed optimization approach is showcased through simulated data in the waveguide, microphone data in the air, and SWellEx-96 data. The linear system modeling is also extended to a distributed sensor network, profiting from the spatial gain brought by various azimuthal directions with respect to the source.

Difference frequency coherent matched autoproduct processing for source localization in deep ocean

Matched autoproduct processing (MAP) refers to a matched field processing (MFP) style array signal processing technique for passive source localization, which interrogates frequency-difference autoproduct instead of genuine acoustic pressure. Due to frequency downshifting, MAP is less sensitive to environmental mismatch, but it suffers from low spatial resolution and a low peak-to-sidelobe ratio of ambiguity surface. These source localization metrics are herein improved with coherent approaches. Specifically, the coherent normalized MFP is extended to coherent matched autoproduct processing (CMAP), a difference frequency coherent algorithm that exploits correlations among the autoproducts at various difference frequencies and eliminates the phase factor of the source spectrum for passive source localization. Phase-only coherent matched autoproduct processing is a CMAP derivation technique that only uses phase information. Through simulations in a Munk sound-speed profile environment, sensitivity analysis in the South China Sea environment, and high signal-to-noise ratio experimental measurements, these two algorithms are validated as compared to the conventional MFP and incoherent MAP. Simulation investigations demonstrate that difference frequency coherent algorithms can suppress sidelobes while simultaneously enhancing the localization resolution and robustness. The experimental results generally support the findings of the simulations.

Reducing ambiguities in single-hydrophone matched-field processing by exploiting source motion

Matched-field processing for localizing an underwater acoustic source in range and depth from power-spectrum measurements obtained at a single hydrophone receiver often suffers from high side-lobes and ambiguities when the signal is narrowband or signal bandwidth is small. In this paper we review how source motion can be utilized to reduce side-lobes in depth and range via an incoherent synthetic-aperture-like approach and explain the mechanisms responsible for side-lobe reduction relative to the height of the main-lobe by using a normal-mode expansion for the pressure field. We also derive an approximation for the depth main-lobe width when the true source range is known for the ideal rigid-waveguide case. Numerical results are presented corroborating the analytical analysis along with some matched-field localization ambiguity surface examples for (a) an ideal shallow-water waveguide with a pressure-release top boundary and a rigid bottom boundary and (b) a more realistic shallow-water Pekeris environment, to demonstrate how side-lobes and ambiguities are reduced when source motion is exploited in the matched-field processing.

Shallow sea matching field continuous tracking method based on trajectory Poisson multi-Bernoulli hybrid filter

In the shallow water waveguide, matched field tracking methods use the continuity of the peak position of the moving source and the disorder of pseudo-peaks on the sequential ambiguity surfaces to track the underwater source trajectory. However, owing to the dual influence of the space-time fluctuating shallow water waveguide environment and the complex sources motion scene, the existing matching field tracking methods are prone to track interruption, switches and false track phenomena, leading to discontinuous tracking results. Using the consistency between the peak position distance likelihood and the peak amplitude likelihood of sequential ambiguity surfaces, a continuous matched field tracking method is proposed based on the trajectory Poisson multi-Bernoulli mixture filter in this paper. The proposed method is applied to SWellEx-96 experimental data, and the tracking performance is measured by the linear programming metric. The results show that compared with the existing matching field tracking method and multi-target tracking method via random finite set, the proposed method achieves continuous tracking and accurate quantity estimation of moving sources trajectory. Among them, the prediction step and updating step in the trajectory space can avoid the phenomenon of trajectory interruption and switches in unvoiced periods.

Resolution of matched field processing for a single hydrophone in a rigid waveguide.

This paper studies resolution of matched field processing for locating, in range and depth, a broadband underwater acoustic source from data measured at a single hydrophone receiver. For the case of an ideal rigid shallow-water waveguide with a pressure-release top boundary and a rigid bottom boundary, the paper derives approximations for the main-lobe widths of the ambiguity surface. The two cases studied in this paper are (1) when coherent measurements of the pressure are available, with the transmitted source waveform precisely known, and (2) when only measurements of the received-signal pressure magnitude-squared are available, such as might occur when the transmitted signal is random and unknown. The analysis uses the normal-mode expansion for the pressure field to derive approximate expressions for the ambiguity-surface main-lobe widths, as a function of the number of modes and frequency band, for both range and depth. Numerical results are presented corroborating the analytical analysis. Finally, the paper argues that this ambiguity analysis can also give insights into Pekeris waveguides under appropriate conditions and shows numerical simulations of matched-field localization ambiguity surfaces for some realistic shallow-water Pekeris environments.

Accurate Passive 3D Polarization Face Reconstruction under Complex Conditions Assisted with Deep Learning

Accurate passive 3D face reconstruction is of great importance with various potential applications. Three-dimensional polarization face reconstruction is a promising approach, but one bothered by serious deformations caused by an ambiguous surface normal. In this study, we propose a learning-based method for passive 3D polarization face reconstruction. It first calculates the surface normal of each microfacet at a pixel level based on the polarization of diffusely reflected light on the face, where no auxiliary equipment, including artificial illumination, is required. Then, the CNN-based 3DMM (convolutional neural network; 3D morphable model) generates a rough depth map of the face with the directly captured polarization image. The map works as an extra constraint to correct the ambiguous surface normal obtained from polarization. An accurate surface normal finally allows for an accurate 3D face reconstruction. Experiments in both indoor and outdoor conditions demonstrate that accurate 3D faces can be well-reconstructed. Moreover, with no auxiliary equipment required, the method ensures a total passive 3D face reconstruction.

A safer and more practical tracheotomy in invasive mechanical ventilated patients with COVID-19: A quality improvement study.

The number of infections and deaths caused by the global epidemic of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) invasion is steadily increasing daily. In the early stages of outbreak, approximately 15%-20% of patients with coronavirus disease 2019 (COVID-19) inevitably developed severe and critically ill forms of the disease, especially elderly patients and those with several or serious comorbidities. These more severe forms of disease mainly manifest as dyspnea, reduced blood oxygen saturation, severe pneumonia, acute respiratory distress syndrome (ARDS), thus requiring prolonged advanced respiratory support, including high-flow nasal cannula (HFNC), non-invasive mechanical ventilation (NIMV), and invasive mechanical ventilation (IMV). This study aimed to propose a safer and more practical tracheotomy in invasive mechanical ventilated patients with COVID-19. This is a single center quality improvement study. Tracheotomy is a necessary and important step in airway management for COVID-19 patients with prolonged endotracheal intubation, IMV, failed extubation, and ventilator dependence. Standardized third-level protection measures and bulky personal protective equipment (PPE) may hugely impede the implementation of tracheotomy, especially when determining the optimal pre-surgical positioning for COVID-19 patients with ambiguous surface position, obesity, short neck or limited neck extension, due to vision impairment, reduced tactile sensation and motility associated with PPE. Consequently, the aim of this study was to propose a safer and more practical tracheotomy, namely percutaneous dilated tracheotomy (PDT) with delayed endotracheal intubation withdrawal under the guidance of bedside ultrasonography without the conventional use of flexible fiberoptic bronchoscopy (FFB), which can accurately determine the optimal pre-surgical positioning, as well as avoid intraoperative damage of the posterior tracheal wall and prevent the occurrence of tracheoesophageal fistula (TEF).

Improvement of a Sample Clock Offset Estimation Method Used in Passive Radar

Sample clock offset must be estimated in order to correctly demodulate an OFDM signal. Estimates are also required in passive radar processing, to produce a reference signal, which is properly matched to the transmission. A recently proposed clock offset estimation method for passive radar is found to be overly sensitive to measurement noise. However, the radar ambiguity surface is found to be unaffected by the specific errors engendered by this noise. The reasons for this are explored. An updated method based on state-space modeling and Kalman smoothing is proposed. This is found to restore clock offset estimation performance in cases of higher noise, achieving this with low processing latency. These improvements enable the method to be employed for other applications requiring high quality, time-critical clock offset estimation.

Resolution of matched field processing for a single hydrophone in a rigid waveguide

This paper studies resolution of matched field processing for locating, in range and depth, a broadband underwater acoustic source from data measured at a single hydrophone receiver. For the case of an ideal rigid shallow-water waveguide with a pressure-release top boundary and a rigid bottom boundary, we derive approximations for the main-lobe widths of the ambiguity surface. The two cases studied in this paper are (1) when coherent measurements of the pressure are available, with the transmitted source waveform precisely known, and (2) when only measurements of the received signal power spectral density (PSD) are available, such as occur when the transmitted signal is random and unknown. The analysis uses the normal-mode expansion for the pressure field to derive approximate expressions for the ambiguity surface main-lobe widths, as a function of the number of modes and frequency band, for both range and depth. Numerical results are presented corroborating the analytical analysis. Finally, we argue that this ambiguity analysis also gives insights into real ocean waveguide localization characteristics under appropriate conditions, and show numerical simulations of matched field localization ambiguity surfaces for some realistic shallow-water Pekeris environments.

Passive Radar Signal Processing in the Presence of Sample Clock Offset

Passive radar signal processing is hindered by the need to sample a reference signal from the chosen illuminator, which is subject to sensor noise and interference from clutter returns. The reference signal may be demodulated and reconstructed to remove artifacts. However, without accounting for the transmitter's clock offset, the remodulated reference signal will be a poor match for the surveillance signal. This article evaluates clock offset estimation methods in terms of the radar ambiguity surface, thereby appraising them specifically for passive radar applications. Existing offset estimation methods are shown to meet variance bounds; however, these bounds worsen with increased clock offset. Ambiguity surfaces constructed from signals reconstructed with poor clock offsets exhibit power leakage. A new clock offset estimator is proposed, which refines coarse estimates made by an existing method. The new estimator is demonstrated to achieve accurate estimation of clock offset. Reference signals reconstructed with these estimates produce ambiguity surfaces with no significant power leakage.

Frequency-difference autoproduct cross-term analysis and cancellation for improved ambiguity surface robustness.

Frequency-differencing, or autoproduct processing, techniques are one area of research that has been found to increase the robustness of acoustic array signal processing algorithms to environmental uncertainty. Previous studies have shown that frequency differencing techniques are able to mitigate problems associated with environmental mismatch in source localization techniques. While this method has demonstrated increased robustness compared to conventional methods, many of the metrics, such as ambiguity surface peak values and dynamic range, are lower than would typically be expected for the observed level of robustness. These previous studies have suggested that such metrics are reduced by the inherent nonlinearity of the frequency-differencing method. In this study, simulations of simple multi-path environments are used to analyze this nonlinearity and signal processing techniques are proposed to mitigate the effects of this problem. These methods are used to improve source localization metrics, particularly ambiguity surface peak value and dynamic range, in two experimental environments: a small laboratory water tank and in a deep ocean (Philippine Sea) environment. The performance of these techniques demonstrates that many source localization metrics can be improved for frequency-differencing methods, which suggests that frequency-differencing methods may be as robust as previous studies have shown.

Multi-Valued Eigen-Processing for Isolating Multiple Sources With a Rectangular Array

The multi-valued Bartlett (MVB) processor is useful for determining the locations of multiple acoustic sources in the ocean [J. Acoust. Soc. Am. 97, 235–241 (1995)]. This approach was originally applied to a vertical line array of hydrophones. The application to a rectangular array is explored here. The MVB processor is an eigen-processor that is based on the eigenvectors of the covariance matrix. It is multi-valued in the sense that an ambiguity surface is constructed for each member of a subset of the eigenvectors that correspond to the largest eigenvalues. The motivation for the approach is the fact that energy from different sources tends to partition into different eigenvectors. One of the advantages of the MVB processor on a rectangular array is that it is possible to determine if the partitioning is favorable without computing replica fields, which is often the most time-consuming task of matched-field processing computations. Examples are presented to illustrate the capabilities and limitations of the approach.

«Io sto bene, io sto male, io non so cosa fare». Generazione X, alternative rock e film di formazione anni Novanta

The paper investigates the “90s cult movies” compilation soundtracks of Enza Negroni’s “Jack Frusciante e uscito dal gruppo” (1996) and Davide Ferrario’s “Tutti giu per terra” (1997), both produced by Consorzio Produttori Indipendenti. It explores the relation between Generation X and 90s Italian films – a type of cinema that Vito Zagarrio defines «in transition» (2000), «with ambiguous forms and surfaces» (2002: 34) – through songs in the films as “Nuotando nell’aria” (Marlene Kuntz, 1994) and “A tratti” (C.S.I., 1994), which constitute the generational key and reestablish a three-dimensional realm, going beyond the image and “embodying” the characters’ “coming-of-age”.

On ambiguity function shaping for broadband constant-modulus signals

Constant-modulus signals such as m-sequences are known to have good autocorrelation properties, as well as good peak-to-average power ratio that allows for full utilization of the transmitter’s power. However, the broadband ambiguity surface for such signals exhibit high sidelobe levels that are undesirable in applications where the signal is subject to broadband Doppler. We formulate an optimization problem to minimize the maximum sidelobe levels of such signals over a set of delay-Doppler values. This problem is non-convex and difficult to solve. We explore a convex regularization of the problem that can readily be solved using semi-definite programming, and show that optimal or near-optimal signals can be designed using this method. We further explore some heuristic methods to reduce computational and memory complexity of the solution, to enable us to design longer signals. We demonstrate the advantage of our signal design over conventional unimodular signals for target detection in strong clutter in a continuous active sonar application.

Use of frequency-difference beamforming for scatterer localization

Acoustic fields interacting with discontinuities or environmental variations lead to secondary scattered fields superimposed onto incident fields. As a result, the signal measured at a remote receiving array will be modified by the scatterer’s presence. Prior work has shown that the effects of strong random scattering are reduced using frequency-difference beamforming to downshift the analysis to a below-band frequency known to be less impacted by scattering. In some applications, information about a scatterer is desired, such as location, shape, or composition. However, a relatively weak scattered field from a single scatterer is difficult to detect when the incident field dominates the measurements, as both conventional and frequency-difference beamforming ambiguity surfaces primarily provide the incident field’s source information. Here, a subtraction-based algorithm is implemented with frequency-difference beamforming to locate the position of a single scatterer near a source. Simulations and water tank experiments with a 110 kHz center frequency signal are considered for incident and scattered fields with a 4 cm diameter spherical scatterer, where the scattered field’s received energy is roughly 2% that of the incident field. The ability to downshift the frequency demonstrates a more robust implementation of subtraction-based algorithms for locating weak scatterers without prior location knowledge. [Work supported by ONR.]

Performance comparisons of array invariant and matched field processing using broadband ship noise and a tilted vertical array.

This paper compares the localization performance of array invariant (AI) and matched field processing (MFP) using a ship of opportunity radiating random noise (200-900 Hz) and a tilted vertical array. AI is a deterministic approach to source-range estimation (i.e., depth-blind), exploiting the dispersion characteristics of broadband signals with minimal/no knowledge of the environment in shallow water. It involves time-domain plane-wave beamforming to separate multiple coherent arrivals (eigenrays) in beam angle and travel time, called "beam-time migration," from which the source range is directly estimated. In contrast, MFP is a model-based approach that requires accurate knowledge of the environment and array geometry (e.g., array tilt) to generate "replicas" for all possible source locations, finding the best match in the two-dimensional ambiguity surface of range and depth. While AI and MFP are both sensitive to array tilt, AI is equipped with self-calibration capability to estimate the array tilt and source range simultaneously. With the array tilt information from AI incorporated, the performance of MFP for range estimation can be comparable to that of AI to such an extent that the environmental knowledge is accurate.

Estimating North Pacific Right Whale calling depths in the Bering Sea via modal dispersion

Calling depth distributions and ranges are estimated for two types of calls produced by critically endangered eastern North Pacific right whales (NPRW) in the Bering Sea, using passive acoustic data collected with bottom-mounted single-hydrophone recorders at the 50 m isobath. Nonlinear time resampling of 12 NPRW “upcalls” and 20 broadband “gunshots” typically isolated 3 to 4 individual mode arrivals below 200 Hz. Matched-mode processing (MMP) methods were then used to estimate range, depth, and propagation environment. When plotted as a function of range and frequency, MMP ambiguity surfaces reveal the existence of large sound speed gradients in the sediment, along with strongly downward-refracting sound speed profiles during certain summer/fall seasons. Refractive propagation effects from these profiles can induce dramatic changes in signal structure that required new developments in “warping” techniques. Gunshot sounds were generally produced at a few meters depth, while upcall depths clustered between 10 and 25 m, consistent with previously published bioacoustic tagging results from North Atlantic right whales. Current work is examining whether consistent differences exist in the calling depths of bowhead, humpback, and right whales, which could potentially provide a feature for species classification of ambiguous calls. [Work sponsored by NPRB.]

Interactional Dynamics in Teams Marked with Power Ambiguity

This paper sheds light on the power dynamics and how work gets done in teams working towards a common goal. Based on an ethnographic study of a software development team, dispersed in 3 locations – US, and Bangalore and Jaipur in India, we found that long-term, sustained states of power ambiguity are normal. Ambiguity is inherent in the importance of the tasks performed by the various sub-teams and in understandings of who is dependent upon whom to achieve the common goal. When this ambiguity surfaces, ‘power claiming behaviors’ are often enacted to resolve the ambiguity, such that temporary power hierarchies may be defined in the situation. Provisional settlements are achieved either by the situationally higher power sub-team making a decision or by postponement of discussion on the topic. We describe these dynamics and how works gets accomplished in situations with power ambiguity among sub-teams.

Does SAE have /flap/? Evidence from Canadian Raising and Vowel Durations

In American English, /t/ and /d/ neutralize to flaps intervocalically: write ∼ writer and ride ∼ rider. There also exist words which contain ambiguous surface flaps that do not alternate, for example, the name Ryder. Does the language user treat this flap like an allophone of /t/ or /d/ (as predicted by the Free Ride Principle), or as an independent segment (as predicted by Lexicon Optimization)? To investigate this question, acoustic data from elicited (Experiment 1) and spontaneous (Experiment 2) speech are analyzed. Voiceless consonants cause the vowel preceding them to be shorter and trigger Canadian Raising. Therefore, if language users treat non-alternating flaps as allophones of /t/, the vowel durations and F1 trajectories of the vowels in these two environments will be similar to each other and different from before flapped /d/, and vice versa if language users treat non-alternating flaps as allophones of /d/. If language users treat non-alternating flaps as different than both the flap allophones of /t/ and /d/, vowel durations and F1 will be different in all three environments. Results show that the durations and F1 trajectories of the vowels in the three environments are all different from each other, providing evidence for Lexicon Optimization.