Signal-to-reverberation Ratio Research Articles

An Adaptive Tracking Method for Moving Target in Fluctuating Reverberation Environment

In environments with a low signal-to-reverberation ratio (SRR) characterized by fluctuations in clutter number and distribution, particle filter-based tracking methods may experience significant fluctuations in the posterior probability of existence. This can lead to interruptions or even loss of the target trajectory. To address this issue, an adaptive PF-based tracking method (APF) with joint reverberation suppression is proposed. This method establishes the state space model under the Bayesian framework and implements it through particle filtering. To keep the weak target echoes, all the non-zero entries contained in the sparse matrix processed by the low-rank and sparsity decomposition (LRSD) are treated as the measurements. The prominent feature of this approach is introducing an adaptive measurement likelihood ratio (AMLR) into the posterior update step, which solves the problem of unstable tracking due to the strong fluctuation in the number of point measurements per frame. The proposed method is verified by four shallow water experimental datasets obtained by an active sonar with a uniform horizontal linear array. The results demonstrate that the tracking frame success ratio of the proposed method improved by over 14% compared with the conventional PF tracking method.

A construction method of reverberation suppression filter using an end-to-end network.

Reverberation is the primary background interference of active sonar systems in shallow water environments, affecting target position detection accuracy. Reverberation suppression is a signal processing technique used to improve the clarity and accuracy of echo by eliminating the echoes, reverberations, and noise that occur during underwater propagation.This paper proposes an end-to-end network structure called the Reverberation Suppression Network (RS-U-Net) to suppress the reverberation of underwater echo signals. The proposed method effectively improves the signal-to-reverberation ratio (SRR) of the echo signal, outperforming existing methods in the literature. The RS-U-Net architecture uses sonar echo signal data as input, and a one-dimensional convolutional network (1D-CNN) is used in the network to train and extract signal features to learn the main features. The algorithm's effectiveness is verified by the pool experiment echo data, which shows that the filter can improve the detection of echo signals by about 10 dB. The weights of reverberation suppression tasks are initialized with an auto-encoder, which effectively uses the training time and improves performance. By comparing with the experimental pool data, it is found that the proposed method can improve the reverberation suppression by about 2 dB compared with other excellent methods.

Enhanced target detection using a new cognitive sonar waveform design in shallow water

A cognitive waveform design is proposed for use in SONARs (Sound Operated Navigation and Ranging) for detecting targets in undersurface environment. The study adopts a waveform design procedure exploiting prior knowledge gained from environmental reverberations and target signals based on maximizing signal- to- interference-plus- noise ratio (SINR) in the receiver. A genetic algorithm is set forth to work out the optimal specifications in a wideband waveform design. Using initial Linear Frequency Modulated (LFM) waveform as input to the proposed optimization algorithm, an optimal waveform is obtained showing significant improvements in SINR. A number of experiments are conducted to simulate Probability of Detection (POD) versus Signal-to-Reverberation Ratio (SRR) in underwater environments. Analyzing simulation results reveals considerable improvements in target detection task utilizing optimal waveform design compared to initial LFM waveform. Also, in comparison with the initial LFM waveform, it was noticed that there was a substantial reduction in the bandwidth of the optimized design waveform.Our proposed method solves the problem of finding the optimal frequency for designing a cognitive waveform appropriate to the conditions of the environment and the target. We proposed the genetic algorithm method to solve the waveform design problem that maximize the SINR. This paper provides a general methodology for extracting the optimal frequency parameters of the waveform and can be extended to other parameters in cognitive design.

Track-before-Detect Algorithm for Underwater Diver Based on Knowledge-Aided Particle Filter.

This work studies the underwater detection and tracking of diver targets under a low signal-to-reverberation ratio (SRR) in active sonar systems. In particular, a particle filter track-before-detect based on a knowledge-aided (KA-PF-TBD) algorithm is proposed. Specifically, the original echo data is directly used as the input of the algorithm, which avoids the information loss caused by threshold detection. Considering the prior motion knowledge of the underwater diver target, we established a multi-directional motion model as the state transition model. An efficient method for calculating the statistical characteristics of echo data about the extended target is proposed based on the non-parametric kernel density estimation theory. The multi-directional movement model set and the statistical characteristics of the echo data are used as the knowledge-aided information of the particle filter process: this is used to calculate the particle weight with the sub-area instead of the whole area, and then the particles with the highest weight are used to estimate the target state. Finally, the effectiveness of the proposed algorithm is proved by simulation and sea-level experimental data analysis through joint evaluation of detection and tracking performance.

A Reverberation Suppression Method Based on the Joint Design of a PTFM Waveform and Receiver Filter.

Transmitting waveform design and signal processing method optimization are effective ways to improve a sonar system's detection performance. In this study, the spectrum and ambiguity function characteristics of pulse trains of frequency modulation (PTFM) signals were deduced and analyzed to address the problem of serious reverberation interference in the detection of low-speed targets in shallow water environments. The action mechanisms of PTFM signal parameters on the comb spectrum and bed of nails ambiguity function were identified. PTFM signal parameters were designed according to reverberation suppression requirements. The threshold was calculated using the estimate-before-detect method, and the comb spectrum waveform cognitive filtering detection algorithm is proposed. The simulation and lake experimental results show that the PTFM signals' reverberation suppression ability for low-speed targets was better than it was for stationary or high-speed targets. The proposed method has good universality, which can improve the output signal-to-reverberation ratio (SRR) by more than 6 dB.

A Prototype Web Application to Support Human-Centered Audiovisual Content Authentication and Crowdsourcing

Media authentication relies on the detection of inconsistencies that may indicate malicious editing in audio and video files. Traditionally, authentication processes are performed by forensics professionals using dedicated tools. There is rich research on the automation of this procedure, but the results do not yet guarantee the feasibility of providing automated tools. In the current approach, a computer-supported toolbox is presented, providing online functionality for assisting technically inexperienced users (journalists or the public) to investigate visually the consistency of audio streams. Several algorithms based on previous research have been incorporated on the backend of the proposed system, including a novel CNN model that performs a Signal-to-Reverberation-Ratio (SRR) estimation with a mean square error of 2.9%. The user can access the web application online through a web browser. After providing an audio/video file or a YouTube link, the application returns as output a set of interactive visualizations that can allow the user to investigate the authenticity of the file. The visualizations are generated based on the outcomes of Digital Signal Processing and Machine Learning models. The files are stored in a database, along with their analysis results and annotation. Following a crowdsourcing methodology, users are allowed to contribute by annotating files from the dataset concerning their authenticity. The evaluation version of the web application is publicly available online.

Enhanced target detection using a new combined sonar waveform design

In this paper, a method for combining wideband and narrowband waveforms is proposed to improve target detection in shallow water environments. In this regard, a sonar waveform design suitable for target speed has been proposed too. The method uses a wideband frequency-modulated waveform for high range resolution in a reverberation environment and the Doppler-sensitive (DS) waveform to improve the detection of moving targets. The proposed combined waveform is mathematically modeled, and the Calculating of ambiguity function (AF) is performed. The AF and autocorrelation function (ACF) of the designed waveform indicate both DS and fair range resolution features simultaneously exist. So the initial range resolution for target detection is preserved. The Peak to Sidelobe level (PSL) ratio of the proposed waveform is at least 25 dB more than the previous state of the art waveforms. Calculating the Q-function criterion for the designed waveform reveals the superior reverberation suppression and detection performance with respect to the state of the art waveforms. After calculating the reverberation channel model, waveform echo, and detection of the target, the probability of detection (Pd) versus signal-to-reverberation ratio (SRR) was simulated by the Monte Carlo method. It was shown that the proposed waveform improved the probability of target detection by 20 dB, comparing to the base waveforms.

Reverberation reduction based on multi-ping association in a moving target scenario.

Conventional reverberation reduction methods are conducted with single-ping data and may fail in a low signal-to-reverberation ratio (SRR) environment. To improve the performance of reverberation reduction, multi-ping data are fully considered in this paper. The reverberation can be treated as a combination of the steady component of reverberation and reverberation fluctuations, and then an alternating direction multiplier method is proposed to reduce the steady component of the reverberation. By exploiting the evolution of the target location along multiple pings, the reverberation fluctuation is reduced by the probabilistic data association method. The proposed method was verified by the field data, and the results show that compared with the accelerated proximal gradient method, the sparse coefficient is improved by a factor of 1.23, and the signal excess is improved by an average value of 2.0 dB. In addition, the performance of the proposed method is found to be closely related to the signal-to-reverberation-fluctuation ratio rather than only the SRR.

Signal-to-Reverberation Ratio Comparison of Linear Frequency Modulated Continuous Active Sonar and Pulsed Active Sonar

Continuous active sonar (CAS) waveforms provide an advantage over conventional pulsed active sonar (PAS) waveforms, which is, they can be processed to provide a higher target update rate through subpulse processing. Performance in reverberation limited conditions is particularly important in shallow water. This article compares the signal-to-reverberation ratio (SRR), echo level, and reverberation level of simultaneously transmitted linearly frequency modulated (LFM) PAS with an equal bandwidth LFM CAS waveforms processed with different CAS subpulse durations in a littoral environment. Data from an experimental sea trial showed that the LFM PAS waveform outperformed the full-band LFM CAS waveform in terms of SRR by 3.0 ± 2.1 dB. The SRR of the CAS waveform degraded by less than the expected 3 dB per halving of the subpulse bandwidth and duration. Energy spreading loss, which increases with bandwidth, was shown to be the dominant cause of the deviation from expected degradation rate. The detection performance of the full-band LFM CAS waveform was approximately equal to that of the LFM PAS waveform as measured by a receiver operating characteristic analysis.

Underwater target detection based on fourth-order cumulants beamforming

Obtaining the target echo data of high signal to reverberation ratio (SRR) or signal to noise ratio (SNR) in the complex ocean environment is a key problem to improve the detection capability of underwater targets. In this paper, combined with the expansion characteristics of fourth-order cumulants to the array aperture and the structure of the smallest redundant array, a robust and high-resolution fourth-order cumulants beamforming method based on the smallest redundant array is presented. The target direction-of-arrival estimation (DOA) is achieved by forming a narrow space beam, while the reverberation interference is reduced. For the broadband detection system, combined with fractional Fourier transform (FRFT), the fourth-order cumulants beamforming method is extended to the DOA estimation of LFM signal. According to the signal characteristics difference between the target echo and the reverberation, the reverberation is filtered out in the FRFT domain, which achieves the secondary suppression of reverberation interference in the spatial domain and the transform domain, and further improves the SRR of the target echo signal. The validity of the research method is verified by the processing results of the active sonar target detection experiment.

Phase reference for the generalized multichannel Wiener filter

The multichannel Wiener filter (MWF) is a well-established noise reduction technique for speech processing. Most commonly, the speech component in a selected reference microphone is estimated. The choice of this reference microphone influences the broadband output signal-to-noise ratio (SNR) as well as the speech distortion. Recently, a generalized formulation for the MWF (G-MWF) was proposed that uses a weighted sum of the individual transfer functions from the speaker to the microphones to form a better speech reference resulting in an improved broadband output SNR. For the MWF, the influence of the phase reference is often neglected, because it has no impact on the narrow-band output SNR. The G-MWF allows an arbitrary choice of the phase reference especially in the context of spatially distributed microphones. In this work, we demonstrate that the phase reference determines the overall transfer function and hence has an impact on both the speech distortion and the broadband output SNR. We propose two speech references that achieve a better signal-to-reverberation ratio (SRR) and an improvement in the broadband output SNR. Both proposed references are based on the phase of a delay-and-sum beamformer. Hence, the time-difference-of-arrival (TDOA) of the speech source is required to align the signals. The different techniques are compared in terms of SRR and SNR performance.

Ideal binary masking for reducing convolutive noise

It is important to know the degree to which convolutive noise disrupts the perceptual aspects of speech and its intelligibility. This paper presents the ideal binary masking criterion for reducing the convolutive noise (reverberation) and to improve the quality and intelligibility of speech. The noise is suppressed using ideal binary time---frequency masking that is based on signal-to-reverberation ratio (SRR) of individual time---frequency channels. All T---F channels with the SRR greater than pre-selected threshold are retained while others are eliminated. The performance of algorithm is evaluated using IEEE sentences corrupted with different degrees of reverberation times (RT60) ranging from 0.3 to 2.0 s. The results indicate that with the increase of reverberation time, the intelligibility and perceptual aspects of speech decrease. Additional analyses indicated that ideal binary masking reduced the temporary envelope spreading effect introduced by the reverberation. The algorithm is evaluated with perceptual evaluation of speech quality, SNRLOSS, log-likelihood-ratio and frequency weighted segmental signal-to-noise ratio.

Reverberant Speech Enhancement by Temporal and Spectral Processing

This paper presents an approach for the enhancement of reverberant speech by temporal and spectral processing. Temporal processing involves identification and enhancement of high signal-to-reverberation ratio (SRR) regions in the temporal domain. Spectral processing involves removal of late reverberant components in the spectral domain. First, the spectral subtraction-based processing is performed to eliminate the late reverberant components, and then the spectrally processed speech is further subjected to the excitation source information-based temporal processing to enhance the high SRR regions. The objective measures segmental SRR and log spectral distance are computed for different cases, namely, reverberant, spectral processed, temporal processed, and combined temporal and spectral processed speech signals. The quality of the speech signal that is processed by the temporal and spectral processing is significantly enhanced compared to the reverberant speech as well as the signals that are processed by the individual temporal and spectral processing methods.

Reverberation Suppression Using Wideband Doppler-Sensitive Pulses

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The influence of transmitted waveforms on the signal-to-reverberation ratio (SRR) of a low-frequency active sonar is analyzed both theoretically and experimentally. Reverberation experiments have been conducted during a sea trial in a littoral water environment in October 1999. The aim of the trials was to compare the performance of three classes of waveforms: standard hyperbolic frequency-modulated (HFM) waveforms, continuous waveforms (CWs), and innovative pulse trains of linear frequency-modulated (PTFM) waveforms. Transmissions were combined (CW/PTFM train) or intermitted (HFM) to compare the performance of the three classes in (exactly) the same environment. Experimental results in highly reverberant environment illustrated that PTFM pulses allow a reduction in reverberation power greater than 10 dB over the standard detection pulses for slowly moving targets. The results are in agreement with theoretical predictions. </para>

FAST BISTATIC SIGNAL-TO-REVERBERATION-RATIO CALCULATION

Closed-form expressions are presented for signal and reverberation in a wide variety of bistatic scenarios including variable bottom bathymetry. These extend the findings and inferences from already published expressions for monostatic sonar and provide considerable insight into sonar performance. They are also developed into a hybrid numerical solution that can be applied to realistic grided environments (though isovelocity so far). Derivations are based on an eigenray sum with (bistatically varying) Lambert's law scattering, and the result is valid for general smoothly varying bathymetry. Examples of reverberation, target echo, and signal-to-reverberation-ratio (SRR) are given for the case of a uniformly sloping bottom abutting a shelf. The SRR is always high immediately behind the receiver (i.e. in the opposite direction from the bistatic source). Conversely the SRR is very poor between the source and receiver. An example of the hybrid numerical approach with realistic bathymetry from the area in between Sicily and Malta shows that Lambert's law with "mode-stripping" lead to high detection ranges. Noise limiting moderates this and there is then a roughly elliptical annular region with high SRR; inside and outside the annulus performance is poor. Calculating a full set of plots takes only a few seconds on a PC and requires no priming or tabulation. Therefore sonar assessment of complete moving scenarios becomes a practical proposition.

Underwater target classification in changing environments using an adaptive feature mapping

A new adaptive underwater target classification system to cope with environmental changes in acoustic backscattered data from targets and nontargets is introduced. The core of the system is the adaptive feature mapping that minimizes the classification error rate of the classifier. The goal is to map the feature vector in such a way that the mapped version remains invariant to the environmental changes. A K-nearest neighbor (K-NN) system is used as a memory to provide the closest matches of an unknown pattern in the feature space. The classification decision is done by a backpropagation neural network (BPNN). Two different cost functions for adaptation are defined. These two cost functions are then combined together to improve the classification performance. The test results on a 40-kHz linear FM acoustic backscattered data set collected from six different objects are presented. These results demonstrate the effectiveness of the adaptive system versus nonadaptive system when the signal-to-reverberation ratio (SRR) in the environment is varying.

Digital processing of Doppler sonar signals

The signal processing gain by digital beamforming in Doppler sonar was investigated in terms of the enhancement of signal-to-reverberation ratio (SRR) at the postbeamforming Doppler-filter output with an objective to determine the minimum number of bits necessary for the quantization of beamformer channel input signals without appreciable degradation of sonar performance. The formulation of the problem follows closely the author’s earlier work which extends Davenport’s analysis of bandpass limiter to the more general multichannel multibit signal processors. Owing to the Doppler shift of target signal frequency and the relatively narrow bandwidth of Doppler filters, we express the frequency selective effect in the nonlinear interacting power series in terms of a new set of coefficients cmk, which bear crucial significance in sonar performance. Extensive numerical calculations of ’’Doppler processing gain’’ were carried out to demonstrate that four-bit quantization of array transducer signals is theoretically sufficient to yield a performance essentially identical to that of a linear beamformer, but severe loss of gain could result if fewer than four bits are taken at the quantizer output. It is further demonstrated numerically and substantiated analytically that, for small input SRR, the processing gain of a digital beamformer with Doppler filters cannot exceed that of a linear (or optimized four-bit digital) beamformer even it its channel signals are quantized into more than four bits.

Signal-processing gain by digital beamforming in Doppler sonar

The signal-processing gain by digital beamforming in Doppler sonar was investigated in terms of the enhancement of signal-to-reverberation ratio (SRR) at the post-beamforming Doppler filter output with an objective to determine the minimum number of bits necessary for the quantization of beamformer channel input signals without appreciable degradation of sonar performance. It is shown that, in the present case, the simplified method of counting spectral lobes originally due to Davenport [W. B. Davenport Jr., J. Appl. Phys. 24, 720 (1953); for application to multichannel multibit signal processors, see H. S. C. Wang, J. Acoust. Soc. Am. 53, 929 (1973)] can only be applied with certain modifications in the evaluation of various signal and reverberation interacting power terms. Extensive numerical calculations of “Doppler processing gain” were then carried out to demonstrate that four-bit quantization of array transducer signals is theoretically sufficient to yield a performance essentially identical to that of a linear beamformer, but severe loss of gain could result if fewer than four bits are taken at the quantizer output. It is further demonstrated numerically and substantiated analytically that, for small input SRR, the processing gain of a digital beamformer with Doppler filters cannot exceed that of a linear (or optimized four-bit digital) beamformer even if its channel signals are quantized into more than four bits.