Spatial rotation technique with application to unmanned underwater vehicle (UUV) sonar arrays

Liang, Guolong; Yu, Haohui; Fan, Zhan

doi:10.1049/el.2017.3502

Cited by 8 publications

(3 citation statements)

References 5 publications

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“…Finally, all spurious peaks in the spatial spectrum can be identified, and the ambiguity will be eliminated. Following the steps in the processing flow, the true directions of targets are more deterministic, which is beneficial to interesting fields such as UUV sonar arrays [31]. This paper focuses on the ambiguity elimination problem rather than an underwater detection problem, so it is assumed that the SNR is enough to execute the processing flow.…”

Section: Processing Flowmentioning

confidence: 99%

Underwater Ambiguity Elimination Method Based on Co-Prime Sensor Array

Lan

Wang

Qiu

2020

Sensors

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Recently, the direction of arrival estimation with co-prime arrays has gradually been applied in underwater scenarios because of its significant advantages over traditional uniform linear arrays. Despite the advantages of co-prime arrays, the spatial spectra obtained directly from conventional beamforming can be degraded by grating lobes due to the sparse spatial sampling in passive sensing applications, which will seriously deteriorate the estimation performance. In this paper, capon beamforming is applied to a co-prime sensor array as a pretreatment before high-resolution direction of arrival (DOA) estimation methods. The amplitudes extracted from the beam-domain outputs of two subarrays and the phases extracted from the cross-spectrum of the spatial spectrum are exploited to suppress the spurious peaks in beam patterns and eliminate ambiguities. Consequently, interference can be further mitigated, and the performance of high-resolution DOA methods will be guaranteed. Simulations show that the method proposed can improve the reliability and accuracy of DOA estimation with great value in practice.

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Section: Processing Flowmentioning

confidence: 99%

Underwater Ambiguity Elimination Method Based on Co-Prime Sensor Array

Lan

Wang

Qiu

2020

Sensors

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“…In general, spatial processing gain and time processing gain are the two SNR gains sought by passive sonars. Spatial gain is generally obtained by array signal reception using a beamforming method [6]. However, due to the size of the underwater unmanned platform, the number and spacing of the array elements are limited, which makes it difficult to obtain the expected effect.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Line Enhancer Based on Maximum Correntropy Criterion and Frequency Domain Sparsity for Passive Sonars

Zhang,

An,

et al. 2023

Electronics

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The low-frequency narrowband components (known as lines) in the radiated noise of underwater acoustic targets are an important feature of passive sonar detection. Conventional adaptive line enhancer (ALE) based on the least mean square algorithm has limited performance under colored background noise and low signal-to-noise ratio (SNR). In this paper, by combining the frequency domain sparse model of lines and maximum correntropy criterion (MCC), a β-adaptive l0-MCC-ALE is proposed to solve the above-mentioned problem. The proposed ALE uses a sparse-driven MCC algorithm to update the weight vector in the frequency domain to further suppress the colored background noise. For the problem that the value of parameter β is sensitive to the performance, β is updated adaptively according to the frequency response of ALE in each iteration. Simulation and real data processing results show that the proposed ALE is insensitive to the given parameter β and has excellent performance for line enhancement. Compared with conventional ALE, the SNR of lines can be improved by 7~8 dB.

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“…Detection and direction-of-arrival (DOA) estimation using an array of sensors are important topics in signal processing and have many applications, such as in radar, sonar, communications and acoustics [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. Considering moving sources in a noisy environment [ 1 , 2 ], it is desirable to use both the spatial and temporal information for better performance, since the DOAs between consecutive time steps are highly correlated. In [ 7 , 8 , 9 , 10 ], recursive Bayesian approaches are proposed for tracking the DOA of moving sources.…”

Section: Introductionmentioning

confidence: 99%

Joint Detection and DOA Tracking with a Bernoulli Filter Based on Information Theoretic Criteria

Zhang

Zheng

Sun

et al. 2018

Sensors

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In this paper, we study the problem of the joint detection and direction-of-arrival (DOA) tracking of a single moving source which can randomly appear or disappear from the surveillance volume. Firstly, the Bernoulli random finite set (RFS) is employed to characterize the randomness of the state process, i.e., the dynamics of the source motion and the source appearance. To increase the performance of the detection and DOA tracking in low signal-to-noise ratio (SNR) scenarios, the measurements are obtained directly from an array of sensors and allow multiple snapshots. A track-before-detect (TBD) Bernoulli filter is proposed for tracking a randomly on/off switching single dynamic system. Secondly, since the variances of the stochastic signal and measurement noise are unknown in practical applications, these nuisance parameters are marginalized by defining an uninformative prior, and the likelihood function is compensated by using the information theoretic criteria. The simulation results demonstrate the performance of the filter.

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Spatial rotation technique with application to unmanned underwater vehicle (UUV) sonar arrays

Cited by 8 publications

References 5 publications

Underwater Ambiguity Elimination Method Based on Co-Prime Sensor Array

Underwater Ambiguity Elimination Method Based on Co-Prime Sensor Array

Adaptive Line Enhancer Based on Maximum Correntropy Criterion and Frequency Domain Sparsity for Passive Sonars

Joint Detection and DOA Tracking with a Bernoulli Filter Based on Information Theoretic Criteria

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