Non-parametric detection in underwater environments

Nielsen, P.A.; Thomas, John B.

doi:10.1109/icassp.1989.267032

Cited by 2 publications

(2 citation statements)

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“…Letting be the signal, the signal strength and the noise, the observed data can be written as (3) Given the noise pdf of , a likelihood ratio function can be written as a function of the estimated signal strength (4) Maximizing the likelihood ratio , or equivalently, minimizing the negative log-likelihood ratio then gives us the best estimate of signal strength (5) The estimated signal strength is expected to be close to zero when no signal is present.…”

Section: A Maximum-likelihood Detectormentioning

confidence: 99%

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Optimal and Near-Optimal Signal Detection in Snapping Shrimp Dominated Ambient Noise

Chitre

Potter

Ong

2006

IEEE J. Oceanic Eng.

183

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Abstract-The optimal detection of signals requires detailed knowledge of the noise statistics. In many applications, the assumption of Gaussian noise allows the use of the linear correlator (LC), which is known to be optimal in these circumstances. However, the performance of the LC is poor in warm shallow waters where snapping shrimp noise dominates in the range 2-300 kHz. Since snapping shrimp noise consists of a large number of individual transients, its statistics are highly non-Gaussian. We show that the noise statistics can be described accurately by the symmetric -stable family of probability distributions. Maximum-likelihood (ML) and locally optimal detectors based on the detailed knowledge of the noise probability distribution are shown to demonstrate enhanced performance. We also establish that the sign correlator, which is a nonparametric detector, performs better than the LC in snapping shrimp noise. Although the performance of the sign correlator is slightly inferior to that of the ML detector, it is very simple to implement and does not require detailed knowledge of the noise statistics. This makes it an attractive compromise between the simple LC and the complex ML detector.

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Section: A Maximum-likelihood Detectormentioning

confidence: 99%

“…Nielsen and Thomas explored the use of nonparametric detectors in snapping shrimp noise [4], however, they concluded that the LC performed better than nonparametric techniques. This conclusion is not in agreement with the results obtained in this paper.…”

mentioning

confidence: 99%

Optimal and Near-Optimal Signal Detection in Snapping Shrimp Dominated Ambient Noise

Chitre

Potter

Ong

2006

IEEE J. Oceanic Eng.

183

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Hybrid Detector for Ship Radiated Signal in Statistically Varying Underwater Noise

Singh

Kumar

Agrawal

et al. 2006

OCEANS 2006 - Asia Pacific

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The problem of passive detection of ship radiated [4]. The ship radiated signal has also been appropriately signals has been investigated for many years. A primary lacuna in modeled and simulated. It contains both, the broadbandmost detectors is that they are optimal for a specific signal and cavitation noise and sinusoidal-tonal components. noise environment, which deviates significantly from the practical A single detector is not sufficient in detecting the ship signal and noise encountered in the ocean medium. Furthermore, radiated signal reliably over a large range of noise statistics.underwater signal and noise statistics varies significantly over time and space, thereby deteriorating the performance of the Wetaporoach the problem by combining several individual detectors that are tuned to be optimal for a particular signal and detectors into a hybrid detector. For this reason three detectors noise assumption. Therefore, a single detector does not seem are considered, each performing optimally in a certain signal sufficient in detecting the signal in this statistically varying and noise environment. The three detectors are namely, the environment. Here, we consider several detectors that are energy detector (ED), the locally optimum detector (LOD) andindividually optimal in a given scenario, and then combine these the locally optimum spectrum detector (LOSD). The energy individual optimal detectors to formulate a hybrid detector that detector is a special case of the LOD for Gaussian signal and performs reasonably well for a large range of noise statistics. Gaussian noise.Simulation results show that the hybrid detector performs better The fusion can be done with the output of each detector than its constituent detectors.

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Non-parametric detection in underwater environments

Cited by 2 publications

References 8 publications

Optimal and Near-Optimal Signal Detection in Snapping Shrimp Dominated Ambient Noise

Optimal and Near-Optimal Signal Detection in Snapping Shrimp Dominated Ambient Noise

Hybrid Detector for Ship Radiated Signal in Statistically Varying Underwater Noise

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