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1.
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。 相似文献
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在高斯白噪声背景下,匹配滤波器作为线性调频信号的最优检测器,在水声信号处理中被广泛应用。 当发射信号为线性调频信号时,由水下目标径向速度引起的多普勒频移会造成回波和样本之间失配, 使匹配滤波器的检测性能下降,增加了目标速度估计的难度。 利用分数阶傅里叶变换对于线性调频信号的聚焦特性,提出了应用分数阶傅里叶变换的水下运动目标线性调频回波检测算法,完成对目标速度的估计, 推导目标运动速度与分数阶傅里叶变换阶数之间的关系,并对测量结果进行误差分析。 仿真测试表明,该算法可有效地估计混响背景下的目标径向速度,且具有良好的估计性能。 相似文献
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This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation, underwater acoustic images segmentation and underwater objects tracking. This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor. First, the real-time data flow (underwater acoustic images) is pre-processed to form the whole underwater acoustic image, and the relevant position information of objects is extracted and determined. An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method. Second, a representation of region information is created in light of the Gaussian particle filter. The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness. Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed. They show that the proposed method can detect and track the moving objects underwater online, and it is effective and robust. 相似文献
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Underwater target tracking relies on a model relating the target states to time-delay and bearing measurements. This furnishes linearized measurement models. Problems arise due to fitting models using the least-squares procedure, whose success may depend on the assumption that the data noise distribution is Gaussian. For many cases of non-Gaussian errors, performance of the least-squares estimators is far from optimal. Robust regression procedures have been proposed to improve the performance of the least-squares procedures for non-Gaussian errors, and to enhance their performance for the Gaussian errors. Filters for time-delay estimation based on the Fair and Andrews's weighting functions of the iteratively reweighted least-squares method are proposed. Computational results are given to illustrate and compare the performances of the two filters as well as that due to ordinary least-squares filters 相似文献
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This paper proposes an improved version of Unscented Kalman Filter (UKF), namely Robust Adaptive UKF (RAUKF), with a special focus on Bearings-Only Target Tracking for three-dimensional case (3DBOT). The automatic tuning of the noise covariance matrices and the robust estimation of the target states form a critical point for the performance of the Kalman-type filtering algorithms, especially in the variable environmental conditions exposed in underwater. The key idea of the proposed filter is to combine robust aspects of UKF and adaption of the process and measurement noise covariance matrices with low computational complexity. The main contribution of this paper is to adjust these matrices by means of the steepest descent algorithm, and the H∞ technique is embedded to achieve superior performance in terms of accuracy and robustness against initial conditions and model uncertainties. Different experiments are performed to evaluate the performance of the proposed algorithm in the 3DBOT problem with a single moving observer. Simulations demonstrate that the proposed filter produce more accurate results with satisfactory computational burden in comparison with other methods. 相似文献
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为解决多传感器水下目标纯方位跟踪中的传感器测量衰减问题,建立水下目标静态多传感器纯方位跟踪模型,将传感器测量衰减建模为统计特性已知的随机变量,基于融合中心接收到的各水声传感器的原始测量值,设计了一种集中式状态估计器结构,利用最小方差方法推导出最优的集中式目标状态估计增益。通过算例仿真可以得出,所提出的算法能够在水声传感器不做机动的前提下跟踪目标,弥补了单个水声传感器观测性不足的缺点,对比传统的集中式Kalman估计器,具有更高的精度,能够有效解决传感器测量衰减问题。 相似文献
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对于有ARMA噪声的线性回归模型,本文给出了只用递推进行模型辨识和参数估计的线性方法。若用所计算得到的回归残差作为数据,采用Hannan-Rissanen的线性估计法求ARMA噪声的参数估计,则本文证明了估计是强相容的,且对正态序列,估计具有渐近正态优效性。 相似文献
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Foresti G.L. Murino V. Regazzoni C.S. Trucco A. 《Oceanic Engineering, IEEE Journal of》1997,22(1):57-65
This paper describes a voting-based approach for the fast automatic recognition of man-made objects and related attitude estimation in underwater acoustic images generated by forward-looking sonars or acoustic cameras. In general, the continuous analysis of sequences of images is a very heavy task for human operators and this is due to the poor quality of acoustic images. Hence, algorithms able to recognize an object on the basis of a priori knowledge of the model and to estimate its attitude with reference to a global coordinate system are very useful to facilitate underwater operations like object manipulation or vehicle navigation. The proposed method is capable of recognizing objects and estimating their two-dimensional attitude by using information coming from boundary segments and their angular relations. It is based on a simple voting approach directly applied to the edge discontinuities of underwater acoustic images, whose quality is usually affected by some undesired effects such as object blurring, speckle noise, and geometrical distortions degrading the edge detection. The voting approach is robust, with respect to these effects, so that good results are obtained even with images of very poor quality. The sequences of simulated and real acoustic images are presented in order to test the validity of the proposed method in terms of average estimation error and computational load 相似文献
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This paper presents a method for tracking a distant moving target using only bearing measurements obtained from a tracking platform. The method is an improvement of the Hinich-Bloom passive tracking approach presented in [1]. The target is assumed to be moving at constant speed on a fixed heading, whereas the platform maneuvers during the measurement period. The direction cosines of the bearings are computed with respect to a rotation of the coordinate system that places 0° at the mean estimated target bearing. This is done to minimize the approximation bias due to the linearization of sine bearing as a function of inverse range and time. The coordinate system is rotated back to estimate the target coordinates. When the noise is Gaussian, the estimates of target range and heading are approximately maximum likelihood when the target's relative range is slowly varying during the observation period. In this case the mean square errors of the target parameter estimates are the smallest achievable within the order of the approximation. 相似文献
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随着对水下目标特性研究的深入和声学探测技术的发展,基于单模态的阵列式信息融合或基于空间信息的分布式信息融合的水下目标识别方法研究已有一定成果,但针对复杂海况导致单一物理场或单一融合层次的系统识别性能提高有限等方面影响的水下目标识别方法研究还有所不足,因此,开展基于多模态深度融合模型的水下目标识别方法研究可利用模态互补,共享信息而提升识别率。文中在国内外研究基础上,深入研究了基于到达时差法和多模态方法组合的检测方法,初步形成了基于水声环境空间中多模态深度融合模型的识别框架,开展了海洋中典型自然与人为事件的信号分析与特征提取,并在此基础上,设计新型基于海底基站的被动识别系统。该系统同步记录和由位置等组成的时间序列标记声、磁和压数据,可实现高精度、高分辨率的识别。本研究可满足未来海洋观测对高性能水下目标探测、定位和跟踪系统的迫切需要,为海洋安全监管、海洋突发事件应急响应等领域提供新的技术手段和科学参考。 相似文献
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针对固定粒子数PF-TBD算法计算量大、复杂环境下地波雷达海上船只目标检测与跟踪性能不佳的问题,本文将粒子滤波方法应用于地波雷达船只目标检测与跟踪中,提出了基于自适应粒子滤波的地波雷达目标检测与跟踪联合处理方法。该方法结合地波雷达回波谱中目标展宽特性,充分利用了地波雷达回波谱中面目标的粒子权重信息来设置粒子自适应采样策略,提高了目标检测和跟踪联合处理的效果。通过地波雷达实测数据的目标跟踪结果及与同步AIS信息的比对分析,结果表明:提出的检测跟踪联合处理方法在对低信噪比、快速机动等复杂环境下的多目标跟踪时,可提高目标整体跟踪性能。 相似文献
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Unmanned Underwater Vehicles (UUVs) are increasingly being used in advanced applications that require them to operate in tandem with human divers and around underwater infrastructure and other vehicles. These applications require precise control of the UUVs which is challenging due to the non-linear and time varying nature of the hydrodynamic forces, presence of external disturbances, uncertainties and unexpected changes that can occur within the UUV’s operating environment. Adaptive control has been identified as a promising solution to achieve desired control within such dynamic environments. Nevertheless, adaptive control in its basic form, such as Model Reference Adaptive Control (MRAC) has a trade-off between the adaptation rate and transient performance. Even though, higher adaptation rates produce better performance they can lead to instabilities and actuator fatigue due to high frequency oscillations in the control signal. Command Governor Adaptive Control (CGAC) is a possible solution to achieve better transient performance at low adaptation rates. In this study CGAC has been experimentally validated for depth control of a UUV, which is a unique challenge due to the unavailability of full state measurement and a greater thrust requirement. These in turn leads to additional noise from state estimation, time-delays from input noise filters, higher energy expenditure and susceptibility to saturation. Experimental results show that CGAC is more robust against noise and time-delays and has lower energy expenditure and thruster saturation. In addition, CGAC offers better tracking, disturbance rejection and tolerance to partial thruster failure compared to the MRAC. 相似文献
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GyungNam Jo Hang S. Choi 《Oceanic Engineering, IEEE Journal of》2006,31(3):565-573
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 相似文献
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The generalized Kalman filtering (GKF) method is applied to underwater target tracking. The proposed GKF is based on the formulation developed by J.C. Lagarias and F. Aminzadeh (1983) establishing a tradeoff between the cost associated with estimation error and the cost related to the lateral discontinuity of the estimates. By assigning proper weights for accuracy and stability in the objective function, the desired balance between accuracy of estimates and lateral continuity is achieved. Computational results illustrate the performance of the technique. Conclusions as to the effects of the accuracy and stability weights are drawn 相似文献
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水下声学定位观测数据中不可避免地存在粗差,随机模型解算广泛地采用等权模型,模型实现简单,但与实际不符,且不能抑制粗差影响。针对该问题,提出一种基于IGG3方案的抗差Helmert方差分量估计方法。该方法通过水深和观测距离将观测值分为两类,利用Helmert方差分量估计确定不同类观测值的权比,抗差解决了粗差导致Helmert方差分量估计模型失效的问题。实验结果表明,相比于传统解算方法,抗差Helmert方差分量估计方法可以合理确定各观测值权比,削弱粗差影响,提高水下定位精度和可靠性。 相似文献
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针对热红外遥感图像由于低对比度、条带噪声、低空间分辨率等特点而导致的检测效果不佳问题,提出了一种近岸舰船目标尺度自适应选择分层多阈值检测方法。采用舰船模板图像尺度归一化高斯拉普拉斯函数取极大值准则进行尺度自适应选择,利用所选的高斯多尺度空间差分多阈值筛选进行近岸舰船检测,并根据不同类型舰船模板图像尺度和分块数选择对热红外图像舰船目标检测的影响进行验证实验。实验结果表明:所提方法能根据模板尺度特征滤除相似区域,通过设置合理尺度和阈值参数能实现有效检测,且具有一定的抗噪能力。 相似文献
20.
Jenhwa Guo Sheng-Wen Cheng Cheng-Yang Ying Te-Chih Liu 《Oceanic Engineering, IEEE Journal of》2003,28(1):55-61
Describes an image registration method for underwater inspection tasks. A remotely operated vehicle equipped with a video camera and a scanning sonar is used as the testbed vehicle. Each image of the underwater scene is saved along with the video camera's position and orientation. The images are then combined to create a large composite picture of the underwater structure being inspected. This method is based upon a maximum a posteriori estimation technique and provides smooth and robust estimates of image shifts. Our results demonstrate the feasibility of this highly promising underwater inspection procedure. 相似文献