Time domain turbo equalization based on vector approximate message passing for multiple-input multiple-output underwater acoustic communications.

This paper proposes a high-performance receiver for underwater acoustic communications based on time reversal processing for multiple-input multiple-output (MIMO) systems. The receiver employs the vector approximate message passing (VAMP) algorithm as a soft equalizer in turbo equalization. By performing self-iteration between the inner soft slicer and the inner soft equalizer, the VAMP algorithm achieves near-optimal performance. Furthermore, an iterative channel-estimation-based soft successive interference cancellation method is incorporated to suppress co-channel interference in the MIMO system. Additionally, the introduction of passive time reversal technology can combine multiple channels into a single channel, which greatly reduces the computational complexity of the MIMO system, especially for large MIMO systems. The effectiveness of the proposed receiver is verified using experimental data collected in Songhua Lake, China in 2019. The results demonstrate that the proposed receiver significantly reduces the complexity of the traditional parallel-VAMP receiver without sacrificing performance and outperforms other receivers of the same type. Moreover, our experimental results also verify that the VAMP-turbo outperforms the generalized approximate message passing (GAMP)-turbo in terms of bit error rate and convergence performance.

Deep transfer learning-based variable Doppler underwater acoustic communications.

This paper proposes a deep transfer learning (DTL)-based variable Doppler frequency-hopping binary frequency-shift keying underwater acoustic communication system. The system uses a convolutional neural network (CNN) as the demodulation module of the receiver. This approach directly demodulates the received signal without estimating the Doppler. The DTL first uses the simulated communication signal data to complete the CNN training. It then copies a part of the convolution layers from the pre-trained CNN to the target CNN. After randomly initializing the remaining layers for the target CNN, it is trained by the data samples from the specific communication scenarios. During the training process, the CNN learns the corresponding frequency from each symbol in the selected frequency-hopping group through the Mel-spectrograms. Simulation and experimental data processing results show that the performance of the proposed system is better than conventional systems, especially when the transmitter and receiver of the communication system are in variable speed motion in shallow water acoustic channels.

Robust adaptive beamforming based on zone orthogonal constraint and steering vector estimation.

This Letter solves steering vector estimation under mismatch for adaptive beamforming. The proposed beamformer implements a stepwise estimation of steering vector, and zone orthogonal constraint is added first based on adaptive constraint framework from Khabbazibasmenj [IEEE Trans. Signal Process. 60(6), 2974-2987 (2012)], which ensures that the estimated steering vector does not converge to an interference steering vector outside the predefined sector, even if the sector deviates from the central observation area of arrays. Then uncertainty set error constraint is used to improve the estimation accuracy. The numerical simulation and experimental results verify the effectiveness of the proposed method.

Ocean ambient noise on the Chukchi Plateau and its environmental correlates.

Conducting research on ocean ambient noise under different sea ice conditions is highly important for the comprehension of the rapidly changing Arctic. We present the first results of ambient noise and its relationship to environmental forcing during the open-water, ice transition and ice-covered periods on the Chukchi Plateau. The ambient noise level (ANL) in the 20 Hz to 2 kHz band is higher, intermediate and lower during the open-water, ice transition and ice-covered periods, respectively. During the ice-covered period, the ambient noise is dominated by the ice-generated noise due to sea ice activities and shows a negative correlation with temperature. Therefore, when the temperature decreases, the sea ice is prone to shrinking and cracking, thus increasing the sea ice activities and resulting in increased ice-generated noise; when the temperature rises and is relatively high in May and June, the ANL is lowest for the sea ice inhibition to wind waves and decreased sea ice activities induced by temperature rise. Sea ice is the most predominant environmental factor affecting Arctic ocean ambient noise, and the ANL can potentially increase due to a reduction in Arctic sea ice and increase in human activities caused by global climate change.

Phenazine-Based Molecular Actuators: The Second Generation.

A streamlined second generation of redox-responsive phenazine-based butterfly coil foldamers has been developed using a novel Z-shaped linker. Their ability to undergo fully reversible extension-contraction has been demonstrated using catalytic hydrogenation and bulk electrolysis.

Blind beamforming-based strong interference suppression in underwater acoustic direct-sequence code-division multiple-access systems.

In an underwater acoustic direct-sequence code-division multiple-access (DS-CDMA) system, the performance of the conventional receiver is severely limited by the strong multiple-access interferences, which is due to the near-far effect. In this paper, a time-frequency-time with eigendecomposition-based blind beamformer (TFT-EBB) method is proposed for a distant user to suppress strong interference from a nearby user in DS-CDMA underwater acoustic communications. When the interference level is moderately higher than that of the desired signal, the TFT-EBB method can estimate the composite steering vector of all multipath components of the weak desired user signal via the eigendecomposition of the array covariance matrix at each frequency bin. Then the proposed energy detection-based RAKE receiver is cascaded to achieve multipath diversity, in which it requires less prior information compared with the conventional RAKE receiver. The proposed method is evaluated by using both simulated and field experimental data, which verifies its effectiveness.

Phenazine-Based Oligomers as Redox-Responsive Molecular Actuators.

Nanosized butterfly-coil foldamers containing alternating phenazine-1,6-dicarboxamide and 2,5-dialkoxyterephthalamide moieties have been demonstrated to undergo extension-contraction in response to changing their oxidation state. Both the chemical (catalytic hydrogenation/aerial oxidation) and electrochemical versions of this process have been shown to be clean and fully reversible.

Wideband signal detection in multipath environment affected by impulsive noise.

Detecting the presence or absence of a known signal is an important aspect of underwater acoustic (UWA) communications as it is a vital first step to process the received data. The influence of impulsive noise and multipath propagation on detection are both considered in this paper. Many robust detectors have been designed to cope with impulsive noise, but they tend to ignore the impact of multipath propagation, which may decrease the detection probability. To emphasize the role of multipath channel, we propose two-stage detection methods. In the first stage, the channel is estimated based on robust orthogonal matching pursuit, while in the second stage, detectors that use the channel estimation from the first stage, namely augmented log-likelihood ratio detector and augmented pseudo-correlation detector, are developed. The former detector is parametric and the latter one is non-parametric. The improved performance is demonstrated in simulated multipath channel and actual UWA channel with both simulated noise and recorded snapping shrimp noise, indicating that the proposed detectors are resistant to impulsive noise. It is also shown that the use of multipath information helps to improve the detection performance.

Label distribution-guided transfer learning for underwater source localization.

Underwater source localization by deep neural networks (DNNs) is challenging since training these DNNs generally requires a large amount of experimental data and is computationally expensive. In this paper, label distribution-guided transfer learning (LD-TL) for underwater source localization is proposed, where a one-dimensional convolutional neural network (1D-CNN) is pre-trained with the simulation data generated by an underwater acoustic propagation model and then fine-tuned with a very limited amount of experimental data. In particular, the experimental data for fine-tuning the pre-trained 1D-CNN are labeled with label distribution vectors instead of one-hot encoded vectors. Experimental results show that the performance of underwater source localization with a very limited amount of experimental data is significantly improved by the proposed LD-TL.

Acylative Kinetic Resolution of Cyclic Hydroxamic Acids.

Racemic cyclic hydroxamic acids bearing an aryl substituent adjacent to the hydroxyl group undergo effective acylative kinetic resolution promoted by benzotetramisole (BTM).

Are Stringent Containment and Closure Policies Associated with a Lower COVID-19 Spread Rate? Global Evidence.

Stringent government policies, in general, and strict containment and closure policies in particular including workplace closing, restrictions on gatherings, close of public transport, stay-at-home order, restrictions on internal movement, and international travel control are associated with a lower spread rate of COVID-19 cases. On the other hand, school closures and public event cancellations have not been found to be associated with lower COVID-19 spread. Restrictions on international travel and the closing of public transport are two policies that stand out and have a consistent and slowing effect on the spread of COVID-19. The slowing effect of the containment and closure policies on the spread of COVID-19 becomes stronger one week after the policies have been implemented, consistent with the SARS-CoV-2 transmission pattern and the incubation period evolution. Furthermore, the slowing effect becomes stronger for culturally tight countries and countries with a higher population density. Our findings have important policy implications, implying that governments need to carefully implement containment and closure policies in their own countries' social and cultural contexts, with an emphasis on the ideas of the common interest, personal responsibility, and the sense of community.

Ambient noise under stably covered ice.

Sea ice and freshwater ice can be different in terms of physical and acoustic characteristics, such as density, salinity, etc. In this paper, under-ice ambient noise in the Mudan river (Jilin Province, Northeast of China) is analyzed using the data recorded by autonomous hydrophones to test if the river ice environment is an effective analog for studying under-ice noise of multi-year ice sheets in the Arctic. The noise spectrum level below 250 Hz and above 1 kHz decreases linearly with the increase in the logarithmic frequency in a quiet environment. The ice cracks are detected and extracted, and Pearson correlation analysis between meteorological information and cracks is carried out. Frequency correlation matrixes are calculated to obtain the correlation between pairs of frequencies and evaluate the frequency correlation of ice crack noise of two hydrophones under different depths, different distances, and different times. Finally, the paper compares the experimental results with Arctic under-ice noise in the literature. Similarities with Arctic under-ice noise are observed in the experiment, including noise spectrum, cracks' peak frequency, and correlations between temperature and crack intensity. This paper believes that the study of under-ice noise in freshwater rivers can be used to simulate multi-year ice regions in the Arctic in terms of thermal-induced cracks and meteorological correlation. And future research is needed to prove this judgment further.

Iterative channel estimation-based soft successive interference cancellation for multiuser underwater acoustic communications.

This paper presents a single-carrier multiuser receiver in underwater acoustic communications with strong multiple access interference (MAI) combining passive time-reversal (PTR) and direct-adaptation-based turbo equalization. The receiver works in an iterative block by block manner. In the first iteration, when the symbols of all users are detected by successive interference cancellation (SIC) in the block, the channel impulse response (CIR) of each user is then updated by post-SIC signal to achieve more accurate MAI reconstruction and PTR combination for the next block. In the following iterations, the a priori mean of symbol in the current block is available and used to further improve the accuracy of reconstructed MAI and the updated CIR. The proposed receiver is demonstrated using experimental data collected at Songhua Lake, China, in 2019. The results show that single-carrier nine-user communication data with quadrature phase-shift keying can be successfully recovered, with an average data rate of 1.67 kbps for each user.

[Levels, Characteristics, and Potential Source of Micro(meso)plastic Pollution of Soil in Liaohe River Basin].

With the Liaohe River basin as the research object, the morphology, abundance, and distribution characteristics of micro(meso) plastics of soil in Liaohe River basin were studied based on the density flotation principle and the technique of stereo microscope and micro-FTIR and the significant factors affecting the distribution of the micro(meso)plastics and their potential sources were reasonably speculated. The results indicated that the average abundance of the soil micro(meso)plastic is (145.83±211.46) n·kg-1. The most abundant types of micro(meso)plastics are debris (46.00%), <1000 µm (39.57%), PP (41.71%), and white (46.86%). Among them, Rayon, PES, and PET micro(meso)plastics are primarily in the shape of fibrous (>85%), PE is mostly in the shape of film and fragments (96.91%), PP is mainly in the shape of fragments (85.62%), and PS is primarily in the shape of foam. Industrial activities (express delivery companies, plastic factories, and clothing factories), agricultural activities (plastic mulch, sewage irrigation, and sludge composting), population density, and sewage treatment plants, etc, may lead to higher levels of micro(meso)plastic abundance in the soil of the study area. Plastic products (pesticide bottles, chemical fertilizer packaging bags, woven bags, and plastic agricultural films), sewage discharge and irrigation, and foam materials used for packaging and decoration are the potential sources of soil micro(meso)plastic in the region.

Frequency-domain equalization with interference rejection combining for single carrier multiple-input multiple-output underwater acoustic communications.

This paper describes a three-step frequency-domain equalization scheme for multiple-input multiple-output (MIMO) underwater acoustic communication. First, an iterative least-squares channel estimation method is developed to enhance the accuracy of channel estimation in MIMO communication. The interference rejection combining method is then adopted to suppress co-channel interference based on the estimated MIMO channels. This technique exploits the correlation between the interference received through different channels. Finally, a decision feedback equalizer embedded with a digital phase-lock loop is cascaded before the final determination of equalized symbols to compensate the phase rotation. Experimental results show that the bit error rates of the proposed scheme can be several orders of magnitude lower than those of conventional frequency-domain equalization schemes.

Phenazine-1,6-dicarboxamides: Redox-Responsive Molecular Switches.

We introduce phenazine-1,6-dicarboxamides as redox-responsive molecular switches. The reduction of their phenazine core transforms them from hydrogen-bond acceptors into hydrogen-bond donors and thus forces the secondary amide substituents to turn around. The resulting conformational changes are envisioned to form the basis for butterfly coil foldamers undergoing reversible extension and contraction in response to changing their oxidation state.

Group sparse underwater acoustic channel estimation with impulsive noise: Simulation results based on Arctic ice cracking noise.

Many underwater acoustic (UWA) channels exhibit impulsive noise, thereby severely degrading the performance of traditional channel estimation algorithms. This paper presents two channel estimation algorithms for impulsive noise, namely (i) the variable forgetting factor l1,0 recursive least sign algorithm (VFF-l1,0-RLSA) and (ii) the variable forgetting factor l2,0 recursive least sign algorithm (VFF-l2,0-RLSA), both of which exploit the group sparse multipath structure and maintain robustness under impulsive noise. By using the l1 norm of the estimation error as part of the cost function, RLSAs are better at detecting and rejecting impulsive noise than the recursive least squares algorithms. A mixed l1,0 or l2,0 norm is incorporated with a RLSA to achieve better performance in group sparse UWA channel estimation. The time-varying forgetting factor and regularization parameter in the two proposed algorithms help to improve their performance. Simulation results based on Arctic ice cracking noise demonstrate the robustness and superiority of the two proposed algorithms.

An active detection method for an underwater intruder using the alternating direction method of multipliers.

The underwater surveillance of harbors is challenging, as the reverberation-limited environment means that intruders with a weak target strength, such as autonomous underwater vehicles and frogmen, may be overlapped or even overwhelmed by reverberations. In recent years, developments in low-rank and sparsity theory have presented an innovative idea for intruder detection. This paper describes a method in which multi-frame data containing echoes of an intruder and reverberations are arranged in a matrix, and then the data matrix is decomposed to achieve detection. Based on this idea, the alternating direction method of multipliers (ADMM) is applied to the problem of intruder detection. The key parameters of ADMM are discussed and recommended values are given. The proposed method is validated and evaluated through a series of experiments.

Moving Target Detection Using Dynamic Mode Decomposition.

It is challenging to detect a moving target in the reverberant environment for a long time. In recent years, a kind of method based on low-rank and sparse theory was developed to study this problem. The multiframe data containing the target echo and reverberation are arranged in a matrix, and then, the detection is achieved by low-rank and sparse decomposition of the data matrix. In this paper, we introduce a new method for the matrix decomposition using dynamic mode decomposition (DMD). DMD is usually used to calculate eigenmodes of an approximate linear model. We divided the eigenmodes into two categories to realize low-rank and sparse decomposition such that we detected the target from the sparse component. Compared with the previous methods based on low-rank and sparse theory, our method improves the computation speed by approximately 4⁻90-times at the expense of a slight loss of detection gain. The efficient method has a big advantage for real-time processing. This method can spare time for other stages of processing to improve the detection performance. We have validated the method with three sets of underwater acoustic data.

Multitarget Tracking Algorithm Using Multiple GMPHD Filter Data Fusion for Sonar Networks.

Multitarget tracking algorithms based on sonar usually run into detection uncertainty, complex channel and more clutters, which cause lower detection probability, single sonar sensors failing to measure when the target is in an acoustic shadow zone, and computational bottlenecks. This paper proposes a novel tracking algorithm based on multisensor data fusion to solve the above problems. Firstly, under more clutters and lower detection probability condition, a Gaussian Mixture Probability Hypothesis Density (GMPHD) filter with computational advantages was used to get local estimations. Secondly, this paper provided a maximum-detection capability multitarget track fusion algorithm to deal with the problems caused by low detection probability and the target being in acoustic shadow zones. Lastly, a novel feedback algorithm was proposed to improve the GMPHD filter tracking performance, which fed the global estimations as a random finite set (RFS). In the end, the statistical characteristics of OSPA were used as evaluation criteria in Monte Carlo simulations, which showed this algorithm's performance against those sonar tracking problems. When the detection probability is 0.7, compared with the GMPHD filter, the OSPA mean of two sensor and three sensor fusion was decrease almost by 40% and 55%, respectively. Moreover, this algorithm successfully tracks targets in acoustic shadow zones.