Uncertainty tolerance in underwater acoustic signal processing

This is a collection of articles written by members of the Underwater Acoustic Signal Processing (UASP) Technical Committee. The first article, by D. W. Tufts, deals with the history of UASP prior to 1980. In this period, initial mathematical models were developed and the first experimental investigations of underwater acoustic propagation were performed. It was also recognized during this time that there are many similarities between radar and sonar signal processing. The article by J.P. Ianniello deals with research in passive and active sonar from 1980 to the present. Work in this period included experimental verification of algorithms that had been developed in the 1960s and 1970s (e.g. for adaptive beamforming), as well as the development of new approaches, which include acoustic propagation modeling in the design of signal processing algorithms. Such processing is referred to as matched field processing. A common task in passive sonar systems is to estimate the difference in times at which different sensors receive the same signal. Time-delay estimation is a first stage that feeds into subsequent processing blocks. I. Lourtie provides a concise review of work in this field. The article by J.C. Preisig deals with underwater acoustic communications. The underwater channel has several features that make reliable communication a challenging problem. Nevertheless, progress is being made by combining results from ocean acoustic modeling, communication theory, and signal processing. The final article, by J.M.F. Moura, deals with the future of signal processing in the ocean. In addition to considering advances in detection and localization, he deals with new applications such as acoustic tomography, physical oceanography, and synthetic aperture sonar.

In the past, both theoretical work and practical implementation of particle filtering (PF) method have been extensively studied. However, its application in underwater signal processing has received much less attention. This paper intends to introduce PF approach for underwater acoustic signal processing. Particularly, we are interested in direction of arrival (DOA) estimation using PF. A detailed introduction along with this perspective is presented in this paper. Since the noise usually spreads the mainlobe of likelihood function and causes problem in subsequent particle resampling step, an exponential weighted likelihood model is developed to emphasize particles at more relevant area. Hence, the the effect due to background noise can be reduced. Real underwater acoustic data collected in SWELLEx-96 experiment are employed to demonstrate the performance of the proposed PF approaches for underwater DOA tracking.

It is well known that underwater acoustic channels are particularly complicated and difficult for typical signal processing procedures due to the time-varying, homogeneous volume, rough boundaries, and the abundance of interference noise sources in these channels. Most traditional methods of statistical signal processing employ simplified assumptions (linear, stationary, Gaussian) for the sake of mathematical tractability that inevitably lead to inadequate performance.

With the rapid development and progress of information technology and the wide usage of audio signal processing in underwater acoustic signal processing, acoustic audio signal acquisition, conversion, and transmission technology always play an important role. To enhance the ability of signal acquisition and conversion with high reliability, this paper designs an embedded multi-channel audio conversion module. The module achieves multi-channel, multi-sample rates with synchronous analog-to-digital/digital-to-analog conversion (ADC/DAC) function, and additionally equips with dual network redundancy. The module uses a chip integrated with ARM and programmable logic FPGA as the main control chip. The writing of the underlying driver and application code ensures the reliable operation of the DAC chip and ADC chip and the steady of the network transmission. Through experimental verification, the audio conversion module performs well in multi-channel and multi-sample rates with synchronous ADC/DAC, and the crosstalk between channels is less than -50 dB. The dual network redundancy design and the application of the RS232 serial port ensure the high fidelity, reliability, and reprogramming of the audio conversion function, which shows the design can be used in a wide range of scenarios.

In underwater acoustic signal processing, direction of arrival (DOA) estimation can provide important information for target tracking and localization. To address underdetermined wideband signal processing in underwater passive detection system, this paper proposes a novel underdetermined wideband DOA estimation method equipped with the nested array (NA) using focused atomic norm minimization (ANM), where the signal source number detection is accomplished by information theory criteria. In the proposed DOA estimation method, especially, after vectoring the covariance matrix of each frequency bin, each corresponding obtained vector is focused into the predefined frequency bin by focused matrix. Then, the collected averaged vector is considered as virtual array model, whose steering vector exhibits the Vandermonde structure in terms of the obtained virtual array geometries. Further, the new covariance matrix is recovered based on ANM by semi-definite programming (SDP), which utilizes the information of the Toeplitz structure. Finally, the Root-MUSIC algorithm is applied to estimate the DOAs. Simulation results show that the proposed method outperforms other underdetermined DOA estimation methods based on information theory in term of higher estimation accuracy.

: The reports cover progress to develop signal processing structure that exploits available knowledge of the environment and of signal and noise variability induced by the environment. The research is directed toward passive sonar detection and classification, continuous wave (CW) and broadband signals, shallow water operation, both platform-mounted and distributed systems, and frequencies below 1 kHz. The results of this research are expected to lead to new passive sonar detectors and classifiers that take advantage of knowledge of medium variability and uncertainty. The results are mainly applicable to passive processing. However, the active processor can be considered a detector matched to the estimated ocean. These results could have significant impact on Navy sonar system applications.

SONAR Systems and Underwater Signal Processing: Classic and Modern Approaches

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The detection of tonal signals with unknown frequencies is an important area of study in underwater signal processing. A common approach to address this issue is to use the Discrete Fourier Transform (DFT) for observations. When a tone does not lie precisely at the discrete DFT frequency point, its energy will leak to adjacent frequency point. This phenomenon is known as scalloping loss or Picket Fence Effect (PFE). PFE leads to the degradation of detection performance based on DFT. This paper studies the problem of robust detection in the case of PFE. A coherently-averaged power processor utilizing the information of adjacent frequency bins is designed. The results of simulations and experiments show that the proposed method is robust against PFE, and is highly suitable for tone detection in practical circumstances.

In most of biomedical signal processing applications the presence of interference signals is inevitable. Processing of lung sounds is not an exemption. In this case the heart sounds are unavoidable and sometimes a severe disturbing noise source. Previous studies indicated that the performance of any interference cancellation scheme relies strongly on an adequate time delay estimation between the reference and the primary signals. Here, a new procedure for time delay estimation using the multi-resolution framework is presented. The proposed methodology possesses such key benefits as the multiple looks information of a signal at different bands, robustness in presence of noise and a validation procedure for the delay estimates. The procedure is applicable to a broad range of problems where time delay estimation is required. Results obtained with lung sounds show the promise of the scheme for the time delay estimation and subsequent interference cancellation.

Chronic low back pain (CLBP) is a significant global concern. Its prevalence continues to rise, and current management strategies demonstrate, at best, moderate effectiveness. The purpose of this study was to explore the concept of uncertainty tolerance and how it affects an individual’s ability to hope, as well as how both of these factors influence emotion regulation. These concepts are highly relevant for both patients and clinicians during CLBP consultations. A social constructivist meta-ethnographic study—a highly interpretative type of qualitative review—was conducted to generate new theory and provide valuable insights into this unique area of pain management. A framework was followed; its iterative analytical process involves multiple search strategies in accordance with PRISMA guidelines. The analysis explored relationships among studies, generated conceptual ideas, and ultimately developed a substantive theory. This review represents the first worked example of a theory generating review process. One model is created to illustrate how individuals with CLBP regulate their emotions; it also considers both the influencing factors and the resulting outcomes of this process. The model identifies pathways leading to either adaptive or maladaptive emotional regulation strategies. Tolerance of uncertainty and ability to hope are key concepts that influence emotion regulation and play a vital role in the physical and psychological well-being of people with CLBP. Further research is required to explore how the model can be operationalised in clinical practice.

This article argues that understanding uncertainty in contemporary societies and its psychosocial consequences is possible through a transdisciplinary perspective. This integrates sociological, psychological, economic and political dimensions. To address this, we offer a critical theoretical reflection that draws on diverse conceptual perspectives within the social sciences. In recent years, in psychological research, uncertainty has been mainly analysed as an intrapsychic phenomenon and as a psychological trait through the concept of (in)tolerance of uncertainty. In contrast, we argue for a psychosocial analysis of uncertainty, considering its socio-economic and political origins, thereby challenging its trait-like analysis. For example, we highlight the inputs of attachment theory for the understanding of uncertainty, connecting it to Marris’s thesis of an unequal distribution of uncertainty and of the power to cope with it (1996). This analysis of uncertainty integrates psychological dimensions with social ones within contemporary western societies, proposing the use of the concept of psychosocial uncertainty. The consequences of uncertainties impact upon employment, relationships and communities, where we can locate the social origins of depression, anxiety, distrust, victim-blaming or lack of cohesion in communities. Besides precarity at work, we now face precarious forms of living, endangering the fundamental processes of psychic and social individuation. Finally, we locate the social origins of uncertainty and its psychological consequences within the responsibilities of social sciences. Drawing on psychology, from social and community psychology to clinical and organizational psychology, we query the relationship between theory and practice. Underpinning this argument is an appreciation of Marris’s contribution to the construction of ‘politics of collaboration/association and reciprocity, as opposed to politics of disempowering uncertainty/dissociation’.

Underwater acoustic signal denoising model based on secondary variational mode decomposition

Although the ocean environment in shallow water is very complex, there still exists stable interference pattern for broadband low frequency sound propagation. The waveguide invariant concept is introduced to describe the broadband interference structure of the acoustic pressure field in a waveguide and now it is widely used in underwater acoustic signal processing. Acoustic vector sensor can measure the particle velocity in the ocean and provides more information for the underwater sound field. In this paper, the interference phenomena of broadband vector acoustic signals in shallow water are investigated by numerical simulation. Energy spatial‐frequency distributions are shown for energy flux density vector obtained by combination of pressure and particle velocity signals and they are analyzed according to normal mode theory. Comparisons of the interference structure between the scale acoustic field and vector acoustic field also have been made. The waveguide invariant concept is extended to describe the interference structure of vector acoustic field in shallow water. A method for extraction of the waveguide invariant from interference patterns in vector acoustic field spectrograms is presented, which can be used in matched‐field processing and geoacoustic inversion. It is shown that this method may have more advantages than the traditional methods which calculate the waveguide invariant using measured sound pressure in the ocean.

Multichannel spatial signal processing of high-speed underwater acoustic communication signals is associated with computationally intensive receiver algorithms. Besides requirements in computational time, large adaptive filters operating under computationally efficient algorithms imply increased sensitivity to numerical errors and large noise enhancement, which limit their performance at high signalling rates. To overcome these difficulties, a receiver is proposed which consists of a multi-input multi-output combiner in which many input channels are coherently combined into a smaller number, suitable for subsequent multichannel decision-feedback equalization. Receiver operations are optimized jointly to ensure minimum mean-squared error detector performance. Experimental results obtained on a long-range shallow water channel with data rates up to 2000 bits per second demonstrate the receiver capability to fully exploit the spatial diversity of underwater multipath while keeping the receiver complexity at a minimum, thus allowing both fast convergence and little noise enhancement. >