To realize space-sea integrated communication between multiple ships under the BeiDou-3 satellite communication topology, this paper proposes a new satellite-ship autonomous communication system based on a deep learning anomaly detection algorithm. A deep learning algorithm combining coarse-grained detection (piecewise oversampling principal component analysis, POsPCA) and fine-grained sorting (VAE and differential ARIMA joint model) was established to realize two-way autonomous communication between BeiDou-3 satellites and ships. Specifically, a segmented oversampling principal component analysis algorithm was proposed to analyze anomalous BeiDou-3 short message data segments in the coarse-grained detection stage. In the fine-grained sorting stage, a joint fusion reconstruction and prediction model was proposed to calculate the fine-grained anomaly score. The autonomous communication system establishes the communication priority of multiple ships based on this score. Using the experimental platform independently built for this study to verify the algorithm performance, the proposed algorithm effectively realizes the priority ranking of anomaly scores by detecting abnormal data segments, effectively saving 64.4% of BeiDou-3 satellite short message communication resources. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

The transmission standard and format of short-message communication in the BeiDou satellite-navigation-system are open, the civilian channel adopts a direct-transmission plaintext mechanism, and the content of short messages is at risk of data leaks. Aiming at addressing the problem of safely transmitting BeiDou short messages, this study proposes a CGAN BeiDou satellite short-message-encryption scheme, using ship PVT (position, speed, and time). Various BeiDou commands with ship position, speed, or time are employed as the input. The two communicating parties use the CGAN (conditional generative adversarial network) confrontation mechanism to encrypt and decrypt the ship-PVT information and generate a symmetrically encrypted key, while the receiver parses only the sender data within the specified PVT-range. Additionally, because the BeiDou system has a positioning error and transmission delay, and considering the ship mobility, the concept of a dynamic tolerance region is introduced at the receiver, to improve the scheme’s decryption success-rate. Finally, the proposed scheme is verified, using simulation and experiments. The proposed algorithm achieves good security, with acceptable efficiency. Furthermore, the experimental platform built by this study is used to prove the feasibility of the scheme applied to BeiDou short-message encryption and decryption. © 2022 by the authors.

舰船电力系统环形网络故障重构本质上是带约束的多目标非线性组合优化问题。为了解决舰船电力系统发生故障时的供电恢复问题,提出了一种改进双粒子群优化算法进行求解。此算法分为主、辅两个粒子群,主粒子群改进了种群初始化、自适应调整惯性权重和学习因子,提高了主粒子群算法的全局寻优能力。同时,辅助粒子群还采用改进的混沌局部搜索策略,增强了种群多样性及局部寻优能力,有效地解决了粒子群算法中容易陷入局部极值的问题。通过系统仿真,分别将几种不同的优化算法进行比较。结果表明该算法具有很高的搜索效率和寻优能力,能有效地提高故障恢复的速度与精度,在处理舰船电力系统网络故障重构方面具有较好的效果。

将基于最小二乘的灰色关联分析应用于火箭弹的毁伤效能评估,利用已知信息推测出火箭弹毁伤效能与各因素之间的潜在联系,解决了火箭弹毁伤效能的多参数优化问题。可采用较少的实验次数搜寻优化参数得到最佳毁伤效能,通过参数的最大与最小灰色关联度之差找到对多性能特性影响较显著的因子。实验结果表明,本方法有效改进了火箭弹的毁伤效能评估,通过改进影响显著的因子,重度毁伤率（含歼灭）可提升30%。

Obtaining voyage data through a vessel monitoring system (VMS) and transmitting it to a remote monitoring center through satellites is an important link to realize the information perception of smart ships. However, improving data quality to ensure the integrity of information is still an open question. Taking into account the complex and harsh marine environment, a BeiDou satellite transmission link will inevitably suffer the challenge of packet loss. Therefore, this paper proposes a novel BeiDou satellite transmission framework with missing package imputation to improve the information perception ability of smart ships. In particular, we propose a two-stage missing packet imputation strategy (T-MPI). First, a bidirectional recurrent neural network (Bi-RNN) based on temporal view imputation is designed to learn the time correlation of the data. Second, considering the attributive view imputation of multivariate data, an autoencoder with a linear aggregation module (LA-AE) is proposed to capture sudden changes in the ship's complex sailing state. An experimental platform was established to verify the developed framework, and real freighter transportation data were used to prove the effectiveness of our proposed imputation strategy under complex sailing conditions.

A satellite information transmission network is different from a ground network. The link distance between the satellite and the ground is large, and the communication between them is affected by the ionosphere. The ground congestion control algorithm cannot provide fast and stable responses to short-term burst flows. Therefore, aiming at the problem of large propagation delays and the complex environments of satellite-to-ground links, this paper investigates the Vegas congestion mechanism of the Space Communication Protocol Standard Transport Protocol (SCPS-TP), incorporates the interference affecting satellite communication links into a discrete model, combines interference estimation with controller design, proposes a reaching law and sliding mode-based predictive control algorithm for satellite communication, and suggests the stability of the introduced algorithm. The simulation results demonstrate the anti-jamming ability of the proposed algorithm for addressing short-term burst flows, and the prediction mechanism of the algorithm improves the utilization of satellite network bandwidth.

高速翼航状态下的全浸式水翼艇能够依靠水翼上产生的升力将船体完全托出水面,克服了兴波阻力和摩擦阻力对船体的影响,大大减轻了船体所受的海浪冲击,具有优良的适航性。然而,在翼航状态下,全浸式水翼艇缺少必要的静稳定性,这就对全浸式水翼艇动力学姿态镇定与航迹引导控制系统的稳定性与鲁棒性提出了更高的要求。本文提出全浸式水翼艇横向运动姿态鲁棒控制技术,通过研究翼航状态下的全浸式水翼艇横向运动非线性动力学,探究水翼艇横向运动姿态稳定鲁棒控制策略,以保证全浸式水翼艇高速运动时横向运动姿态的全局稳定性。本论文主要开展了以下几个方面的研究工作:首先,对论文相关内容的研究进展、所存在的问题及论文的整体思路进行阐述。针对全浸式水翼艇的横向运动姿态控制,分析了全浸式水翼艇的水翼布置方案,并针对全浸式水翼艇的运动特性给出了其运动控制系统的体系结构与设备构成;基于该总体设计方案,针对航向镇定与航迹控制问题,提出了全浸式水翼艇艏摇/横摇联合控制方案与航迹跟随控制方案的系统体系结构;分析了全浸式水翼艇横向平面操纵运动模型,对水翼系统和支柱系统的受力情况进行了水动力学分析,并针对规则波与随机海浪作用下全浸式水翼艇横向运动姿态的受扰运动进行了分析。其次,针对翼航状态下的全浸式水翼艇艏摇/横摇鲁棒联合控制问题,进行了基于迭代学习策略的全浸式水翼艇艏摇/横摇输出反馈滑模鲁棒控制研究。将迭代学习策略融入到状态观测器与滑模控制器的设计中。设计了迭代学习观测器实现了对全浸式水翼艇艏摇/横摇动力学模型中系统状态与集总干扰的一体化估计;利用迭代学习观测器重构出的系统状态观测值设计了一种迭代学习滑模控制律,提高了全浸式水翼艇艏摇/横摇姿态控制的干扰抑制性能,降低了系统控制设计的保守性。接着,为了在艏摇/横摇联合控制策略的设计中体现全浸式水翼艇艏摇动力学与横摇动力学状态轨线的时间尺度特征及艏摇/横摇动力学的耦合摄动特性对控制器设计的影响,进行了全浸式水翼艇艏摇/横摇双时标输出反馈奇异扰动控制策略研究。将测量系统的随机噪声特性纳入状态观测器的设计与分析中,基于无源性理论进行状态观测器设计,利用包含测量噪声的系统输出对系统状态进行重构,从而获得艏摇/横摇动力学系统控制所需的全部状态变量。进而基于奇异扰动理论,挖掘艏摇动力学系统与横摇动力学系统的不同时间尺度特征,设计了艏摇/横摇双时标控制策略以实现全浸式水翼艇艏摇与横摇的姿态镇定。然后,在翼航状态全浸式水翼艇艏摇/横摇联合鲁棒控制研究的基础上,进行了全浸式水翼艇直线航迹跟随级联干扰抑制控制策略的研究,针对全浸式水翼艇的运动学系统的航迹引导任务与动力学系统的姿态跟踪任务进行级联控制律设计。基于对传统视线法引导律和全浸式水翼艇的运动学特性两方面的深入探究,提出了特别用于全浸式水翼艇的具有横倾约束的双通道航迹引导策略。进而针对航迹引导系统获得的期望艏向角与期望横倾角,设计了基于扩张状态观测器的指令滤波反步控制策略,实现了对期望艏向角与期望横倾角的跟踪。通过仿真验证,证实了所设计的双通道引导算法的有效性与横向姿态控制系统对系统集总干扰的鲁棒性。最后,为进一步提高全浸式水翼艇翼航状态下的机动性,进行了基于自适应横漂补偿的全浸式水翼艇曲线航迹跟随鲁棒积分控制研究。通过对路径规划法则进行评估,设计了基于三次样条插值法的曲线航线生成策略。基于浸入—不变集理论提出了一种自适应鲁棒双通道引导算法,实现了对期望艏向角中未知侧滑角的估计与补偿。针对全浸式水翼艇翼航状态的航向/横倾姿态跟踪控制问题研究了非线性鲁棒积分控制策略,利用连续的控制器输出完成了水翼艇横向姿态受扰状态下的渐进跟踪,并保证了由运动学子系统与动力学子系统组成的级联系统在集总干扰作用下的全局一致渐近稳定。系统仿真证实了所提出的航线生成方法的实用性,验证了全浸式水翼艇的高机动性与所提出的级联式航迹引导与姿态控制策略的鲁棒性。

BeiDou-3 satellites have short-message communication capabilities, which are not available in other navigation systems. However, the information transmission capacities of BeiDou-3 satellites are limited, which means that the string length of a single transmission is restricted. To improve transmission performance, this paper proposes a lossy data compression algorithm to transmit ship data. First, due to the large amount of measurement noise in the ship data and the difficulty of adaptively adjusting the compression threshold of the swinging door trend, a dynamic threshold adjustment strategy based on model-free adaptive control is designed. Furthermore, because the performance of the strategy depends on the initial value, chaos multilayer particle swarm optimization is employed to optimize the strategy and achieve better generalization and convergence performance. In addition, this paper introduces an experimental system and uses real ship motor vibration and electromagnetic radiation data to verify the compression algorithm. The experimental results indicate that the proposed algorithm displays reasonable performance. Presently, the system designed in this paper has been operating stably for more than six months.