基于CT非线性模型的水下目标跟踪算法比较

针对水下目标跟踪非线性跟踪精度问题,假设目标机动模型为恒转速运动模型,贝叶斯框架下,因扩展卡尔曼滤波跟踪方法进行模型在估计点的泰勒展开,忽略一阶以上高阶项,存在模型误差,比较了扩展卡尔曼滤波、无迹卡尔曼滤波、容积卡尔曼滤波在高斯噪声干扰下滤波误差均方根,以及3种方法运行时间。仿真证明,非线性系统下状态维度为5,容积卡尔曼滤波跟踪的精度高于无迹卡尔曼滤波,无迹卡尔曼滤波高于扩展卡尔曼滤波。该研究为海上目标非线性测量系统提供仿真实例,为进一步滤波算法改进提供基础。     

HY1621多波束测深仪的性能分析

基于HY1621多波束测深仪的多次研制试验,利用不同水域的测试数据,重点分析了HY1621多波束测深仪的测深稳定性、边缘波束稳定性以及测量精度。通过对比分析HY1621和T50-P多波束对新安江水库区域的水下地形扫测成果,以及对HY1621多波束在长江三峡库区的水下地形扫测成果所做的分析,验证了HY1621是一款达到预期性能设计指标的多波束测深仪。     

多传感器组合导航系统研究

为了满足水下航行器高精度导航定位的需求,建立了多传感器组合导航的系统模型。针对信息融合过程中出现的非线性环节,在传统联邦滤波器的基础上,提出了基于粒子滤波的混合联邦滤波器。其中,线性子系统采用卡尔曼滤波算法进行滤波估计,非线性子系统采用粒子滤波算法进行滤波估计。计算机仿真分析表明,该混合联邦滤波算法能够将线性和非线性子系统的滤波结果很好地融合起来,提高了组合导航系统的定位精度。     

AUV搭载多波束声纳进行地形测量的现状及展望

多波束声纳是一种常用的水底地形测量设备,AUV搭载多波束声纳对深海地形进行测量得到了普遍应用。首先介绍了目前国内外AUV搭载多波束声纳在地形测量中的应用情况,然后总结了这种方式的高效率、高质量、高经济性等优点,并分析了导航定位精度、载体运动、系统兼容性等方面对于提高测量精度存在的技术难点,最后介绍了该技术的应用经验,并对该技术的未来应用前景进行了展望。     

顾及地形变化的多测线粗差剔除方法在一体化水深测量中的应用

单波束测深仪是现代海洋和内河水下地形测量中使用最为频繁的测量仪器。硬件设备固有特性和水下复杂的特殊环境,易导致单波束测深仪在实际使用中产生各类型的粗差。单波束采集时按照每条测线进行处理,在数据处理上往往存在不同船只、不同测线难以一体化处理的问题。文中针对水深值粗差的特点,设计了单波束数据采集和处理一体化方法,在区域处理单波束数据的基础上,提出一种顾及地形的单波束水深测量数据多测线粗差检测方法,并针对上海周边实测区域对单波束测深数据采集和处理进行全方位的验证,结果表明应用本方法不但提升了数据精度和数据处理可靠性,而且大幅提高了作业效率。     

基于阈值自适应确定的多波束点云滤波算法

针对水下多波束地形测量点云去噪问题,提出了一种基于阈值自适应确定的点云滤波算法。首先引入虚拟网格对多波束点云进行分区编号,并采用二次分层统计法剔除显著离群噪点;其次归一化计算网格内种子点与邻域各点的坡度角,引入k-Medoids聚类算法自适应更新坡度阈值;最后按照多尺度滤波窗口逐级对点云进行迭代运算,得到精细化地形点云。2个实验区的多波束点云滤波实验结果表明,本文算法能较好去除多波束点云的噪声和非地形点,有效提高坡度阈值的自适应性,滤波精度有明显提升,可以适用于大规模的多波束点自动化云滤波工作。     

基于无人机摄影测量的潮间带单波束测深空间插值精度评估

针对单波束测深数据插值模型精度验证困难等问题,利用潮间带潮汐规律,提出了一种基于高精度无人机数据验证插值模型精度的方法。在低潮时利用无人机摄影测量构建高精度潮间带数字表面模型,高潮时获取单波束测深数据并结合全球导航卫星系统技术计算得出潮间带地形点的三维坐标,使用克里金插值法、反距离权重法、规则样条函数法以及自然邻域法分别构建潮间带数字高程模型。以无人机数字表面模型数据为基准,分别对4种插值方法构建的潮间带数字高程模型进行精度分析。结果表明：1)后处理差分技术辅助无人机摄影测量可以构建高精度潮间带数字表面模型。2)在潮间带区域可以使用无人机数据作为单波束测深数据精度的评价标准。3)潮间带地形较为平坦时,规则样条函数法相比于其他3种插值方法精度更高,粗差率为12.5%。     

误差量测与杂波环境对水下目标跟踪的影响分析

在水下特殊的环境中,大误差量测与强杂波环境会对目标跟踪有显著的影响。量测误差越大,则预测门限区域越大,杂波密度越高,那么轨迹更易于与杂波关联,进而降低正确量测的权重,滤波精度因此下降。文中依据量测误差模型与杂波模型,建立了误差量测与杂波对水下目标跟踪的影响模型。依据该模型可定量分析量测误差与杂波对目标跟踪的影响,可为目标跟踪滤波器提高抗杂波能力或者提高滤波精度提供理论依据。     

导航型GPS在海上地球物理勘探中的应用──卫导数据随机噪声处理

分析了导航型GPS在海上地球物理勘探应用中存在的问题，着重研究了卡尔曼滤波对号航数据中航向和航速的处理；提出两种滤波模型，对模拟的导航数据和真实航行数据进行计算，并将结果用于重力测量数据的Eotvos改正，对出现的问题进行了讨论。文章提出适当的处理方法，使导航型GPS适应海上地球物理勘探的要求，提高了导航精度和满足测量了精度。     

多波束声纳计量测试系统设计

为满足多波束声纳量值溯源与传递需求,设计多波束声纳关键参数的计量测试系统。基于大比尺原型深水港池和多维运行控制机构,通过水下横向测距代替垂向测深的方式对多波束声纳进行了测深准确度与有效条带宽度的计量测试。阐述了测试系统的主要组成和测试方法,给出了本测试系统测深结果的扩展不确定度。参考标准值与示值(或标称值)比对结果表明,被检多波束声纳测深示值误差小于0.2%,条带宽度误差小于7%。为规范水下声纳设备技术指标校准,指导多波束声纳计量标准建设提供参考。     

Application of particle filter combined with extended Kalman filter in model identification of an autonomous underwater vehicle based on experimental data

This study proposes a method for identification of the nonlinear dynamic model of an AUV while some states are unmeasured; hence, it concentrates on a nonlinear “state and parameter estimation” issue. In this method, a local linearization is used for solving the nonlinear dynamics based on the extended Kalman filter (EKF), and a particle filter (PF) is used to minimize errors and variances of the nonlinear system. In other words, the PF is combined with the EKF in the form of the extended Kalman particle filter (EKPF). The EKPF method is independent of the initial values and satisfies the limits of the parameters and also the assumption that the hydrodynamic coefficients are constant. Hence, it is shown when the ranges or signs of some parameters are known, the EKPF is a more accurate estimator than the EKF. Moreover, a new simulation is done using the model estimated by the EKPF and the results are compared and validated with the measured data of a new experimental test. It is shown that the obtained model can predict the trajectory path with the total normalized root-mean-square error (NRMSE) of 14% and the surge mean speed with the NRMSE of 5%; and it describes the 6DOF motion of the AUV more accurate than the EKF model.     

几种非线性滤波算法的性能比较与分析

在非线性状态估计中,传统的扩展卡尔曼滤波通过线性化来实现高斯近似,由于截断误差的存在很难保证估计精度;而基本粒子滤波容易出现粒子退化,导致滤波发散。针对粒子滤波的两个基本假设：蒙特卡罗假设和重要采样假设,采用蒙特卡罗随机链的方法来提高粒子的多样性,并利用无味卡尔曼滤波来产生更高精度的替代分布,发展了无味粒子滤波。通过仿真实验证明,相比较扩展卡尔曼滤波和基本粒子滤波,改进后的无味粒子滤波算法性能更优越,对含有非线性非高斯的状态估计问题有更好的滤波效果。     

基于声呐图像的深海采矿车组合定位导航算法

实现高精度的定位导航是深海采矿车完成海底工作任务的基础条件。在采矿车行进过程中,声呐设备生成的图像信息能够反映海底场景的变化,从而体现采矿车本身的运动,由此建立了一种声呐图像里程计,并将其与轮式里程计和USBL测量数据相结合提出了一种深海采矿车组合定位导航算法。首先对多波束前视声呐图像进行预处理,然后使用Canny算法进行特征检测并对特征点云进行配准,再结合声呐成像原理构建了声呐图像里程计运动模型,最后通过轮式里程计运动模型推导预测方程、声呐图像里程计运动模型和USBL测量数据推导更新方程,利用EKF（extended Kalman filter）算法实现基于多传感器融合的定位与姿态估计。海试数据验证了该组合定位算法能实现轮式里程计、声呐里程计和超短基线在速度、位置、艏向角估计、定位速率的精度互补,具有一定的有效性和精确性,该算法为深海采矿车的定位与导航算法研发提供了参考。     

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.     

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.     

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.     

面向地形匹配的多波束测深数据抽稀方法研究

基于多波束测深的地形定位是水下潜器导航技术研究和发展的重点,多波束测深数据的高精度快速重采样是水下地形匹配定位的前提。传统的实时抽稀方法因对多波束测深数据模型的过分简化而效果欠佳。参考Douglas-Peucker算法和点云数据抽稀方法,采用角度-弦高联合准则对多波束每ping数据进行抽稀处理,参考导航地形图对抽稀后的多ping数据基于点云离散度进行二次抽稀处理,从而实现多波束测深数据的高精度快速抽稀处理。典型的数学仿真地形和实测多波束条带数据实验表明:文中提出的抽稀方法数据抽稀率仿真地形在85%以上,实测地形在90%以上,数据抽稀前后点云构成的曲面DEM误差在3%以内,并且算法实时性较好。     

顾及声线弯曲的横摇偏差迭代算法

横摇偏差校准是多波束水深测量测前准备的一项重要内容。针对传统多波束横摇偏差校准操作复杂且存在主观因素问题,同时考虑到横摇偏差引起海底地形失真的非线性变化,提出了顾及声线弯曲的横摇偏差自动迭代算法。该算法以平坦海底为假设,基于常梯度声线跟踪模型和最小二乘原理,对多Ping数据进行迭代拟合,最后取其平均值作为横摇偏差。仿真分析结果表明,迭代算法能逐步调整横摇偏差引起的海底地形非线性失真,提高横摇偏差计算值的准确性。     

重力辅助惯性导航的匹配算法初探

对重力辅助惯性导航技术的基本原理进行了分析,将采样卡尔曼滤波算法用于重力图形匹配。滤波通过设计少量的Σ点,并计算这些Σ点的经由非线性函数的传播,从而获得滤波值基于非线性状态方程的更新,较广义卡尔曼滤波具有计算精度高、便于计算的特点。