Active Sonar Detection Research Articles

Shallow sea reverberation suppression based on a range azimuth patch matrix model.

Reverberation is the main background interference for active sonar detection in shallow sea. Reverberation suppression is crucial for enhancing the performance of active sonar. In this paper, a reverberation suppression method based on low-rank sparse decomposition is proposed. First, both the sparseness property of the targets and the non-local self-correlation property of the reverberation are used to construct a range azimuth patch matrix model. The reverberation suppression problem is then transformed into an optimization problem for the recovery of a low-rank sparse matrix. The validity of the proposed method is verified by using the measured data. Results show that, compared with the reverberation pre-whitening and sparse fractional Fourier transform methods, the proposed method significantly improves the reverberation suppression performance and achieves a better detection result when the signal-to-interference ratio is below -2 dB.

Analysis of Bottom Reverberation Intensity Under Beam-Controlled Emission Conditions in Deep Water

A comprehensive understanding of the characteristics and the formation mechanism of reverberation is the key to improving the performance of the active target detection. In response to the challenge of analyzing the intensity of bottom reverberation in typical deep-sea environments, this study proposes a prediction method for the bottom reverberation intensity under beam-controlled emission conditions. It explains the variation law of bottom reverberation intensity under beam-controlled emission conditions in typical deep-sea environments of the South China Sea through theoretical and simulation analyses. Reverberation intensity of the deep-sea bottom under beam-controlled emission conditions exhibits significant fluctuations during the duration of reverberations in the direct sound zone of the seabed. This phenomenon is closely related to the directionality of the source emission, leading to intermittent reverberation masking and detectable areas in the active sonar detection. In addition, the duration of the high-reverberation zone near the cutoff distance of the direct sound from the seabed is longer under the beam-controlled emission conditions of the emission array located within the surface waveguide layer of the deep sea during winter.

Enhancing ship noise reduction: a deep-learning based noise extraction model

In active sonar detection systems, the self-radiated noise from the platform itself is a primary factor that interferes with system performance. The platform self-noise exhibits non-Gaussian characteristics, comprising line spectrum and continuous spectrum, where line spectrum exhibits higher intensity and greater frequency stability. To reduce the ship noise, this study introduces a deep-learning based time-domain model with an encoder-separator-decoder architecture. In detail, the encoder and decoder modules utilize learnable convolutional layers to generate distinguishable features with a symmetrical structure. For separator module, we observe that noise components prominently predominate within the noisy signal in low signal-to-noise ratio (SNR) scenarios. The extraction of noise components is typically more tractable than of signal components. Therefore, in contrast to conventional frameworks that focus on extracting the signal subspace, this module is dedicated to extracting the noise subspace. Besides, the modified scale invariant SNR (SI-SNR) is proposed as the loss function for model optimization, which yields better performance than non-noise extraction structure. The robustness of the model is validated on the DeepShip dataset with four ship categories, demonstrating that the model consistently outperforms baselines, including matched filter, in all ship categories.

Deep learning based effective feature extraction for active sonar target detection

We propose a deep learning (DL) model suitable for classifying target and non-target using a small amount of active sonar data. The proposed model uses two hand-crafted features (STFT and CQT) extracted from the same raw active sonar data, to complement each other and enhance the generalization of DL under insufficient data. The attention-based complementary learning module in proposed model reinforces one feature by referring to the other feature. The comprehensive feature from the complementary learning module pass through a shallow layer CNN and classify targets and non-targets. To verify the performance of the proposed model, we compared it with prevalent deep learning models including ResNet and ViT in terms of generalization performance and learning stability using two real-ocean datasets. The generalization performance of the proposed model having much smaller number of parameters was similar to or superior to the existing deep learning models depending on the training dataset, while the proposed model had the best learning stability for the two datasets.

Effect of Emergence Angle on Acoustic Transmission in a Shallow Sea

In this study, the effect of the emergence angle of a source array on acoustic transmission in a typical shallow sea is simulated and analyzed. The formula we derived for the received signal based on the Normal Mode indicates that the signal is determined by the beamform on the modes of all sources and the samplings of all modes at the receiving depth. Two characteristics of the optimal emergence angle (OEA) are obtained and explained utilizing the aforementioned derived formula. The observed distributions of transmission loss (TL) for different sources and receivers are consistent with the obtained characteristics. The results of this study are valuable for the development and design of active sonar detection.

Seamount Clutter Modeling for Long Range Seabed Reverberation in Deep Sea

Reverberation clutter induced by discrete strong scatterers is an important reason which will increase the false alarm probability of active detection, which seriously affects the performance of active sonar detection. In this paper, taking seamount as an example, the theoretical modeling and simulation of the clutter in the deep-sea induced by seamount are carried out by using the ray-mode theory. Through ray-mode approximation, the acoustic rays in surface and reverse channels are ignored, a theoretical model is proposed to calculate the seabed reverberation clutter induced by seamounts, and the physical mechanism of how the seabed reverberation clutter is induced by seamounts is analyzed. The results show that reverberation intensity will increase in the location of seamount and induce discrete reverberation clutter. The greater the fluctuation of seamount, the greater the reverberation clutter intensity.

Active sonar detection with acoustic spiral waves: experiment and modeling

Active spiral-wave active localization is a technique for determining location of acoustic targets [after Dzikowicz et al., JASA 146, 4821–4830 (2019)], which relies on measuring the phase difference between a reference and spiral wavefronts. This research presents a monostatic model of spiral detection and tracking for multiple targets in sparse noise limited environments. Simulation and experimental results from an acoustic spiral wave beacon in a small underwater test tank will be presented. Results show good agreement to resolve targets in horizontal and vertical dimensions with a compact aperture. [Work supported by ONR 321MS.]

Bio-Inspired Covert Active Sonar Detection Method Based on the Encoding of Sperm Whale Clicks

The covertness of an active sonar is a very important issue and the sonar signal waveform design was studied to improve covertness of the system. Click is one of the most common cetacean sounds, and has excellent detection performance. Meanwhile, existing interception systems normally classify cetacean sounds as ocean noise and filter them out. Based on this, a bio-inspired covert active sonar detection method is proposed by encoding the clicks produced by sperm whales. First, based on the frequency distribution characteristic of sperm whale clicks and frequency-hopping sequence, a set of bionic sub-pulses are constructed by encoding the centroid frequency of the real clicks. Based on the inter-click interval characteristic of the clicks and time-hopping sequence, the bionic sonar signal is constructed by combining the constructed bionic sub-pulses and encoding the inter-pulse interval between two adjacent pulses. Then, a single bionic sonar signal is utilized to estimate the speed and range of the target. Based on the characteristics of sperm whale click trains, a camouflage application method is designed to improve the camouflage ability of the bionic sonar signal. Finally, experiment results show that when the target speed is 5m/s and 10m/s and the signal to noise ratio varies from −20dB to 20dB, the root-mean-square error of estimated speed and range are lower than 0.1m/s and 0.1m, respectively. In addition, the constructed bionic sub-pulses have a 99% probability of being classified into sperm whale clicks. Experimental results demonstrate the effectiveness and covertness of the proposed method.

Bionic covert anti-reverberation active sonar detection method based on imitating whale whistles

Bionic covert anti-reverberation active sonar detection method based on imitating whale whistles

Underwater reverberation suppression based on non-negative matrix factorisation

Reverberation is the main background interference in underwater active sonar target detection that seriously interferes with the extraction of the target highlight echo. In consideration of the difference in the time-frequency distributions of the target highlight echo and reverberation, an underwater reverberation suppression method based on non-negative matrix factorisation is proposed in this study. The Wigner-Ville time-frequency matrix of the underwater target echo is used as the input, and non-negative matrix factorisation is applied to express the time-frequency matrix as a low-rank matrix. The influences of rank selection on the reverberation suppression effect and signal expression of the target highlight echo are analysed. Given that the time-frequency matrix of the target highlight echo cannot be expressed in the low-rank form when transmitting linear frequency modulation signal, this matrix is processed with low-rank preprocessing through matrix rotation. The components of the target highlight echo, which can be expressed in the form of a low-rank matrix, are preserved. By contrast, the components of the reverberation interference, which cannot be represented in such a form, are removed in the underwater target echoes. The simulation and experimental results show that the algorithm can effectively improve the signal-to-reverberation ratio of underwater target echoes.

Horizontal Correlation of Long-Range Bottom Reverberation in Shallow Sloping Seabed

The performance of active sonar detection systems is seriously affected by the reverberation at the bottom of the waveguide in shallow water. In order to improve the performance of active sonar detection, it is necessary to understand the horizontal correlation of shallow-water bottom reverberation in active towed-array processing technology. However, the current research on the spatial correlation of reverberation is mainly based on vertical correlation, little work has been done on the horizontal correlation characteristics of long-distance seabed reverberation, and there is no support from sea test data. In this paper, the coupled mode reverberation model is applied to the horizontal correlation, and is studied according to the receiving position, time, and frequency. The simulation results show that, for the long-range bottom reverberation, the lateral correlation is greater than the longitudinal correlation in the horizontal space. By introducing the adiabatic mode solution, the mathematical model of horizontal correlation in the range-dependent waveguide with depth is derived. The numerical results show that the influence of the seabed dip angle on the horizontal correlation should be considered and that the horizontal correlation is affected obviously by the propagation effects of the sloped sea floor. Finally, the experimental data processing and analysis are given and verify the correctness of the algorithm.

Integrated waveform for continuous active sonar detection and communication

A novel integrated waveform (IW) for continuous active sonar detection and communications is proposed in this study based on a generalised sinusoidal frequency-modulated signal. This study first introduces the mixed modulation of the IW and a model for the transmitting signal, and then it analyses the time and frequency resolution and anti-reverberation capability of the proposed IW. The performance of two underwater acoustic (UWA) communication receivers based on the proposed IW are compared and analysed under Gaussian noise and multipath conditions. A UWA communication experiment was carried out in Songhua Lake in December 2019. According to the numerical simulation and experimental results, it was concluded that the IW proposed in this study can meet the requirements of active sonar detection and UWA communications with satisfactory performance.

Three dimensional height information reconstruction based on mobile active sonar detection

The generation of 3D image is of great significance for underwater exploration. Direct generation underwater 3D images by forward looking sonar are more complicated and have a low resolution. This paper introduces an algorithm for reconstructing 3D altitude information of underwater objects from single 2D sonar image. Underwater information is acquired by a remote operated vehicle(ROV) equipped with an active forward looking sonar. Using the measurement mode provided by the viewpoint software, the altitude information of the object is extracted according to the acoustic shadow information and the echo distance in a single sonar image.

Poles Extraction of Underwater Targets Based on Matrix Pencil Method

The majority of the sonic frequency bands used in active sonar detection and identification are within the resonance region of the target. The poles of target are very important characteristics of the resonance region. This paper analyzes and studies the method of extracting poles by using the matrix Pencil Method. A method which can determine the number of poles of underwater target automatically is proposed. It can average the poles that are gathered to synthesize a point as an alternative pole. Then by setting up a reasonable threshold. The poles with the higher energy in the target echo is extracted as the main pole. Aiming at the problem that the main poles of the target are missing or there are false poles in some directions, the main poles extracted from multiple directions of the target are integrated to obtain the final poles of the target. Finally, to prove the feasibility of proposed novel method echo pole extraction, the experiment was conducted in underwater spherical shell and thin rod in a silencing pool.

Robust Active Sonar Detection in Frequency and Time Dispersive Channels Using Matching Envelope Spectrum of Multi-Pulse LFM Signals

For detecting the target echoes undergoing distortion in frequency and time dispersive channels, a novel robust active sonar detector is proposed. The proposed active detector firstly extracts the matching envelope (ME) of the multi-pulse linear frequency modulation (LFM) signals, and then the peaks of the matching envelope spectrum (MES) contained in the designed grid searching windows are detected. The grid searching windows are designed based on the theoretical analysis of the features of the MES. Lastly, the detector utilizes the detected peaks to make a judgement for determining whether there are target echoes existing in the received signal. In addition, the proposed detector can be applied to detect the multi-pulse single frequency target echoes. The proposed active detector shows a more stable performance in the frequency and time dispersive channels, compared to several classical methods, including the replica correlation (RC), the segmented RC (SRC), and the RC integration (RCI) detectors. Simulation results validate the improved performance of the active detector, showing a gain of 0.5-4 dB compared with more standard state-of-the-art detectors. Experimental results based on sea trial data have also verified the validity and feasibility of the proposed active detector.

Application of adaptive line spectrum enhancer in adaptive matched filter

The most classical detector of active sonar and radar is the matched filter (MF), which is the optimal processor under ideal conditions. Aiming at the problem of active sonar detection, we propose a frequency-domain adaptive matched filter (FDAMF) with the use of a frequency-domain adaptive line enhancer (ALE). The FDAMF is an improved MF. In the simulations in this paper, the signal to noise ratio (SNR) gain of the FDAMF is about 18.6 dB higher than that of the classical MF when the input SNR is -10 dB. In order to improve the performance of the FDAMF with a low input SNR, we propose a pre-processing method, which is called frequency-domain time reversal convolution and interference suppression (TRC-IS). Compared with the classical MF, the FDAMF combined with the TRC-IS method obtains higher SNR gain, a lower detection threshold, and a better receiver operating characteristic (ROC) in the simulations in this paper. The simulation results show that the FDAMF has higher processing gain and better detection performance than the classical MF under ideal conditions. The experimental results indicate that the FDAMF does improve the performance of the MF, and can adapt to actual interference in a way. In addition, the TRC-IS preprocessing method works well in an actual noisy ocean environment.

Rational-Orthogonal-Wavelet-Based Active Sonar Pulse and Detector Design

A family of rational orthogonal wavelets is explored in active sonar detection to achieve Doppler robustness and noise mitigation. The broadband active sonar system is classified as wavelet-based noncoherent subband energy detection. It features a flexible broadband sonar pulse design with low peak-to-average power ratio (PAPR), and a detector of low computation complexity via fast rational wavelet filter bank. The designed family of broadband pulses is based on a combination of multiple basis functions of the complex rational orthogonal wavelet (CROW). Differing from the conventional dyadic wavelet (with an integer scale factor of 2), the CROW has a rational scale factor and much higher resolution in the partition of the time-scale plane. This family of wavelets presents great flexibility in the system design. Design example is presented with minimized PAPR to serve for applications demanding the stealth. The sonar detector is based on the CROW analysis filter bank. Detection performance is analyzed regarding its resistance to Doppler noise and multipath by simulations using a geometric underwater acoustic channel model. The performance of the wavelet-based active sonar system is compared with a linear frequency modulated pulse-based system. The receiver operating characteristic curves demonstrate that the designed system is able to cope with severe multipath, high ambient noise, and severe Doppler dispersion. The framework provides possible solutions for underwater applications in low signal-to-noise ratio and varying mobility conditions.

Robust adaptive beamforming method for active sonar in single snapshot

Forming narrow beams is a useful way for active sonar to anti-reverberation when it works in the shallow water. High-resolution adaptive beamforming with the performance of narrow beamwidths and low sidelobe levels is a better and more efficient method, particularly in the scenario where the installation space for sonar array is limited, such as hull-mounted sonar. Due to the short duration of target echo signal in the complex and varying acoustic channel, conventional adaptive beamforming methods are invalid. Therefore, this paper proposes a robust adaptive beamforming method for active sonar in single snapshot, also called the steered dominant mode rejection (STDMR). Firstly, STDMR steered the sample covariance matrix (STCM) based on wide-band focusing, which the needed number of snapshots is greatly reduced. Secondly, by partial eigendecomposition, the large eigenvalues of the STCM which are greater than the noise energy and their eigenvectors are used for dominant mode rejection (DMR). DMR is a typical eigenspace-based algorithm which has small computational load and fast convergence speed. Finally, modified with the methods of diagonal loading of 3-5dB over the noise energy and signal mismatch protection, improved the robustness of this method. Simulation and experimental data analysis shows that the STDMR method achieves narrow beams and low-level sidelobes in single snapshot. Hence, the STDMR beamformer is an appropriate implementation to use for active sonar detection systems.

Comb waveform optimisation with low peak‐to‐average power ratio via alternating projection

The active sonar detection performance in shallow water is mainly restricted by the reverberation level. When target echoes are separable from reverberation according to Doppler shifts, comb waveforms with the bed-of-nails ambiguity function can achieve reverberation suppression. However, some comb waveforms present significantly low transmitting efficiency measured by the high peak-to-average power ratio (PAPR), which may severely affect the detection performance in a noise-limited scenario. In order to effectively improve their transmitting efficiency, the authors propose an approach of comb waveform optimisation with low PAPR via alternating projection in this study. The main idea is based on designing projection constraint sets and corresponding projection operators to achieve the shaping of comb spectra. Hence, the approach has the capability to make a compromise between the transmitting efficiency and reverberation suppression performance. The PAPR control of geometric comb waveforms is implemented in simulations, which prove the validity of the approach.

Underwater target detection based on fourth-order cumulants beamforming

Obtaining the target echo data of high signal to reverberation ratio (SRR) or signal to noise ratio (SNR) in the complex ocean environment is a key problem to improve the detection capability of underwater targets. In this paper, combined with the expansion characteristics of fourth-order cumulants to the array aperture and the structure of the smallest redundant array, a robust and high-resolution fourth-order cumulants beamforming method based on the smallest redundant array is presented. The target direction-of-arrival estimation (DOA) is achieved by forming a narrow space beam, while the reverberation interference is reduced. For the broadband detection system, combined with fractional Fourier transform (FRFT), the fourth-order cumulants beamforming method is extended to the DOA estimation of LFM signal. According to the signal characteristics difference between the target echo and the reverberation, the reverberation is filtered out in the FRFT domain, which achieves the secondary suppression of reverberation interference in the spatial domain and the transform domain, and further improves the SRR of the target echo signal. The validity of the research method is verified by the processing results of the active sonar target detection experiment.