Underwater target detection based on fourth-order cumulant beamforming

Li, Xiukun; Jia, Hongjian; Yang, Mei

doi:10.1121/2.0000663

Cited by 3 publications

(5 citation statements)

References 3 publications

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“…Bayesian methods (BMs) are also applied to the estimation of the DoA of wideband linear frequency modulation (LFM) signals using a uniform linear array [130]. The authors resort to the fractional Fourier transform to extract the wanted signal from a reverberating background and improve the operating signal-to-noise ratio.…”

Section: Related Work 79mentioning

confidence: 99%

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

Dubrovinskaya

Casari

2019

OCEANS 2019 - Marseille

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Casari knows no boundaries. He believed in me to allow me to work independently while providing all the possible support and was by my side when needed. His high standards both in research and communication have become my constant beacon in my personal and professional growth. His assistance in every aspect of research work was absolutely invaluable.Another thank you should definitely go to my tutor Prof. Albert Banchs Roca for all his help with the paperwork from the very first days of my Ph.D. I would also like to say thanks to Dr. Ivor Nissen for his introduction to the world of underwater acoustic localization research, and for always keeping an eye on my progress. I am grateful to Dr. Diamant for welcoming and hosting me at Haifa University and enduring me during numerous sea trials. All the field experience I got during my trips to Israel is still one of the most unforgettable go through during my Ph.D.Furthermore, I would like to say many thanks to Dr. Konstantin Kebkal and Evologics GmbH colleagues for hosting me at their premises in Berlin and for all the invaluable help in organizing lab and field experiments. Special thanks to Veronika Kebkal who pushed everyone to make it possible (and fun!) Also, I would like to thank Dr. Fraser Dalgleish who hosted me at Florida Atlantic University and for sharing experimental data even after I left.A huge bunch of thanks goes to all my colleagues at IMDEA Networks for all the coffee break talks, dinner drinks, board games battles, and barbeque parties. Special thanks go to the "ground-floor" team for all the evening gossip times and fun we had.Last but not least thank you goes to my wonderful family. Thanks to my parents for teaching me to value knowledge and for giving me everything I need. And the most important thanks -to my husband Sergey Samodov, who was solving all my life problems, listened to my nagging during the hardest days saying, "this too shall pass", waiting for me to come back. I couldn't have done this journey without you.

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Section: Related Work 79mentioning

confidence: 99%

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

Dubrovinskaya

Casari

2019

OCEANS 2019 - Marseille

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“…) According to the expansion characteristics of the fourthorder cumulants, a fourth-order cumulant matrix [67]- [72] can be constructed ** [( 1) ,…”

Section: Third-order Cumulant and Bispectrummentioning

confidence: 99%

“…Fourth-order cumulant Suppress Gaussian noise while preserving that symmetrical portion of the signal [51]- [63] Normalized fourth-order cumulant Reduce the probability of blind communication classification errors [62], [63] Simplified calculation of fourth-order cumulants Reduce that computational complexity [66] Fourth-order cumulative matrix Enlarge the aperture of the beamforming array [67]- [72] Trispectrum and diagonal slices of trispectrum Trispectrum Preserve the advantages of the fourth-order cumulants [73]- [78] The estimate of diagonal slices for fourth-order cumulants Reduce the amount of calculation [79][17] [80] The slice spectrum of fourth-order cumulants The harmonic components of that signal are extracted for phase couple detection [81] Weighted fourth-order cumulant slice Adaptive linear enhancement [82] Off-diagonal slices of fourth-order cumulants Enhance the dynamic line spectrum feature of the signal [83] Windowed fourth-order mixed cumulant slice Avoid spectrum leakage [84] order mixed cumulant is used to calculate the polarization filter coefficient in feature extraction, and the noise spectrum can be filtered to extract the line spectrum. Technical development of the fourth-order domain feature extraction methods in the field of ocean acoustic observation is shown in Table 2.…”

Section: Fourth-order Cumulantmentioning

confidence: 99%

“…In the aspect of single vector hydrophone, based on characteristics of aperture expansion of higher-order cumulant array, [19] used third-order cumulants to estimate the two-dimensional direction of arrival of multiple non-Gaussian sources, and [55], [69] used fourth-order cumulants to provide efficient and accurate beamforming and DOA estimation methods for vector hydrophones processing non-Gaussian sources in the presence of generalized Gaussian noise or interference sources. [67] extended the fourth-order cumulant beam formation method combined with fractionalorder Fourier transform (FRFT) to extend the algorithm to DOA estimation of broadband LFM signals and apply the algorithm to active sonar target detection. [68] obtained multiple invariance matrices by defining a series of fourthorder cumulant matrices, and then extracted the localization information of the near-field source from these invariance matrices.…”

Section: Doa Estimation Of Vector Hydrophonementioning

confidence: 99%

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High-Order Domain Feature Extraction Technology for Ocean Acoustic Observation Signals: A Review

et al. 2023

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For the acquisition of ocean observation information, the underwater acoustic signal is the only known medium that can propagate over long distances in water. However, the underwater acoustic field environment is highly time-varying and spatially variable, and ocean acoustic observation signals are mixed Gaussian, non-cooperative, and nonlinear. Therefore, feature extraction of underwater target signals has been a challenging research direction. The high-order domain feature extraction method of ocean acoustic observation signal is widely used because of its advantages of anti-Gaussian background noise and preservation of signal phase information. Firstly, this paper analyzes three aspects, including the characteristics of ocean acoustic observation signals, the limitations of second-order domain processing methods, and advantages of high-order domain processing methods. Then, this paper focuses on theoretical advantages and application areas of signal high-order domain feature extraction technology. The technical development and application performance of common feature extraction technology in the field of ocean acoustic observation signal processing by higher-order domain methods in recent years are analyzed in the paper, and the challenges and future trends of higher-order domain feature extraction technology in marine acoustic observation signal processing are discussed in the context of recent studies.

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“…A similar approach [35] employs mono-pulse processing to cancel incoherent multipath components that would interfere with the receiver in a reverberating shallow water acoustic communications scenario. Bayesian methods (BMs) are also applied to the estimation of the DoA of wideband linear frequency modulated (LFM) signals using a uniform linear array [36]. The authors resort to the fractional Fourier transform to extract the wanted signal from a reverberating background and improve the operating signal-to-noise ratio.…”

Section: Related Workmentioning

confidence: 99%

Underwater Localization via Wideband Direction-of-Arrival Estimation Using Acoustic Arrays of Arbitrary Shape

Dubrovinskaya

Kebkal²,

Kebkal³

et al. 2020

Sensors

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Underwater sensing and remote telemetry tasks necessitate the accurate geo-location of sensor data series, which often requires underwater acoustic arrays. These are ensembles of hydrophones that can be jointly operated in order to, e.g., direct acoustic energy towards a given direction, or to estimate the direction of arrival of a desired signal. When the available equipment does not provide the required level of accuracy, it may be convenient to merge multiple transceivers into a larger acoustic array, in order to achieve better processing performance. In this paper, we name such a structure an “array of opportunity” to signify the often inevitable sub-optimality of the resulting array design, e.g., a distance between nearest array elements larger than half the shortest acoustic wavelength that the array would receive. The most immediate consequence is that arrays of opportunity may be affected by spatial ambiguity, and may require additional processing to avoid large errors in wideband direction of arrival (DoA) estimation, especially as opposed to narrowband processing. We consider the design of practical algorithms to achieve accurate detections, DoA estimates, and position estimates using wideband arrays of opportunity. For this purpose, we rely jointly on DoA and rough multilateration estimates to eliminate spatial ambiguities arising from the array layout. By means of emulations that realistically reproduce underwater noise and acoustic clutter, we show that our algorithm yields accurate DoA and location estimates, and in some cases it allows arrays of opportunity to outperform properly designed arrays. For example, at a signal-to-noise ratio of –20 dB, a 15-element array of opportunity achieves lower average and median localization error (27 m and 12 m, respectively) than a 30-element array with proper λ / 2 element spacing (33 m and 15 m, respectively). We confirm the good accuracy of our approach via emulation results, and through a proof-of-concept lake experiment, where our algorithm applied to a 10-element array of opportunity achieves a 90th-percentile DoA estimation error of 4 ∘ and a 90th-percentile total location error of 5 m when applied to a real 10-element array of opportunity.

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Underwater target detection based on fourth-order cumulant beamforming

Cited by 3 publications

References 3 publications

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

High-Order Domain Feature Extraction Technology for Ocean Acoustic Observation Signals: A Review

Underwater Localization via Wideband Direction-of-Arrival Estimation Using Acoustic Arrays of Arbitrary Shape

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