Affine Frequency Division Multiplexing (AFDM) is an advanced communication waveform designed specifically for time-varying channels. This chirp-based multicarrier modulation technique is computationally efficient, which enables compact sonar implementations while achieving robust sensing performance through flexible parameter adjustments. Such characteristics make AFDM well-suited for Integrated Systems for Underwater Detection and Communication (ISUDC). In this paper, we explore an AFDM-based ISUDC system and propose a waveform model capable of transmitting multiple symbols to increase data capacity. We derive the Wideband Ambiguity Function (WAF) for this waveform and enhance it using complementary sequence coding, which reduces sensitivity to WAF variations and improves detection accuracy. Simulation results demonstrate that the proposed AFDM-based ISUDC waveform, featuring both multi-symbol support and complementary sequence coding, increases data capacity and improves communication bit error rate (BER) compared to traditional ISUDC waveforms. Additionally, the optimized WAF achieves enhanced detection performance, fulfilling critical ISUDC requirements.

Integrated systems for underwater detection and communication (ISUDC) plays a pivotal role in improving sonar integration and efficiency and has become a key research focus. This article tackles the underwater doubly dispersive wireless channel (DDWC) by introducing a novel transmitter side waveform design and a receiver side channel estimation algorithm based on affine frequency division multiplexing (AFDM) within the ISUDC framework. At the transmitter we employ AFDM as the core signal and target minimization of weighted sidelobes in the wideband ambiguity function (WAF). We use numerical analysis to quantify coding effects on the WAF and apply optimized random phase perturbations in P4 encoding via particle swarm optimization (PSO) to enhance detection and improve time Doppler resolution. At the receiver we develop a sparse channel estimation method based on an affine Fourier dictionary, which uses pilot signals to estimate phase perturbations and exploits delay-Doppler sparsity to improve accuracy in dynamic underwater environments while reducing multipath interference. We also derive new bounds on the pairwise error probability (PEP) for underwater acoustic DDWC, including numerical lower bounds and Chernoff upper bounds. Simulations demonstrate that jointly optimizing waveform design and channel estimation reduces PEP and normalized mean-square error (NMSE), provides superior detection for consecutive identical coded symbols and yields an ideal “thumbtack” shaped WAF. The proposed framework delivers a reliable and efficient solution for ISUDC in complex underwater environments.

Orthogonal signal-division multiplexing (OSDM) is an attractive alternative to conventional orthogonal frequency-division multiplexing (OFDM) since it can reduce the peak-to-average power ratio and provide more flexibility. However, the overlap-add operation in the traditional zero padded (ZP) OSDM system incurs information loss. To cope with this issue, we investigate the use of frequency-domain oversampling for ZP-OSDM in this letter. However, this comes at the price of a cubic direct equalization complexity. To ease this computational burden, a low-complexity equalization algorithm is developed, which can achieve linear complexity in the transformed domain. Numerical results show that the proposed frequency-domain oversampled ZP-OSDM not only outperforms traditional ZP-OSDM and frequency-domain oversampled ZP-OFDM, but also exhibits robustness against residual carrier frequency offset.

The complex underwater environments pose major challenges to acoustic target recognition with insufficient labeled samples and mismatched domain issues. Although current few-shot learning (FSL) methods could alleviate the data scarcity problem, yet they still suffer from limited application scenarios and poor performance. Here, this article proposes a novel domain-adapted few-shot underwater acoustic target recognition (UATR) method based on environmental feature adaptation and frequency feature contrast (EFFC) that fully leverages unlabeled samples in the target domain to enhance model fine-tuning performance. First, an environmental feature adaptation module is purposely designed to integrate the weighted statistics of unlabeled samples from the current domain to capture the environmental information, promoting rapid adaptation to new environments. Next, a frequency feature contrast module is specifically devised by utilizing contrastive-learning to understand the characteristics of frequency bands from augmented, unlabeled samples, enabling the model to learn the general feature representations of ship-radiated noise. The performance is comprehensively evaluated on three public datasets, ShipsEar, DeepShip, and QiandaoEar22, as well as our dataset, DanShip, which is publicly available athttps://github.com/NPU-416/DanShip. Experimental results demonstrate that the model achieves the highest accuracy rates of 72.91%, 85.67%, 98.67%, and 82.56% on the ShipsEar, DeepShip, QiandaoEar22, and DanShip datasets, respectively, outperforming the other FSL methods.

Underwater long-distance wireless communication (ULWC) is a critical challenge in many applications, such as marine environmental monitoring, underwater remote control, and underwater navigation, to name a few. However, very little literature focuses on ULWC, especially where the communication distance ups to thousands of kilometers, which is urgently required in the Underwater Internet of Things (UIoT) in the large-scale and deep sea. In this article, to improve the underwater communication capacity at a level of thousands of kilometers, we propose a three-hop underwater wireless acoustic communication (3H-UWAC) structure based on the sound fixing and ranging (SOFAR) channel. The proposed 3H-UWAC consists of transmitters, relay stations (RSs), and receivers. Different from the existing ULWC, 3H-ULWC can improve energy efficiency with a small vertical directivity angle (VDA). Due to the characteristics of UWAC, the straight-line communication link can be realized in the proposed three hops, and the communication distance can be increased to thousands of kilometers. Respecting the randomness of underwater devices, tools from stochastic geometry are used to model the spatial distributions of transmitters’, receivers’, and RSs’ locations. RSs are set on the SOFAR channel at a known depth. In the first hop, the transmitter sends information to the nearest first RS (NFRS) on the SOFAR plane. In the second hop, the NFRS sends information to the nearest RS, which is called the nearest second RS (NSRS), to the receiver on the SOFAR plane. In the third hop, SNFS sends information to the receiver. All three communication hops can be achieved with a narrow beam width, where the energy efficiency is improved critically. With given densities of transmitters, RSs, and receivers, the coverage probabilities (CPs) of the three hops (transmitter to first RS (FRS), FRS to second RS (SRS), and SRS to receiver) are analyzed, and the final CP from a transmitter to a receiver through the 3H link is derived. Insights about the effects of VDAs at the transmitters, FNRS, and SNRS, as well as the depths of transmitters and receivers, are revealed. A rapid optimization method is proposed based on the analytical results. The accuracy of the analysis is verified by Monte Carlo simulations.

Efficient target localization is critical to many marine applications in the Internet of Underwater Things (IoUT). Doppler effect becomes more predominant in the underwater environment when the relative speed of the moving object, i.e., the observer, to the signal propagation speed in water is much larger than that in the air. This along with the observer-target geometry will bring in a notable impact on the localization performance. In this article, we derive the Cramér–Rao lower bound (CRLB) and formulate the A-optimality criterion-based observer trajectory optimization problem to improve the localization performance based on time delay and Doppler shift measurements. We show that in the worst case scenario, there will be a conflict between the nonaccessible zone constraint and the observer dynamics constraint, which will lead to an erroneous result. To address this problem, we propose a warning zone-based augmented Lagrange multiplier method (ALMM) where the nonaccessible zone constraint is relaxed to resolve the conflict and ensure the nonaccessible requirement of the targeted zone is maintained. Performance evaluations are conducted through extensive simulations for different scenarios, and the results are compared to other methods with or without trajectory optimization. We demonstrate that trajectory optimization using time delays and Doppler shifts can greatly improve the target localization accuracy in underwater networks.

In this paper, we propose a novel clustered multitask diffusion RLS (MT-DRLS) algorithm over network to further improve the performance of its counterpart, the multitask diffusion LMS (MT-DLMS) algorithm. Its transient behavior is investigated, in the mean and mean-square error sense. Simulation results illustrate the significant improvement of the MT-DRLS over the MT-DLMS in terms of convergence rate and steady-state error, as well as the accuracy of the theoretical findings.

International audience

We propose a Taylor expansion multiple signal classification (TE MUSIC) method for joint direction of departure (DOD) and direction of arrival (DOA) estimation in a bistatic multiple-input multiple-output (MIMO) array. First, using a Taylor expansion of the steering vector, a two-dimensional (2D) search in the conventional MUSIC method for MIMO arrays is reduced to a two-step one-dimensional (ID) search in the proposed TE MUSIC method. Second, DOAs of the targets can be achieved via Lagrange multiplier by a ID search. Finally, substituting the DOA estimates into the 2D MUSIC spectrum function, DODs of the targets are obtained by another ID search. Thus, the DOD and DOA estimates can be automatically paired. The performance of the proposed method is better than that of the MIMO ESPRIT method, and is similar to that of the 2D MUSIC method. Furthermore, due to the ID search, the TE MUSIC method avoids the high computational complexity of the 2D MUSIC method. Simulation results are presented to show the effectiveness of the proposed method.

Driven by the huge demand to explore oceans, underwater wireless communications have been rapidly developed in the past few decades. Due to the complex physical characteristics of water, acoustic wave is the only media available for underwater wireless communication at any distance. As a result, underwater acoustic communication (UAC) is the major research field in underwater wireless communication. In this paper, characteristics of underwater acoustic channels are first introduced and compared with terrestrial communication to demonstrate the difficulties in UAC research. To give a general impression of the UAC, current important research areas are mentioned. Furthermore, different principal modulation-based schemes for short- and medium-range communications with high data rates are investigated and summarized. To evaluate the performance of UAC systems in general, three criteria are presented based on the research publications and our years of experience in high-rate short- to medium-range communications. These three criteria provide useful tools to generally guide the design and evaluate the performance of underwater acoustic communication systems.

Underwater wireless sensor networks (UWSNs) can provide a promising solution to underwater target tracking. Due to limited energy and bandwidth resources, only a small number of nodes are selected to track a target at each interval. Because all measurements are fused together to provide information in a fusion center, fusion weights of all selected nodes may affect the performance of target tracking. As far as we know, almost all existing tracking schemes neglect this problem. We study a weighted fusion scheme for target tracking in UWSNs. First, because the mutual information (MI) between a node’s measurement and the target state can quantify target information provided by the node, it is calculated to determine proper fusion weights. Second, we design a novel multi-sensor weighted particle filter (MSWPF) using fusion weights determined by MI. Third, we present a local node selection scheme based on posterior Cramer-Rao lower bound (PCRLB) to improve tracking efficiency. Finally, simulation results are presented to verify the performance improvement of our scheme with proper fusion weights.

Single-carrier with frequency domain equalization (SC-FDE) has been considered for bandwidth efficiency underwater acoustic (UWA) communication recently due to its reduced computational complexity and low peak-to-average power ratio. A multi-channel time-frequency domain equalization method for pseudurandom noise (PN) based SC-FDE is proposed in this paper. The proposed equalizer includes a multi-channel frequency domain equalizer followed by a low order multi-channel adaptive time domain decision feedback equalizer (DFE). The proposed algorithm is applied to the real data receiving from a lake test conducted in November 2011. It is demonstrated that the uncoded error-free data rates of around 1500 and 3000 bps are achieved using one transmitter and six-channel receiving hydrophone array at a distance of 1.8 km. Experiment results shows that the performance can be enhanced by 4.5-5.5 dB in terms of output signal-to-noise ratio (SNR).

In this paper, we consider the problem of power constrained partially coherent distributed detection over fading multi-access channel. The deflection coefficient maximization (DCM) is used to optimize the performance of detectors. Two cases of the channel gain information are considered separately at the fusion center, one case with perfect channel gain (the corresponding method is referred to as PC-DCM, with PC being the abbreviation for “partially coherent”), the other case with statistical information of channel gain (the corresponding method is referred to as PC-DCM-CS, with CS being the abbreviation for “channel statistics”). We derive the closed-form solutions to the considered problems. Monte-Carlo simulations are carried out to verify the performance of the proposed methods. Simulation results show that the proposed new methods could significantly improve the detection performance of the fusion system at low signal-to-noise ratio (SNR).

A new generalized eigenstructure-based 3-dimensional joint estimator (GETJE) for the direction, frequency, and time-delay of multiple sources is presented. For 2-dimensional joint parameter estimation, we proposed an ESPRIT-based algorithm (Qunfei Zhang and Jianguo Huang, Int. Conf. On ASSP, 1999). Now we extend it to the 3-dimensional estimator. Using a single echo wave, the bearings, frequencies and time-delays of multiple reflectors are jointly estimated. We construct 2 sub-arrays like ESPRIT, and then conduct generalized eigen-decomposition for their auto-correlation matrix and cross-correlation matrix. Bearing parameters can be estimated from eigenvalues, while frequency parameters can also be obtained from corresponding eigenvectors. After modifying the time-delay vectors of the envelop of the emitting signal according to the estimated frequencies, the time-delay parameters can be obtained simultaneously. Computer simulations show that the GETJE can carry out the 3-dimensional joint parameter estimation without additional pairing in the case of lower SNR. Preferable results are also obtained in water tank experiments, which indicate that the GETJE is robust for sensor array errors and has potential applications.

Joint estimation of direction of arrival (DOA) and time-delay plays a great role in source localization, which attracts many researchers not only in the areas of radar, sonar, geological exploration but also in wireless communication. M. Wax (see IEEE Trans. on SP, vol.45, no.10, p.2477-84, 1997) applies approximate MLE with iteration algorithm, which convert a 2-D search into two or three 1-D search. A.J. van der Veen (see IEEE Trans. on SP, vol.46, no.2, p.405-18, 1998) use 2-D ESPRIT to conduct joint estimation. Both of them show good performance at a cost of large computation. Both of them require deconvolution in the frequency domain to transfer time-delay into phase. The deconvolution lends to two problems. One is blowing up noise, the other is leading to spurious peak if the emitted signal is non-minimum phase. In this paper, a simple method using 1-D ESPRIT is presented to complete joint estimation of DOA and time-delay, which requires no deconvolution. It is suitable for active underwater localization where a non-minimum phase signal is frequently employed. The method can estimate parameters of three reflectors with big difference between amplitudes as large as 12 dB. The statistical performance of new estimators and the probability of correct pairing are given by computer simulations. It shows that better performance of the new method can be achieved for multiple source localization even in low SNR.