基于可重置联邦滤波器的水下运载体导航定位方法

单一导航系统无法满足水下运载体高精度、高可靠性的导航需求,文中根据常用水下导航系统的特点,提出基于可重置联邦滤波器的水下运载体导航定位方案,设计了以惯导系统(INS)为主参考系统,声学定位系统/深度计、多普勒计程仪(DVL)、罗经为子参考系统的联邦滤波器,并进行了仿真研究。结果表明文中设计的滤波器能有效融合各个传感器的导航信息,实现水下运载体高精度导航定位,并具有一定容错性。     

Geometrical aspects of a sonar-based navigation system for underwater vehicles

A novel self-contained navigation system has been devised for underwater vehicles operating in and around offshore installations. This system matches data from a sector-scanning sonar device to a computer model of the installation. The paper begins by highlighting the existing approaches to subsea navigation before outlining the main features of the proposed system. It then concentrates on a key component of this system which is a method for calculating the position and heading of an underwater vehicle navigating in the vincinity of tubular steel structures. An iterative solution method is presented which incorporates six degree of freedom vehicle motions and this is verified in a series of laboratory experiments with various arrangements of structural members and using a commercial sonar device. The key features, applications and performance of this method are discussed. The main conclusion is that the proposed method for calculating the position and heading of an underwater vehicle contributes towards achieving an accurate and reliable subsea navigation capability.     

重力辅助匹配惯性导航系统研究

常规的航位推算方法无法满足水下潜器长时间工作的导航要求,惯导设备的定位误差随时间积累,重力异常数据和重力梯度数据进行匹配辅助导航可以连续的对惯性导航系统积累误差进行校正。 文章介绍了利用重力辅助惯导的思想和原理,对重力辅助惯性导航进行了讨论,建立包含重力异常/ 重力梯度数据的 Kalman 滤波算法,并采用改进的 ICCP 算法对重力异常匹配导航进行了模拟试算,结果表明在现有的技术条件下,重力辅助匹配导航能够胜任水下航行的工作任务,保证长航时的水下定位精度。     

基于倒置声学基阵的INSUSBL组合导航算法研究

文中关注水下潜航器导航定位时,电磁波传播途径中能量衰减、惯导系统长航时积累误差以及提高水下潜航器定位精度等问题。基于倒置的超短基线声学基阵,分析声波往返传播时间(RTT)、平面波近似方法和USBL导航解算方法及其坐标转换过程,结合INS误差方程,建立INS/USBL松组合模型。为进一步提高系统精度、动态性能和抗干扰性,考察USBL的原始斜距、斜距差以及声学基阵的空间分布信息,提出基于USBL原始输出信息的INS/USBL紧耦合组合导航方法。通过MATLAB仿真对导航算法进行验证,结果表明两种算法能充分抑制纯惯导误差随时间积累问题,且有效地估计出姿态、速度和位置误差角;其中紧耦合方法状态估计误差最小,导航参数精度相对松组合提高30%以上,对于提高水下载体导航定位精度、海洋探测具有重大意义。     

Simulation of an Inertial Acoustic Navigation System With Range Aiding for an Autonomous Underwater Vehicle

This paper presents an integrated navigation system for underwater vehicles to improve the performance of a conventional inertial acoustic navigation system by introducing range measurement. The integrated navigation system is based on a strapdown inertial navigation system (SDINS) accompanying range sensor, Doppler velocity log (DVL), magnetic compass, and depth sensor. Two measurement models of the range sensor are derived and augmented to the inertial acoustic navigation system, respectively. A multirate extended Kalman filter (EKF) is adopted to propagate the error covariance with the inertial sensors, where the filter updates the measurement errors and the error covariance and corrects the system states when the external measurements are available. This paper demonstrates the improvement on the robustness and convergence of the integrated navigation system with range aiding (RA). This paper used experimental data obtained from a rotating arm test with a fish model to simulate the navigational performance. Strong points of the navigation system are the elimination of initial position errors and the robustness on the dropout of acoustic signals. The convergence speed and conditions of the initial error removal are examined with Monte Carlo simulation. In addition, numerical simulations are conducted with the six-degrees-of-freedom (6-DOF) equations of motion of an autonomous underwater vehicle (AUV) in a boustrophedon survey mode to illustrate the effectiveness of the integrated navigation system.     

基于单水声信标距离量测的匹配定位方法

水声通信和测距能力是实现水下航行器准确定位的重要技术手段。当前基于水声定位的方法主要有利用测距和测向功能的水声定位技术以及水声测距辅助导航技术，二者的系统物理复杂度都比较高。本文提出了一种基于单水声信标距离量测的匹配定位方法，航行器在水声信标测距覆盖范围内，利用航行过程中多次测距信息构建测距圆序列形成位置约束，基于航位推算导航信息，将航行器在连续测距时间段内的相对航迹在圆序列上进行最优匹配，从而获得位置估计，通过对测距误差进行补偿可进一步提升定位精度。本方法所需物理系统结构复杂度低、可操作性强，仿真实验表明，该方法可以独立实现较高精度的定位。     

Mine avoidance techniques for underwater vehicles

It is shown that by implementing certain mine avoidance techniques, an underwater vehicle equipped with an obstacle avoidance sonar (OAS) and a navigation system can safely navigate an unknown minefield. The mine avoidance techniques take into account the physical limitations of the sonar and the navigation system, the maneuverability constraints on the underwater vehicle, and the required safe standoff distance from all mines. Extensive computer simulations have verified the mine avoidance capability in more than 50 different minefields. In all 50 simulations the vehicle reached a predetermined end point and maintained at least the specified, minimum safe standoff distance from each mine. The simulation accurately models the major difficulties associated with the sonar, the navigation system, and the vehicle dynamics. The sonar model includes surface, bottom, and volume reverberation; thermal, ambient, and flow noises; actual receiver and projector beam patterns; and false alarms and missed detections. The navigation system model contains the effects of biases, random noises, and scale factor errors. The vehicle dynamic model simulates angular velocities and accelerations associated with underwater vehicles     

Intelligent behaviour-based team UUVs cooperation and navigation in a water flow environment

This paper considers the problem of intelligent behaviour-based team unmanned underwater vehicles (UUVs) cooperation and navigation, especially in a water flow environment. Animals often have behaviour which aims to maintain them living as groups. We learn from animals’ typical group behaviour and develop behaviour-based rules for team cooperation of UUVs. We create simulation scenarios in which a team of vehicles cooperate to track a target in a water current environment. This paper customises several behaviour-based rules to satisfy the requirement of the desired scenarios. We use fuzzy logic controllers to set different priority weights for each rule on-line according to the situation that the vehicles meet. The decision of the vehicle's next step steering direction is made by the combination of these rules multiplied by the relative priority weights. The line-of-sight guidance law is modified as the navigation rule in a water flow environment. The dynamic manoeuvring model of a real small UUV, SUBZERO III, is used in the simulation. The simulation results indicate that the entire system is successful in reaching the target without any collision within the scenario. The different trajectories and travel times are compared and discussed when normal and modified line-of-sight guidance rules are applied.     

Underwater Terrain Positioning Method Based on Least Squares Estimation for AUV

To achieve accurate positioning of autonomous underwater vehicles, an appropriate underwater terrain database storage format for underwater terrain-matching positioning is established using multi-beam data as underwater terrainmatching data. An underwater terrain interpolation error compensation method based on fractional Brownian motion is proposed for defects of normal terrain interpolation, and an underwater terrain-matching positioning method based on least squares estimation(LSE) is proposed for correlation analysis of topographic features. The Fisher method is introduced as a secondary criterion for pseudo localization appearing in a topographic features flat area, effectively reducing the impact of pseudo positioning points on matching accuracy and improving the positioning accuracy of terrain flat areas. Simulation experiments based on electronic chart and multi-beam sea trial data show that drift errors of an inertial navigation system can be corrected effectively using the proposed method. The positioning accuracy and practicality are high, satisfying the requirement of underwater accurate positioning.     

用于水下潜器的惯性导航系统安装和初始对准技术

水下潜器通常采用捷联惯性导航和多普勒计程仪组合导航系统。为提高惯性导航系统的导航精度,保障水下潜器顺利作业,文章以高性能惯导系统PHINS为例,介绍其安装和初始对准技术。PHINS在安装时须计算其与船体的偏差以及与船体和外部传感器的力臂,尤其与多普勒计程仪组合时应执行传感器自动对准程序;PHINS的初始对准是其精确导航的前提,可在海上或静态时进行;惯导系统的安装误差和初始对准精度对于其导航精度具有决定性的影响。     

Mosaic-based navigation for autonomous underwater vehicles

We propose an approach for vision-based navigation of underwater robots that relies on the use of video mosaics of the sea bottom as environmental representations for navigation. We present a methodology for building high-quality video mosaics of the sea bottom in a fully automatic manner, which ensures global spatial coherency. During navigation, a set of efficient visual routines are used for the fast and accurate localization of the underwater vehicle with respect to the mosaic. These visual routines were developed taking into account the operating requirements of real-time position sensing, error bounding, and computational load. A visual servoing controller, based on the vehicle's kinematics, is used to drive the vehicle along a computed trajectory, specified in the mosaic, while maintaining constant altitude. The trajectory toward a goal point is generated online to avoid undefined areas in the mosaic. We have conducted a large set of sea trials, under realistic operating conditions. This paper demonstrates that without resorting to additional sensors, visual information can be used to create environment representations of the sea bottom (mosaics) and support long runs of navigation in a robust manner.     

Underwater Terrain Positioning Method Based on Least Squares Estimation for AUV

To achieve accurate positioning of autonomous underwater vehicles, an appropriate underwater terrain database storage format for underwater terrain-matching positioning is established using multi-beam data as underwater terrain-matching data. An underwater terrain interpolation error compensation method based on fractional Brownian motion is proposed for defects of normal terrain interpolation, and an underwater terrain-matching positioning method based on least squares estimation (LSE) is proposed for correlation analysis of topographic features. The Fisher method is introduced as a secondary criterion for pseudo localization appearing in a topographic features flat area, effectively reducing the impact of pseudo positioning points on matching accuracy and improving the positioning accuracy of terrain flat areas. Simulation experiments based on electronic chart and multi-beam sea trial data show that drift errors of an inertial navigation system can be corrected effectively using the proposed method. The positioning accuracy and practicality are high, satisfying the requirement of underwater accurate positioning.     

Large Area 3-D Reconstructions From Underwater Optical Surveys

Robotic underwater vehicles are regularly performing vast optical surveys of the ocean floor. Scientists value these surveys since optical images offer high levels of detail and are easily interpreted by humans. Unfortunately, the coverage of a single image is limited by absorption and backscatter while what is generally desired is an overall view of the survey area. Recent works on underwater mosaics assume planar scenes and are applicable only to situations without much relief. We present a complete and validated system for processing optical images acquired from an underwater robotic vehicle to form a 3-D reconstruction of the ocean floor. Our approach is designed for the most general conditions of wide-baseline imagery (low overlap and presence of significant 3-D structure) and scales to hundreds or thousands of images. We only assume a calibrated camera system and a vehicle with uncertain and possibly drifting pose information (e.g., a compass, depth sensor, and a Doppler velocity log). Our approach is based on a combination of techniques from computer vision, photogrammetry, and robotics. We use a local to global approach to structure from motion, aided by the navigation sensors on the vehicle to generate 3-D submaps. These submaps are then placed in a common reference frame that is refined by matching overlapping submaps. The final stage of processing is a bundle adjustment that provides the 3-D structure, camera poses, and uncertainty estimates in a consistent reference frame. We present results with ground truth for structure as well as results from an oceanographic survey over a coral reef.      

A wideband, high-resolution, low-probability-of-detection FFTbeamformer

Navigation of an underwater minefield by a remotely operated vehicle (ROV) or an autonomous undersea vehicle (AUV) requires the detection, localization, and avoidance of obstacles. The sizes of obstacles to be avoided range from the diameter of cables up to the size of other vehicles. A classical solution to this problem is the use of an obstacle avoidance sonar, but due to the high degree of sophistication of modern-day mines and unfriendly vehicles, it is desirable to avoid signal energies that might be detectable. The use of spread-spectrum signal structures is one possible way to avoid this difficulty while retaining the capability of despreading the energy at the receiver. This paper presents the development of a beamforming system that uses a frequency-decomposition FFT beamformer and a spread-spectrum signal structure for low-probability-of-detection navigation     

In Situ Alignment Calibration of Attitude and Doppler Sensors for Precision Underwater Vehicle Navigation: Theory and Experiment

This paper reports the development and experimental evaluation of two in situ least squares techniques for estimating the alignment matrix of Doppler sonars commonly used for precision navigation of oceanographic submersibles. Most previously reported methods addressed the problem of single degree-of-freedom heading alignment using bottom-lock Doppler sonar data and global positioning system (GPS) navigation data. This paper reports and evaluates two techniques for three degree-of-freedom calibration of attitude and Doppler sonar sensors using sensor data available to vehicles at full ocean depth. The first technique provides a general linear least squares estimate of the alignment matrix. The second technique results in a least squares alignment matrix estimate constrained to the group of rotation matrices. The performance of these estimates is evaluated with a laboratory remotely operated vehicle (ROV) and a field-deployed autonomous underwater vehicle (AUV). Experimental results are reported which demonstrate that Doppler navigation employing the reported alignment calibration techniques significantly improves navigation precision. The experiments show that the latter technique provides calibration estimates that improve Doppler navigation precision not only on the calibration data set itself, but also provide improved precision over a wide variety of vehicle trajectories other than the calibration data set.     

Autonomous underwater vehicles - challenging developments and technological maturity towards strategic swarm robotics systems

ABSTRACT

Reliable power supply, precise position determination and effective communication are the key requirements for strategic autonomous underwater vehicles (AUV) involved in long duration scientific missions, search operations and when operated as a swarm. The paper presents the challenging range of AUV developed for deep water, Polar and intervention applications; demanding technical requirements for strategic AUV; reliability modeling done on the lithium-ion batteries to identify the redundancy requirements for achieving near-zero failures; navigation model to estimate the achievable level of position accuracies using the state-of-the-art navigation system; limitations in underwater communication; and their importance in realizing vehicle autonomy and swarm intelligence. It is identified that a strategic grade Doppler velocity- aided inertial navigation system could provide position accuracies of about 0.5% of the distance travelled when navigated using sea bottom or ice reference, and a 38?kWh lithium-ion battery pack requires about 7% redundant battery capacity to achieve a failure probability of <?1% in a period of 1 year.     

Underwater acoustic noise measurement in test tanks

The range capability of underwater acoustic equipment installed onboard underwater vehicles is limited by the noise generated by propellers, hydraulic pumps.... Measuring this noise at sea is quite expensive. Here is described a procedure allowing the measurement of the radiated noise in test tanks. This method is derived from techniques previously developed in aerial acoustics and in electromagnetism     

基于ICCP匹配算法的海底地形匹配辅助导航

利用海底地形辅助导航是水下载体导航技术致力研究的新方向，采用ICCP算法作为对准匹配算法，利用实测地形数据和已知地形数据库，进行仿真计算，修正惯性导航系统累计误差，得到水下载体的最佳匹配位置，以提高水下载体的导航精度。     

A study of increasing the precision of navigation position for submerged body

Currently, most submerged bodies use the long-baseline acoustic position system (LBL) to identify the navigation position for submerging. A precise navigation position is always the target pursued by underwater technology. The conventional long-baseline acoustic position systems normally use Kalman filter correction to handle the problem of positional errors. This article proposes a new modification, which is based on the periodically measured actual navigation distance, and associated with the three-dimensional geometrical relations between the transponder on the seabed and the navigation distance. This new modification employs the iterative approximation to modify the errors of the measured navigation position from the conventional long-baseline acoustic position system. In order to verify the availability of the modified model by the essay, the study uses the navigation position for an underwater surveying submerged body as the study object. After the numerical simulation analysis, the result shows that the modification was presented by the article can only use very few iterations to precisely modify the errors of the measured navigation position from the conventional long-baseline acoustic position system, which is highly applicable for positioning in long-term and long-distance submersion. Moreover, the modification method proposed by the paper can also help submersion positioning for the underwater vehicle, as well as the military submerged body.     

Velocity-Aided Underwater Navigation System Using Receding Horizon Kalman Filter

This paper discusses the problems related to constructing a receding horizon filter for underwater inertial navigation systems which are subject to external disturbances. Noises are assumed to be bounded, additive, and contained in both state and measurement equations. An estimator is designed according to the sliding-window strategy to minimize the receding horizon estimation cost function. The derived filter is applied to a velocity-aided inertial navigation system. Simulations show that the derived filter is more accurate than the standard Kalman filter (KF) for underwater navigation systems subject to temporary unknown disturbances