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In this paper, we present a full coverage path planning (CPP) algorithm for the marine surveys conducted in the convex polygon shaped search area. The survey is supposed to carry out by torpedo-type AUVs (autonomous underwater vehicles). Due to their nonholonomic mechanical characteristics, these vehicles have nonzero minimum turning radius. For any given polygon shaped search area, it can always be partitioned into one or more convex polygons. With this in mind, this paper proposes a novel search algorithm called CbSPSA (Calculation based Shortest Path Search Algorithm) for full coverage of any given convex polygon shaped search area. By aligning the search inter-tracks alongside the edge with the minimum height, we can guarantee the minimum number of the vehicle's turns. In addition, the proposed method can guarantee the planned path is strictly located inside the polygon area without overlapped or crossed path lines, and also has the total path length as short as possible. Considering the vehicle's nonzero minimum turning radius, we also propose a sort of smoothing algorithm which can smooth the waypoint path searched by CbSPSA so that the vehicle can exactly follow it. The smoothed path is also guaranteed to be strictly located inside the polygon. Numerical simulation analyses are also carried out to verify the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

The tightly coupled global navigation satellite system (GNSS) precise point positioning (PPP) and inertial navigation system (INS) can provide high-precision position, velocity and attitude information. The coupled system utilizes single receiver, which is particularly suitable for the environment without reference station, such as marine survey. In the former works, the integer ambiguity resolution of PPP/INS in terrestrial environment is researched. However, the GNSS observation is severely affected by the multipath effect in marine environment. In addition, the sideslip caused by wind and sea wave also impact float ambiguity estimation, consequently introducing difficulty for PPP ambiguity fixing. Therefore, the PPP/INS tightly coupled model with fixed ambiguity is proposed for marine survey. The correction model of INS gyroscope bias in closed-loop is deduced in detail. The influence of ship motion noise and multipath in marine environment is reduced by introducing the robust factor to the Kalman filter. The feasibility of the method is verified in a real marine experiment, with a detail evaluation of the data quality and positioning accuracy. The results show that the accuracy of PPP/INS can reach centimeter level after fixing the ambiguity in marine environment. Furthermore, the precise INS-predicted position can significantly shorten the re-fixed time of PPP/INS, which proves the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

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Based on the ongoing techniques among control theory, communication networks, and sensor design, unmanned aerial vehicles (UAVs), unmanned undersea vehicles (UUVs) and unmanned surface vehicles (USVs) are experiencing rapid development. Research on these unmanned systems and those intelligent sectors inside has absorbed interests and investments from not only military but also civil organizations. The well-applied fields include surveillance and reconnaissance, surface warfare, antisubmarine warfare, mine countermeasures, oceanic environment monitoring, search and rescue, hydrographic survey, and so on. Comparing with those studies on UAVs and UUVs, the one focusing on USVs was started later and has been developed quickly in the past 20 years. Since 2013, USV has advanced considerably in China, particularly in the marine survey field. Owing to its characteristics of light-weighting, intelligence, and unmanned operations, USV is attractive for shallow water, extreme environments, and marine accidents. This paper comprehensively summarizes the recent progress of the marine survey USV in China. The structure of the paper is divided into three parts. First, we briefly recall the developing history and introduce several excellent USVs of China in recent years. The marine survey USVs invested by the State Oceanic Administration (SOA) are then summarized in the next section, along with the details of hydrographic survey in the South China Sea, Antarctic marine survey, and oil spill emergency response. Finally, the paper points out current deficiencies and future directions of the potential technique. [ABSTRACT FROM AUTHOR]

Autonomous recognition of marine targets is considered a promising technology for autonomous underwater vehicle (AUV) marine survey, and AUV equipped with side-scan sonar (SSS) for recognition is the key to surveys. As a fundamental function, SSS recognition remains unsolved due to the challenging image conditions of SSS and insufficient algorithm robustness. This paper proposes an accurate and real-time dual-branch recognition framework containing segmentation and refinement branches. Firstly, the segmentation branch uses a lightweight learning network to analyze the data comprehensively. In this branch, we propose a densely connected local attention recurrent residual (LAR2) block as the backbone, and at the same time, an atrous convolution is introduced. This branch can focus on the features of interest in the image, ensuring better feature representation with low-resolution SSS information while guiding the next branch. Secondly, the refinement branch is to adjust the previous branch's results and combines the low-level and high-level features. We propose holistic attention (HA) block in this branch, which can further improve the target recognition performance. Finally, we adopt the feature fusion method of bilinear pooling to integrate the results of the two branches to output a high-precision recognition image. In offline experiments and sea trials, our proposed method outperforms other competing algorithms in the four indicators of semantic segmentation, and achieves a computation speed of 92.66 ms (± 0.86 ms) per image on AUV dedicated hardware. The method has strong robustness, meets real-time performance, and can be widely used in AUV marine survey. • A dual-branch framework is proposed for the AUV marine survey. • The framework has the characteristics of autonomy, real-time and high precision. • Experiments are carried out to prove the universality and robustness of the framework. • Potential engineering application areas of the framework are analyzed. [ABSTRACT FROM AUTHOR]

The processing of Chirp data is limited by the usual recording of the signal envelope, which enhances its immediate visibility but prevents applying methods based on wave equations. This is normally not the case for Boomer data. However, both systems are monochannel instruments, which cannot estimate properly the propagation velocity of the signal in the rocks. In this paper, we present two theorems: the first one links the Chirp or Boomer source spectrum with an expected amplitude decay curve; the second one defines conditions for the deconvolution stability of the enveloped Boomer signal when the full waveform of the source signal is known. In this way, we can jointly process and integrate heterogeneous surveys including both data types. We validated the proposed algorithms by applying them to synthetic and real data. The presented tools can improve the image resolution and the characterization of geological formations in marine surveys by reflectivity anomalies, which are distorted by standard equalization methods. [ABSTRACT FROM AUTHOR]

Wang, H.; Chen, S.H., and Luo, L., 2020. Topological characterization and optimization design for general arrangements of the research vessels. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 391-395. Coconut Creek (Florida), ISSN 0749-0208. A research vessel is a special ship designed to conduct the surveys and experiments of marine hydrology, geology, meteorology, and biology. Research vessels are equipped with many laboratories and experimental instruments required by various scientific researches, such as physics, chemistry, biology, etc. Hence, the general arrangement design of the research vessels is a complex task. Current approaches to this design problem are the repetitive process of trial-and-error and rely heavily on the design experience and inspiration of ship designers. This process is time and resource-intensive, which limits the discovery of optimal arrangements and increases the design costs and time. This paper presents a novel topology optimization design approach for the general design of research vessels. In the proposed approach, a multiscale network is utilized for characterizing the general arrangements. And, a mapping from the geometric arrangement to the topological network is defined. Besides, the meta-heuristic optimization techniques are applied in the design phases. For verifying the validity, the topology optimization design approach is demonstrated on the general arrangement design of the noted research vessel Atlantis. [ABSTRACT FROM AUTHOR]