Three dimensional passive underwater target motion analysis using correlated data fusion

In this paper a new method of passive underwater TMA (target motion analysis) using data fusion is presented. The findings of this research are based on an understanding that there is a powerful sonar system that consists of many types of sonar but with one own-ship, and that different target parameter measurements can be obtained simultaneously. For the analysis 3 data measurements, passive bearing, elevation and multipath time-delay, are used, which are divided into two groups: a group with estimates of two preliminary target parameter obtained by dealing with each group measurement independently, and a group where correlated estimates are sent to a fusion center where the correlation between two data groups are considered so that the passive underwater TMA is realized. Simulation results show that curves of parameter estimation errors obtained by using the data fusion have fast convergence and the estimation accuracy is noticeably improved. The TMA algorithm presented is verified and is of practical significance because it is easy to be realized in one ship.

Simulation study of passive target motion analysis

In this paper, the problem of underwater passive target motion analysis (TMA) in three dimensions is discussed using the measurements of passive bearings and elevation and frequency on the condition that acoustic source and observer are in different horizontal planes. Simulation results with both of the PLE (pseudo-linear estimation) and MLE (Maximum likelihood estimation) show that the TMA method is effective in oceanic environment. Its error covariance curves tend to its Cramer-Rao lower bounds.

Comparison of different pseudo-linear estimators for vision-based target motion estimation

Vision-based target motion estimation based Kalman filtering or least-squares estimators is an important problem in many tasks such as vision-based swarming or vision-based target pursuit.In this paper,we focus on a problem that is very specific yet we believe important.That is,from the vision measurements,we can formulate various measurements.Which and how the measurements should be used?These problems are very fundamental,but we notice that practitioners usually do not pay special attention to them and often make mistakes.Motivated by this,we formulate three pseudo-linear measurements based on the bearing and angle measurements,which are standard vision measurements that can be obtained.Different estimators based on Kalman filtering and least-squares estimation are established and compared based on numerical experiments.It is revealed that correctly analyzing the covariance noises is critical for the Kalman filtering-based estimators.When the variance of the original measurement noise is unknown,the pseudo-linear least-squares estimator that has the smallest magnitude of the transformed noise can be a good choice.

Methods for bearings-only underwater target motion analysis

The problem of estimation of underwater target motion parameters via bearings only is the most of ten encountered and most difficult to solve in the underwater target motion analysis.As the bearings-only target motion analysis is a nonlinear and multiextremal global optimization problem, so most classical estimation methods often lead the solution to convergence to one of the local extremes other than the global extreme, especially, when the noise of target bearing observation is added. In this paper we propose to use the Generalized Least Square method on the rough estimation of target motion parameters, and then use the Sequential Uniform Design method to gain a more precise estimation on the bases of rough estimation.The latter ensures that the result convergences to the global extreme. The algorithm based on the above two methods is profitable for the bearings-only target motion analysis even under conditions of large bearing observation error.

Passive bearings-only target motion analysis based on association of multiple arrays

The method for Bearings-Only Target Motion Analysis (BO-TMA) based on bearing measurements fusion of two arrays is studied. The algorithms of pseudolinear processing, extended Kalman filter and maximum likelihood estimation are presented. The results of simulation experiments show that the BO-TMA method based on association of multiple arrays not only makes contributions towards eliminating maneuvers needed by bearings-only TMA based on single array,but also improves the stabilization and global convergence for varied estimation algorithms.

A multiple template approach for robust tracking of fast motion target

Target tracking is very important in computer vision and related areas. It is usually difficult to accurately track fast motion target with appearance variations. Sometimes the tracking algorithms fail for heavy appearance variations. A multiple template method to track fast motion target with appearance changes is presented under the framework of appearance model with Kalman filter. Firstly, we construct a multiple template appearance model, which includes both the original template and templates affinely transformed from original one. Generally speaking, appearance variations of fast motion target can be covered by affine transformation. Therefore, the affine tr templates match the target of appearance variations better than conventional models. Secondly, we present an improved Kalman filter for approx- imate estimating the motion trail of the target and a modified similarity evaluation function for exact matching. The estimation approach can reduce time complexity of the algorithm and keep accuracy in the meantime. Thirdly, we propose an adaptive scheme for updating template set to alleviate the drift problem. The scheme considers the following differences： the weight differences in two successive frames; different types of affine transformation applied to templates. Finally, experiments demonstrate that the proposed algorithm is robust to appearance varia- tion of fast motion target and achieves real-time performance on middle/low-range computing platform.

Dual-quaternion-based modeling and control for motion tracking of a tumbling target

This paper investigates the problem of controlling a chasing spacecraft(chaser)to track and rendezvous with an uncontrolled target.Based on the actual situation,the torque-free motion of an axisymmetric prolate rigid body is employed to represent the short-term attitude motion of the tumbling target.By taking advantage of the dual quaternion’s compact and efficient description of the general rigid motion,the coupled and integrated model of the 6-degree-of-freedom(6-DOF)relative motion between the chaser and the tumbling target is derived in the chaser’s body fixed frame after taking full consideration of coordinate transformation.Based on the logarithm of dual quaternion,a sliding mode control(SMC)law based on the exponential reaching law and the continuous relay function is brought forward to address the problem of synchronization control of the 6-DOF relative motion.Simulation results illustrate the effectiveness of the proposed method.

Micro-motion effect in inverse synthetic aperture radar imaging of ballistic mid-course targets

For ballistic mid-course targets,in addition to constant orbital motion,the target or any structure on the target undergoes micro-motion dynamics,such as spin,precession and tumbling.The micro-motion characteristics of the ballistic mid-course targets were discussed.The target motion model and inverse synthetic aperture radar(ISAR) imaging model for this kind of targets were built.Then,the influence of micro-motion on ISAR imaging based on the established imaging model was presented.The computer simulation to get mid-course target echoes from static darkroom electromagnetic scattering data based on the established target motion model was realized.The imaging results of computer simulation show the validity of ISAR imaging analysis for micro-motion targets.

Micro-motion dynamics analysis of ballistic targets based on infrared detection

The dynamic characteristics related to micro-motions, such as mechanical vibration or rotation, play an essential role in classifying and recognizing ballistic targets in the midcourse, and recent researches explore ways of extracting the micro-motion features from radar signals of ballistic targets. In this paper, we focus on how to investigate the micro-motion dynamic characteristics of the ballistic targets from the signals based on infrared (IR) detection, which is mainly achieved by analyzing the periodic fluctuation characteristics of the target IR irradiance intensity signatures. Simulation experiments demonstrate that the periodic characteristics of IR signatures can be used to distinguish different micro motion types and estimate related parameters. Consequently, this is possible to determine the micro-motion dynamics of ballistic targets based on IR detection.

基于嵌入式技术的运动目标控制与自动追踪系统设计

针对目前移动机器人运动目标定位不准确和追踪过程中容易丢失的问题,设计了一种基于嵌入式技术的运动目标控制与自动追踪系统。本系统以光斑模拟运动目标,通过算法编程不但可以实现目标的运动轨迹控制,还可对其运动轨迹进行自动追踪。本设计以嵌入式芯片STM32F103为核心,通过OpenMV进行图像数据处理,并由PID精确算法调节舵机,从而控制光斑在屏幕上按照设定程序进行移动和追踪。经测试,该系统能够准确地完成运动目标的控制和自动追踪任务,反应灵敏,性价比高,可广泛应用于运动目标追踪等智能控制设备中。

ACCURATE DETECTION OF HIGH-SPEED MULTI-TARGET VIDEO SEQUENCES MOTION REGIONS BASED ON RECONSTRUCTED BACKGROUND DIFFERENCE

The paper first discusses shortcomings of classical adjacent-frame difference. Sec ondly, based on the image energy and high order statistic(HOS) theory, background reconstruction constraints are setup. Under the help of block-processing technology, background is reconstructed quickly. Finally, background difference is used to detect motion regions instead of adjacent frame difference. The DSP based platform tests indicate the background can be recovered losslessly in about one second, and moving regions are not influenced by moving target speeds. The algorithm has important usage both in theory and applications.

MOTION QUALITY EVALUATION OF TARGET-REACHING MOVEMENT OF INDEX FINGER

ms paper proposes a set of objective and quantitative human motion evaluation indices, among Which the index of difficulty and index of performance are introduced as the general indices for the quality measure of 2-D target-to-talget movement. As an example, the target-reaching movement of index finger, which is a basic functional action of index finger in the daily life of hUman beings, were experimentally investigated. In the experiment five healthy male subjects were asked to perform three target-reaching movement tasks Which have different indices of difficulty. All movements were recorded by a 3-D motion analysis system. Later, their motion qualities were measured with these evaluation metrics. The results showed that these indices are reasonable and have potential applications to biomedical engineering.

基于视频的振动测量技术研究进展

振动测量是保障结构安全和良好状态的基本手段。高精度的振动测量可为结构设计、安装调试、健康管理等振动试验提供精确的输入与响应测试。相较于传统的振动测量手段,基于视频的振动测量技术将相机的全部像素转化为高精度振动传感器,利用视频图像方式让人们肉眼可视结构在物理世界的真实振动形态,具有非接触、全视场、高空间分辨率、灵活方便等优点,近年来受到业界的广泛关注。该文主要介绍了视频振动测量技术的系统构成与测量过程、当前主要方法和相关技术最新进展,并总结了视频振动测量技术与其他技术相比存在的优势。通过分析与对比,肯定了视频方法是解决振动测量问题的有效手段和对传统测量方法的有力补充,随着相关技术和硬件设备的发展,视频振动测量方法将具有越来越大的研究意义和应用价值。

模拟复眼视叶神经网的目标运动方向检测模型

如何对杂乱背景中物体(目标)的运动方向做出准确可靠的检测与感知,是计算机视觉研究领域中一个重要问题。自然界中,飞虫(如苍蝇、蜻蜓等)高适应性和高可靠性的感知目标运动是一种自然特性,本文基于飞虫−果蝇视叶神经纤维网最新的生理学研究成果,提出一种基于果蝇视觉感知目标运动方向的多层级检测模型系统。通过对不同场景下拍摄的视频序列样本进行实验和测试,并与2-Q运动检测器模型、基于ON和OFF信号通道处理运动信息的检测模型等进行了对比,验证了其在杂乱背景下对于目标水平和垂直方向运动检测的有效性和鲁棒性。

非合作线谱声源分布式定位方法

非合作目标定位是水声定位领域的研究热点。为充分挖掘并利用各类可观测参数,提高非合作目标定位能力,提出一种基于目标频率变化信息的非合作目标定位方法。该方法针对匀速直线运动目标的定位问题,首先根据多普勒频移原理,建立观测频率与目标辐射频率、目标运动速度、位置之间的函数映射关系,利用最小均方准则建立目标函数,通过优化算法估计分布式定位系统中各个测量单元与目标运动轨迹的致近点距离,最后综合各观测节点的测距结果,构建几何定位模型,求得目标运动轨迹的解析解。通过仿真分析,证明了该方法的有效性,并指出了该方法需要目标通过与各测量单元的致近点才能获得较好的距离估计能力。文中分析了不同频率估计精度对定位精度的影响,结果表明,提出的定位方法对测频精度具有一定的容限,是一种高精度的非合作线谱声源定位方法。

单站水下方位频率机动目标运动分析方法

水下方位频率机动目标运动分析常需已知中心频率先验信息且存在机动检测错误等,因此提出了一种基于方位与多线谱信息融合的自适应无迹卡尔曼滤波算法。该算法将方位与多线谱频率信息融合处理,重新构建了方位−多线谱目标运动分析模型。将中心频率信息引入状态向量中构建实时迭代估计,同时引入了自适应时变渐消因子,实时调整过程噪声协方差矩阵使其适应机动目标。仿真与海试数据处理结果表明,所提方法的机动目标运动分析性能最优,其目标运动分析结果能以最快的速度逼近克拉美罗下界。

直升机运动状态下雷达回波建模与微动特性分析

针对直升机常规雷达回波建模未考虑直升机运动时自身姿态变化对回波影响导致仿真结果与实际不符的问题,基于自由空间下旋翼叶片散射点回波模型,引入了多个参数矩阵和向量,实现直升机运动状态下雷达回波统一模型的构建.然后从理论上分析了在不同运动状态下,直升机回波微动特性变化.仿真结果验证了理论分析的正确性,表明运动状态变化对直升机雷达回波会产生影响.本文的研究对直升机目标识别及意图识别领域发展具有一定的价值.

无人潜航器解算目标运动要素的一种方法

随着计算机技术、人工智能、能源技术的发展,无人潜航器也被应用于军事领域。在分析了无人潜航器水下侦察搜索、反水雷战、水下诱骗战应用的基础上,提出潜艇采用线导方式控制双无人潜航器进行目标运动要素解算的方法,并分别通过图解法和计算法分析了其解算的原理。该方式只需探测目标的方位信息,降低了目标其他要素探测的难度,不仅增加了潜艇的探测距离还利于潜艇隐蔽,这对水下无人潜航器应用具有一定的参考意义。

运动目标的多维度微运动特征提取研究

微多普勒特征提取作为一种常用的时频分析工具,对微动目标特征的提取重构具有重要意义.为了更好地研究多运动的微多普勒效应,提出了一种运动姿态分类方法.按照目标频移是否随时间变化可以将运动姿态分为频移时变运动和频移时不变运动.频移时变运动包括平移、翻滚和振动.针对这种运动应分析对比不同时间对应的瞬态频移,频移时不变运动主要为旋转运动.本文通过微多普勒效应理论结合电磁波频域模型,实现3D运动目标微动特性提取的仿真建立目标,分析不同环境条件例如晴天阴天、有无湍流对探测的影响,为后续实验研究奠定理论基础.开展基于收发同置系统的多特征运动目标的微多普勒频移探测实验,实验结果表明,不同目标位置上频移的幅度、正负性和谱线宽度旨在反演目标形状、运动姿态、运动方向和速度.利用FFTshift函数对一维数据进行解调分析,实现三维时间-频率-强度关系的研究.本研究实现了对目标宏观形状特性的测量以及微观运动信息的提取,为雷达探测和识别奠定基础.

天基逆合成孔径雷达脉内脉间运动补偿及高分辨成像

近年来,太空态势感知在军用和民用领域都得到了越来越多的关注。天基逆合成孔径雷达(SBISAR)能够实现对空间目标的高分辨成像,支撑部件提取、姿态估计、类型识别等后续任务,是太空态势感知的重要工具。然而,在SBISAR成像场景下,平台与空间机动目标间存在复杂的相对高速运动,传统距离-多普勒成像方法不再适用,必须进行运动补偿。本文针对高速径向速度下传统“停—走—停”模型失效、长相干积累时间内目标转速不一致的两个典型误差来源,分别设计了脉内运动及脉间运动补偿算法。首先,建立SBISAR成像的信号模型。然后,基于最小熵准则构建参数估计代价函数,通过估计目标对应回波信号的调频率,构造补偿项进而实现脉内补偿。同时,建立图像熵代价函数,在估计转动参数后,完成对目标转动的空变相位补偿。所提算法有效解决了天基高速机动背景下传统距离-多普勒成像方法的距离像展宽、方位散焦问题,实现了SBISAR对空间目标的高分辨成像。通过基于仿真数据的实验分析,验证了所提算法的有效性。