An improvement to the pulse compression scheme

Courmontagne, Philippe; Julien, Gregory; Bouhier, Marie Edith

doi:10.1109/oceanssyd.2010.5603643

Cited by 6 publications

(7 citation statements)

References 2 publications

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“…The SMF has been used for detection in the time domain in diverse fields such as modulated wideband signal detection in active sonar 31,32 or audio pattern detection in automatic speech recognition. 33 Another formulation of the SMF as a time-varying linear filter provides faster online data processing and significant representations of the method's filters.…”

Section: Detection Strategymentioning

confidence: 99%

“…33 Another formulation of the SMF as a time-varying linear filter provides faster online data processing and significant representations of the method's filters. 32 Recently, the SMF has been used for sperm whale click and echo detection 28 that even outperforms the Teager-Kaiser-Mallat filter method. 16 To continue investing the potential of the SMF as a passive acoustic monitoring tool, it is explored for ABW call detection.…”

Section: Detection Strategymentioning

confidence: 99%

“…S 0 and N 0 are both assumed centered, second-order stationary and mutually independent. 32 The SMF theory 29 shows that it is possible to expand Z into a sum of known vectors W i weighted by uncorrelated random variables z i such as Z ¼ P I i¼1 z i W i and where fW i g i¼1;2;…;I is a I-dimensional deterministic basis. Therefore, depending on the choice of basis vectors, some random variables are carrying more signal than noise.…”

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confidence: 99%

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Passive stochastic matched filter for Antarctic blue whale call detection

Bouffaut

Dreo

Labat

et al. 2018

The Journal of the Acoustical Society of America

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As a first step to Antarctic blue whale (ABW) monitoring using passive acoustics, a method based on the stochastic matched filter (SMF) is proposed. Derived from the matched filter (MF), this filter-based denoising method enhances stochastic signals embedded in an additive colored noise by maximizing its output signal to noise ratio (SNR). These assumptions are well adapted to the passive detection of ABW calls where emitted signals are modified by the unknown impulse response of the propagation channel. A filter bank is computed and stored based on knowledge of the signal second order statistics and simulated colored sea-noise. Then, the detection relies on background noise and SNR estimation, realized using time-frequency analysis. The SMF output is cross-correlated with the signal's reference (SMF + MF). Its performances are assessed on an ccean bottom seismometer-recorded ground truth dataset of 845 ABW calls, where the location of the whale is known. This dataset provides great SNR variations in diverse soundscapes. The SMF + MF performances are compared to the commonly used MF and to the Z-detector (a sub-space detector for ABW calls). Mostly, the benefits of the use of the SMF + MF are revealed on low signal to noise observations: in comparison to the MF with identical detection threshold, the false alarm rate drastically decreases while the detection rate stays high. Compared to the Z-detector, it allows the extension of the detection range of 30 km in presence of ship noise with equivalent false discovery rate.

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Section: Detection Strategymentioning

confidence: 99%

Section: Detection Strategymentioning

confidence: 99%

mentioning

confidence: 99%

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Passive stochastic matched filter for Antarctic blue whale call detection

Bouffaut

Dreo

Labat

et al. 2018

The Journal of the Acoustical Society of America

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“…SMF PRINCIPLE The SMF, introduced by Cavassillas [11], is an extension of the MF for random signal in colored noise. Different improvements have been reported in [12], where it is presented as a time-varying linear filter. In addition of being used as an active sonar signal processing method, recent work [13], [14] dealt with impulsive noise detection e.g.…”

Section: Introductionmentioning

confidence: 99%

“…the method requires both signal and noise references for the preprocessing stage such as S0S0 and N0N0 , respectively the signal's and noise's covariance matrices. These inputs are used in the following Generalized Eigenvalue Problem (GEP) [12]:…”

Section: Introductionmentioning

confidence: 99%

Antarctic Blue Whale calls detection based on an improved version of the stochastic matched filter

Bouffaut

Dreo

Labat

et al. 2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-As a first step to Antarctic Blue Whale monitoring, a new method based on a passive application of the Stochastic Matched Filter (SMF) is developed. To perform Z-call detection in noisy environment, improvements on the classical SMF requirements are proposed. The signal's reference is adjusted, the background noise estimation is reevaluated to avoid operator's selection, and the time-dependent Signal to Noise Ratio (SNR) estimation is revised by time-frequency analysis. To highlight the SMF's robustness against noise, it is applied on a Ocean Bottom Seismometers hydrophone-recorded data and compared to the classical Matched Filter: the output's SNR is maximized and the false alarm drastically decreased.

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A comparison between the classical pulse compression and the improved WV-SMF-PC on ifremer sea trials signals

Julien

Courmontagne

Bouhier

2011

OCEANS 2011 IEEE - Spain

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In several domains of engineering technologies, such as telecommunications, sonar imaging, positioning systems, radar, medical imaging, the main problem is to identify a transmitted useful pulse in a noise-corrupted received signal. A solution to this problem consists in using a modulated pulse for emission and a matched filter for reception. Such a concept is known as pulse compression. Taking into account the main assumptions of the matched filter theory, it has been proposed a new algorithm, the Wigner Ville -Stochastic Matched Filter -Pulse Compression (WV-SMF-PC). This one considers the random nature of the signal and the coloration of the noise, and is based on the jointly used of Time Frequency techniques and a stochastic extension of the Matched Filter notion: the Stochastic Matched Filter. However, some new sea trials have pointed out two main problems linked, on the one hand, to the noise power estimation and, on the other hand, to the real time compatibility. In this article, we propose and discuss a solution to these two problems exploiting informations given by the time frequency domain and we propose a complementary technique to reach the real time. Finally, some results obtained on real data are given.

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An improvement to the pulse compression scheme

Cited by 6 publications

References 2 publications

Passive stochastic matched filter for Antarctic blue whale call detection

Passive stochastic matched filter for Antarctic blue whale call detection

Antarctic Blue Whale calls detection based on an improved version of the stochastic matched filter

A comparison between the classical pulse compression and the improved WV-SMF-PC on ifremer sea trials signals

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