Aiming at the real-time observation requirements in marine science and ocean engineering, based on underwater acoustic communication and satellite communication technology, a seabed real-time sensing system for in-situ long-term multi-parameter observation applications (SRSS/ILMO) is proposed. It consists of a seabed observation system, a sea surface relay transmission buoy, and a remote monitoring system. The system communication link is implemented by underwater acoustic communication and satellite communication. The seabed observation system adopts the “ARM + FPGA” architecture to meet the low power consumption, scalability, and versatility design requirements. As a long-term unattended system, a two-stage anti-crash mechanism, an automatic system fault isolation design, dual-medium data storage, and improved Modbus protocol are adopted to meet the system reliability requirements. Through the remote monitoring system, users can configure the system working mode, sensor parameters and acquire observation data on demand. The seabed observation system can realize the observation of different fields by carrying different sensors such as those based on marine engineering geology, chemistry, biology, and environment. Carrying resistivity and pore pressure sensors, the SRSS/ILMO powered by seawater batteries was used for a seabed engineering geology observation. The preliminary test results based on harbor environment show the effectiveness of the developed system.

With the goal of achieving high stability and reliability to support underwater point-to-point communications and code division multiple access (CDMA) based underwater networks, a direct sequence...

As a communication system for maritime monitoring and navigation, automatic identification system (AIS) has been employed for many years, but its service range is limited in 40 nautical miles. Fortunately, an updated service navigation system named as space-based AIS has been presented in recent years, which can provide global coverage service. However, it encounters frequency offset issue caused by the relative satellites/ships motion. To cope with it, in this paper, a novel Doppler shift estimation algorithm is proposed for space-based AIS signals over satellite-to-ship wireless fading channels and non-Gaussian noise. In the estimation stage, the signals including the Doppler shift information are firstly separated from the received ones, but they are also disturbed by the noise. Then, Doppler shift is extracted from the above detached signals via the higher moments which cancel some excrescent parameters by using several flexible algebra operations, and its estimated expression is presented. Finally, numerical simulations are carried out to verify the performance of the proposed method, and simulation results demonstrate the benefits of the suggested scheme.

Orthogonal signal division multiplex (OSDM) is an emerging signal modulation technology which has a lower peak-to-average power ratio (PAPR) and a flexible subcarrier system architecture. Particularly, it can be seen as a bridge between the single-carrier modulation and the orthogonal frequency division multiplexing (OFDM) modulation in the frequency domain. Aiming at the development trend and demand of underwater acoustic hybrid and adaptive modulation communication technology, a pseudo-noise (PN) sequence-based underwater acoustic OSDM communication system is proposed in this paper. A data frame structure with PN sequence is designed to solve the multipath and Doppler effect of underwater acoustic channel. On the basis of the PN sequence, a compressive sensing method based on the orthogonal matching pursuit (OMP) algorithm and the minimum mean square error (MMSE) algorithm is designed for channel estimation and equalization. On the basis of the system construction, the relationship among the OSDM vector length M, the OSDM subcarrier number N, and the underwater acoustic channel length is further studied for adaptive modulation of underwater acoustic communication. Finally, the proposed system is verified by simulation. The OSDM system has lower and controllable PAPR. When the OSDM vector length M is bigger than the channel length, and the system subcarrier flexibility is guaranteed, the bit error rate (BER) of the OSDM system is lower than that of the OFDM system and the single-carrier system. The PN sequence-based compressive sensing channel estimation and equalization with the OMP and MMSE algorithms has a good performance to resist the multipath effect of underwater acoustic channel.

Dynamic underwater acoustic network is a research hotspot. Due to the complexity and time-varying of underwater acoustic channel, the performance of single-mode underwater acoustic communication system is often limited by the worst channel situation. Orthogonal signal division multiplexing (OSDM) is a new signal modulation technology, which can be regarded as a bridge between single carrier modulation and orthogonal frequency division multiplexing (OFDM) modulation. In order to improve the channel adaptive ability of underwater acoustic communication system and obtain a unified architecture of different carrier modulation, an adaptive multi-mode underwater acoustic communication system based on OSDM and direct sequence spread spectrum modulation (AMMUAC/OS) is proposed in this paper. Combined with spread spectrum modulation, the system can realize single carrier time domain spread spectrum (SC-TDSS), single carrier system with cyclic prefix (SC-CP), OSDM, multicarrier frequency domain spread spectrum (MC-FDSS), and OFDM communication system by adjusting the vector length M of OSDM. The addition of a variety of digital mapping methods enables the system to achieve multi-mode communication with a unified architecture. Based on the relationship between the OSDM vector length M and the underwater acoustic channel delay, a joint adaptive decision criterion based on the maximum channel delay and the channel signal-to-noise ratio (SNR) is proposed. Firstly, the OSDM vector length M is determined according to the maximum channel delay, and then the system communication mode is selected according to the channel SNR. Orthogonal matching pursuit (OMP) channel estimation algorithm is used to obtain channel information and minimum mean square error (MMSE) channel equalization algorithm is used for channel compensation. An adaptive multi-mode data frame structure is designed for the interaction between the sender and the receiver. The simulation results show that the proposed AMMUAC/OS can adapt to underwater acoustic channels with different channel delay and SNR.

Shipborne high-frequency surface wave radar (HFSWR) systems face the challenge of sea clutter spreading, which obscures vessel echoes and makes detection difficult. In this article, we propose a novel 3-D target detection algorithm that effectively identifies vessel targets in sea clutter using multidimensional fusion features. The algorithm consists of two stages: 3-D spectrum construction and target detection. In the 3-D spectrum construction stage, the digital narrow beam forming (DNBF) method is combined to transform the range-Doppler (RD) spectrum into a range-Doppler–azimuth 3-D spectrum. In the target detection stage, a two-level cascade target detection algorithm is proposed. At the first level, a 3-D extremum detection algorithm identifies potential vessels in sea clutter from the 3-D spectrum and locates the 3-D tensor blocks containing high-dimensional morphology features of these potential vessels. At the second level, we introduce an intelligent 3-D tensor block classifier, which includes a two-channel 3-D feature-extraction network and a feature classifier. This network extracts 3-D morphology features from the tensor blocks using 3-D discrete wavelet transform and a 3-D convolutional neural network (CNN). The extracted features are then fused using robust sparse linear discriminant analysis (RSLDA), and an extreme learning machine processes the fusion features to produce the final results. The experimental results show that the proposed algorithm outperforms state-of-the-art methods in terms of detection rate and false alarm rate.