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We investigate the underwater acoustic scattering from various distributed “ice balls” floating on the water, aiming to understand acoustic scattering in the marginal ice zone (MIZ). The MIZ, including a wide range of heterogeneous ice cover, significantly impacts acoustic propagation. We use acoustic modelling, simulation, and laboratory experiments to understand the acoustic scattering from various distributed ice balls. The acoustic scattering fields from a single sound source (90 kHz) in water are analyzed based on selected principal scattering waves between the surfaces of ice and water. The target strengths are calculated using the plate element method and physical acoustic methods, which are validated with water tank experimental data. The methodology is then extended to multiple ice ball cases, specifically considering a single ice ball, equally spaced ice balls of the same size, and randomly distributed ice balls of various sizes. Additionally, experimental measurements under similar conditions are conducted in a laboratory water tank. The scattering intensities at different receiving positions are simulated and compared with lab experiments. The results show good agreement between experimental and numerical results, with an absolute error of less than 3 dB. Scattering intensity is positively correlated with water surface reflection when the receiving angle is close to the mirror reflection angle of the incident wave. Our approach sets the groundwork for further research to address more complex ice–water interfaces with various ice covers in the MIZ.

Abstract Fast and accurate estimation of sinusoidal signals plays an important role in many fields like communications, radar, sonar, etc. In underwater signal processing applications, sinusoidal signals usually take the form of CW pulses in most practical applications, therefore, zero-padding and duty-cycle show their great importance to the estimation of sinusoidal signals. In this paper, a high-precision estimation algorithm of sinusoidal signal is proposed, which combines amplitude ratio algorithm and fractional Fourier coefficient interpolation algorithm. The proposed algorithm uses the adjacent spectral line ratio algorithm instead of the Fourier coefficient maximum amplitude discrete spectral line search algorithm for coarse estimation, and modifies the traditional interpolation method. The proposed algorithm improves the Fourier coefficient interpolation algorithm by combining zero-padded signals to achieve the accurate frequency estimation for zero-padded sinusoidal signal. The performance of the algorithm is also in accordance with theoretical level for zero-padded signals, which is a great improvement over the frequency estimation algorithm for non-padded signals as well as the algorithm for zero-padding signals. The theoretical results are verified by extensive computer simulations which show that the proposed algorithm can both achieve better results for zero-padding cases and maintain comparable performance with competing algorithms for the non-padded signal. Therefore, the algorithm can be better applied to practical underwater detection or communication signals.

The large propagation delay in underwater acoustic networks results in spatial and temporal uncertainty between communication links. This uncertainty, in turn, leads to problems with spatial unfairness and packet collision in media access control (MAC) solutions. To address these issues, this research paper proposes a spatially fair and low-conflict media access control (SFLC-MAC) protocol. Within the protocol, a contention window spatial fairness adjustment strategy is designed, including random and fair states. Nodes autonomously adjust their contention states based on the perceived network information. Nodes in the fair state increase their listening time to ensure that nodes in the random state can successfully access the channel, thereby overcoming the fairness issues in channel access. A method based on postponing data packet transmission is proposed to avoid collisions between data packets and neighbors’ control packets. By scrutinizing the spatio-temporal constraints pertinent to these conflicts, the exact duration of the delay required for this method is ascertained. Simulation results demonstrate that SFLC-MAC effectively improves network throughput, reduces end-to-end delay, decreases network energy consumption, and enhances channel access fairness among nodes.

The long propagation delay of acoustic links leads to the complex randomness of packet collision, which reduces the network packet delivery rate (PDR) and aggravates network congestion. A single vector hydrophone with directional reception characteristics can concentrate the reception gain on a certain direction, which can increase spatial reuse, reduce packet collision, and help to improve the performance of the underwater acoustic wireless sensor networks (UASNs). Herein, this paper proposes a cross-layer protocol with low interference and low congestion (CLIC) based on directional reception. An integrated routing-medium access control (MAC) design is also devised in the CLIC scheme to use the directional beams to create the least-interfering, highest-capacity data transmission links, weighing key factors affecting network performance to obtain routes with low collisions and low congestion. Simulation results show that the CLIC has a higher packet delivery rate (PDR) and higher energy efficiency compared to the QELAR, CITP, and VBF protocols.

ABSTRACTThis study examines the association between the globalised board of directors and corporate environmental performance, and then investigates the moderating effect of regional green development on the above association. Using a sample from the Chinese stock market during the period of 2008–2016, the findings reveal that the globalised board of directors is significantly positively associated with corporate environmental performance, suggesting that the globalised board of directors can play an important role in strengthening the moral and strategic motivations of corporate environmental responsibility, and enhance corporate environmental performance. Further, regional green development attenuates the positive relation between the globalised board of directors and corporate environmental performance. Above findings are robust to a variety of sensitivity tests and our main conclusions are still valid after controlling for the potential endogeneity between the globalised board of directors and corporate environmental performance. Interestingly, additional tests reveal that the positive effect of foreign directors on corporate environmental performance is more pronounced for those from the countries (regions) with shorter time zone difference, stronger investor protection and better performance in environmental responsibilities.

Aiming at the difficulty of feature extraction of echo signal in active sonar,a self-encoder algorithm based on the combination of denoising self-encoder and convolution denoising self-encoder was proposed.Firstly,the preprocessing of noisy signal was carried out by using the advantage of denoising self-encoder in signal as a whole,and then the local feature of signal was optimized by combining convolutional denoising self-encoder to denoise the signal locally,so as to enhance the signal.The time domain waveform of the received signal is used as the feature input by the algorithm,and retains the signal’s amplitude and phase characteristics.The experimental results show that the algorithm not only effectively reduces the noise component in the signal,but also achieves better recovery effect in both time and frequency domains.

Weighted fractional Fourier transform-based hybrid carrier communication can be regarded as a combination of single-carrier communication and multicarrier communication, providing strong flexibility due to the changeable transform order. The hybrid carrier underwater acoustic communication based on the joint time-frequency domain equalization is proposed in this paper. With the time-domain equalization based on time reversal, multipath spreads of underwater acoustic channels can be greatly suppressed. Thus, the length of the required cycle prefix is shortened, improving the bandwidth efficiency. The residual inter-symbol interference can be removed using frequency-domain equalization based on the minimum mean square error or zero force. The experimental results show that the optimal transform orders to achieve the best communication performance are different in different environments. Compared with the traditional frequency-domain equalization method, the proposed method performs better with respect to bit error rate and bandwidth efficiency.

Due to the advantage of the distributed multisensor detection system which makes sonar detect further and more accurate estimation of the target state, distributed multisensor data fusion algorithms are widely applied to the sonar detection system. However, on the one hand, the most asynchronous algorithms focus on how to convert asynchronous data fusion into synchronous data fusion. On the other hand, sonar detection system suffers from more serious asynchronous data problems (such as more serious random delay and packet loss defaults) than radar and other fields. Therefore, the traditional asynchronous fusion method has some limitations. When the targets are sparse, this paper proposed a novel asynchronous multisonar data integration approach, in which the Gaussian mixture probability hypothesis density (GMPHD) filter is used to filter clutter for local sonar sensor. Then, the Gaussian mixture model (GMM) algorithm is used to model asynchronous data over a period of time. Finally, all local sonar detection data are integrated into a surveillance region image to help to detect the target. Several simulation tests and a sea test are presented in this paper to test this approach performance.

In this study, we examine whether education, as an important component of the human capital of auditors, is related to the occurrence of financial misstatement, and investigate the moderating effect of professional experience. Using a sample of 16,651 firm-year observations from the Chinese stock market from 2003 to 2014, we find that the education level of signing auditors is significantly negatively associated with the likelihood of financial misstatement, which suggests that higher education can enhance the ethics and independence of auditors and mitigate the risk of financial misstatement. In addition, professional experience attenuates the negative relation between the education level of signing auditors and financial misstatement. Our findings are also robust to a variety of sensitivity tests, and our conclusions still hold after using a two-stage OLS-logistic regression to address the endogeneity problem. Lastly, the negative effect of education level on financial misstatement holds only for 985 Project universities, low individual-level (audit-firm-level) client importance, and state-owned enterprises. Keywords: Auditor human capital, Financial misstatement, Education level, Professional experience, Signing auditors, JEL classification: M42, J41, P36

We propose an improved proportionate affine projection algorithm (PAPA), which is realized by integrating a hybrid-norm constraint into the affine projection algorithm (APA) to estimate the cluster sparse signals that are happened in satellite and network echo channels. The proposed algorithm optimizes the hybrid ${l_{2,0}}$ -norm of the filter coefficients, and the PAPA is a special case of the proposed method. Moreover, an enhanced PAPA is modified for the cluster sparse channel estimations. Various simulation experiments are performed to verify that the proposed algorithms are superior to the APA, PAPA, and related sparse algorithms with different input signals and various parameters.

In this paper, an enhanced proportionate normalized least mean square (PNLMS) algorithm with the hybrid l2,0-norm constraint is proposed for block-sparse signal processing. The proposed algorithm penalizes a mixed l2,0-norm on the PNLMS to fully exploit the sparsity and handle block-sparse signals, which is called the l2,0 norm constrained PNLMS (L20-PNLMS). The L20-PNLMS is well derived and carefully analyzed. Various experiments have been constructed to verify the effectiveness of the devised L20-PNLMS. The experimental results demonstrate that the devised L20-PNLMS performs better than the previous PNLMS algorithms do in block sparse signal processing.

Accurate channel information is usually required in under-ice acoustic (UIA) communication, which exhibits a sparse characteristic. A type of norm-constrained least mean square (LMS) algorithm performs well in estimating the real-valued (passband) channels but cannot be directly applied to complex-valued (baseband) channels. This paper generalizes norm-constrained complex LMS. Complex-valued zero-attracting LMS and l0-norm LMS (C l0-LMS) are mentioned first. These two algorithms render a fixed penalty to each coefficient, which may deteriorate the performance. Then, we propose a complex-valued adaption penalized LMS (CAP-LMS) to further utilize the sparsity of the UIA channels. The adaption penalty is achieved by dividingp-norm-like constraints into two separate groups according to the l1norm of each coefficient. For the dominant coefficients in the large group, the norm constraint disappears to reduce the estimation bias. For the small coefficients, the adaption penalty aims to accelerate the convergence speed. Simulation results are presented to demonstrate the superior performance of the CAP-LMS algorithm. Data processing results from two under-ice experiments show the feasibility and validity of the proposed algorithms in practical UIA applications.

To mitigate the inter-symbol interference (ISI), multiple access interference (MAI), and the effect of different Doppler shifts within a data package incurred in variably mobile asynchronous underwater multiuser communications (VMAUMC), a Kalman filter-based chip differential blind adaptive multiuser detection (D-KF-BAMUD) algorithm is proposed in this paper. The Kalman filter-based blind adaptive multiuser detection (KF-BAMUD) algorithm has been adopted to combat ISI and MAI in the scenario of static users, and underwater and under-ice multiuser communication experiments have been carried out to verify the effectiveness of the KF-BAMUD algorithm. To tackle the more challenging VMAUMC, a differential modulation and demodulation technique operating at the chip level is proposed to reduce the impact of Doppler shift residues after the Doppler compensation with an average Doppler frequency offset within each data package. The technique is combined with the KF-BAMUD algorithm, leading to the D-KF-BAMUD algorithm, which is able to effectively handle ISI, MAI, and the effect of Doppler shift residues simultaneously in VMAUMC. This paper reports our experiments on VMAUMC carried out in Songhua River in April 2016 (seven users, data rate 7.87 bit/s, up to 2 m/s variably relative velocity in each data package, and horizontal distance 200-m shallow-water channel between transducer and hydrophone), and the encouraging experimental results demonstrate the effectiveness of the proposed system and the D-KF-BAMUD algorithm.

An adaptive approach is proposed to denoise and detect the underwater sonar image in this paper. Firstly, to improve the denoising performance of non-local spatial information in the underwater sonar image, an adaptive non-local spatial information denoising method based on the golden ratio is proposed. Then, a new adaptive cultural algorithm (NACA) is proposed to accurately and quickly complete the underwater sonar image detection in this paper. Concretely, NACA has two improvements. In the first place, to obtain better initial clustering centres, an adaptive initialization algorithm based on data field (AIA-DF) is proposed in this paper. Secondly, in the belief space of NACA, a new update strategy is adopted to update cultural individuals in terms of the quantum-inspired shuffled frog leaping algorithm (QSFLA). The experimental results show that the proposed denoising method in this paper can effectively remove relatively large and small filtering degree parameters and improve the denoising performance to some extent. Compared with other comparison algorithms, the proposed NACA can converge to the global optimal solution within small epochs and accurately complete the object detection, having better effectiveness and adaptability.

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 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.