Time-varying filter estimation for the deconvolution of environmental reverberation from active sonar returns
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The estimation and removal of the time-varying two-way impulse response to environmental scatterers from broadband reverberation data is considered for increasing the signal-to-noise ratio of sonar returns from targets in the water column. Spectrograms of simulated and real reverberation time series data from active sonars in the mid-frequency range show strong evidence of interference patterns which give clues to the number of important paths to environmental scatterers as well as their depth in the water column. In this talk we consider the estimation of a time dependent de-convolution filter for the removal of these environmental reverberation returns from active sonar data. Issues regarding the degrees of freedom required for the efficient implementation of this filter and the stability of these estimates are considered. Simulation results are shown which demonstrate the potential gain of using this approach to partially null the impact of environmental scatterers in active sonar data.Keywords:
Impulse response
Spectrogram
Finite impulse response
Active sonar performance is determined by the characteristics of the target, the sonar system and the effect of the environment on the received waveform. The two main influences of the environment are propagation effects and the contamination of the target echo with a background. The ambient noise and reverberation are mitigated by means of signal processing, mostly through beamforming and matched-filtering. The improvement can be quantified by the signal to noise ratios before and after processing. Propagation effects can have a large influence on the gains obtained by the processing. To study the effect of the channel on the matched filter performance, broadband channel impulse responses were modeled and compared to measurements acquired during the Office of Naval Research-funded 2013 Target and Reverberation Experiment (TREX). In shallow water, a large time spread is often observed, reducing the effectiveness of the matched filter. TREX data show, however, a limited time spread. Model predictions indicate that this could be caused by a rough sea-surface, which while increasing propagation loss, at the same time increases matched filter gain.
Impulse response
Matched filter
Sonar signal processing
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This study concerns the mathematical modelling of speech related acoustical hearing discomforts in medium to large environments (e.g. auditoriums and concert halls). Discomforts arise from both phase distortion (echo) and perceived frequency transformations (Comb filters) Bonwick[1], Ando[3]. These distortions are caused by the physical constraints imposed on sound transmission within large environments. Deconvolution was applied to the measured signals to recover the original sound from the environmentally distorted sound, thus separating it from the transformation system function (Room impulse response). Several samples were used for different positions within the hall. The different methods investigated for the deconvolution process were cross-correlation, cepstrum and adaptive filter techniques, Oppenheim[2]. Upon separation the inverse of the system transfer function was determined and used in the latter part of the study to pre-deform the original sound. Only a part of the system response was used. The first 20 - 30 ms constructively contribute to the intelligibility of speech and masked towards the end of the impulse response by the background noise at 40 dBA, Borwick[1]. The critical part between 0.020 and 2 sec was then used as the basis of the filter algorithm design. Because of the length of this part of thc impulse response as well as the real time processing constraints a FIR filter could not be implemented, Ando[3], Tohyama[4]. Instead the filter was designed in the frequency domain. During transmission the environment now acting on the pre-deformed (filtered) sound renders better quality speech that is easier to understand, effectively removing part of the deformation. Finally the psychoacoustics of the total system were evaluated by a panel of listeners in the auditorium (concert hall) and the system was found to be effective for some targeted arcas within the particular hall. The impact of these results for addressing acoustical problems will be discussed.
Impulse response
Inverse filter
Room acoustics
Finite impulse response
Architectural acoustics
Cepstrum
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Long detection ranges require low frequencies because of the attenuation of sound by seawater. Unfortunately, in order to get directionality at low frequencies, large arrays are required. To achieve higher directivity, the product of the size and the frequency must increase. In addition to the choice of frequency and size, the computational requirements of a sonar system need to be considered. The choice of type and duration of active sonar pulses is a classic example of tradeoffs. There are four basic types of pulses: continuous wave (CW), coded pulses (CP), pseudo random pulses (PRN), and explosive or impulsive pulses. Each type has inherent advantages and disadvantages in both detection and localization. Most modern, monostatic active sonars in search mode use omni, or wide-sector transmissions, with a highly directional receiver. These receivers have reduced ambient noise, reduced reverberation, and have the ability to provide accurate bearings for tracking. Controlled Vocabulary Terms impulse noise; noise; pseudonoise codes; sonar
Directivity
Impulse response
Ambient noise level
Sonar signal processing
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A new tool for estimation of both the central arterial pressure and the unknown channel dynamics has been developed. Given two peripheral waveform measurements, this new signal processing algorithm generates two models that represent the distinct branch dynamic behavior associated with the measured signals. The framework for this methodology is based on a Multichannel Blind Deconvolution (MBD) technique that has been reformulated to use Stochastic Calculus (SC). The technique is based on MBD of dynamic system are mathematically analyzed, in order to reconstruct the common unobserved input within an arbitrary scale factor. The convolution process is modeled as a Finite Impulse Response (FIR) filter with unknown coefficients. The source signal is also unknown. Assuming that one of the FIR filter coefficients are time varying, we have been able to get accurate estimation results for the source signal, even though the filter order is unknown. The time varying filter coefficients have been estimated through the SC algorithm, and we have been able to deconvolve the measurements and obtain both the source signal and the convolution path. The positive results demonstrate that the SC approach is superior to conventional methods.
Finite impulse response
Convolution (computer science)
Impulse response
SIGNAL (programming language)
Wiener deconvolution
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Impulse response
Wideband
Finite impulse response
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The estimation and removal of the time-varying two-way impulse response to environmental scatterers from broadband reverberation data is considered for increasing the signal-to-noise ratio of sonar returns from targets in the water column. Spectrograms of simulated and real reverberation time series data from active sonars in the mid-frequency range show strong evidence of interference patterns which give clues to the number of important paths to environmental scatterers as well as their depth in the water column. In this talk we consider the estimation of a time dependent de-convolution filter for the removal of these environmental reverberation returns from active sonar data. Issues regarding the degrees of freedom required for the efficient implementation of this filter and the stability of these estimates are considered. Simulation results are shown which demonstrate the potential gain of using this approach to partially null the impact of environmental scatterers in active sonar data.
Impulse response
Spectrogram
Finite impulse response
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In this paper multi-microphone dereverberation is considered under the constraint that no or little additional delay should be introduced by the FIR deconvolution lters. This is crucial for a number of applications such as hearing aids etc. Assuming that the acoustic impulse responses (AIRs) are known n e.g. by estimation, we determine the maximum degree of attainable dereverberation. Even though the AIRs are in general non-minimum phase, complete dereverberation can be accomplished in principle, using causal FIR lters of the same order as the AIRs, yielding no or only a little additional delay. We show that complete dereverberation with no or little delay will, however, reduce the SNR. For a given SNR gain and low delay, therefore, the achievable dereverberation is limited. We employ a time domain FIR multichannel Wiener lter with a delay constraint to nd the MSE-sense optimal deconvolution lters. Dereverberation performance and SNR gain are demonstrated for typical AIRs with reverberation times of T60 500ms and N = 4000 taps which have been measured in a conference room. Furthermore, we propose a new method utilizing a shaped desired total response, which is capable of selectively eliminating late reverberation while maintaining the SNR.
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Impulse response
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Abstract : This study is concerned with deconvolution methods applied to underwater propagation in shallow water, whereby the received signal is modelled as the convolution between the transmitted pulse and the medium impulse response. The aim of the method is to extract information on backscattering, travel time delays, boundary reflection and refraction from the received signal on a point receiver or an array for both seismic and active sonar data. Since experimental data are generally mixed phase, due in part to the multiple reflections (bottom and surface), the conventional linear filtering which assumes the minimum phase property, loses in efficacy. In order to handle this mixed phase characteristic of the data, we proceed in two steps. We first apply a homomorphic filter (complex cepstrum) to deconvolve the wavelet. Then we deconvolve the medium impulse response by means of Wiener filter. The efficacy of the method is shown on both simulated and real data for explosive and active sonar data. Keywords: Acoustic sonar signals; Scattering; Seismic waves; Cepstrum technique; Bottom reflection; Low frequency; Wave propagation; Seismic data; Towed array.
Impulse response
Wiener deconvolution
Cepstrum
Wiener filter
Finite impulse response
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The range-averaged intensity model (RAIM) long known as a powerful method for transmission loss estimation in waveguides, is extended to other aspects of the acoustic field: impulse response and angular pattern estimations at a receiver, general time spreading in a waveguide, signal fluctuations, reverberation levels, and ambient noise structure. An example of its application to a SOFAR propagation and detection case is presented. This method appears to be a very efficient and reliable analysis tool for many underwater acoustics configurations: particularly long-range horizontal telemetry and shallow-water sonar.< >
Underwater Acoustics
Impulse response
Underwater acoustic communication
Transmission loss
Ambient noise level
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Speech in rooms is subject to degradation caused by acoustic reverberation. Signal processing techniques to remove reverberation have required multiple microphones or knowledge of the room impulse response. In this paper, complex cepstral deconvolution is applied to acoustic dereverberation. A new ap proach to the segmentation and windowing procedure for speech improves the complex cepstral identification of the reverberant impulse response, and least squares inverse filters are used to remove the estimated impulse response from the reverberant speech. Although complete removal of the impulse response is not possible, reduction of reverberation with this technique is demonstrated.
Cepstrum
Impulse response
Finite impulse response
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