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.

Selection and modification of ground motion records using Newmark-Hall spectrum as target spectrum for long-period structures

Input ground motions have significant impacts on the uncertainty of structural responses in time-history analysis.In this study,records were selected and scaled for the evaluation of mean structural responses according to the target spectrum.The Newmark-Hall spectrum is closely related to seismic response of short,medium and long-period structures,so it was taken as the target spectrum here.The nonlinear time-history analyses of 9-story and 20-story steel moment-resisting frame structures were carried out as examples.They represent medium and long-period buildings,respectively.Three target spectra with risk of 50%,10%and 2%probabilities for exceedance in 50 years were calculated by the average Newmark-Hall spectrum method for three ground motion sets developed in the SAC Steel Project.The predicted structural mean responses of these Newmark-Hall spectra were compared with those calculated by the average spectral acceleration method for the same record set.It is found that both methods have similar accuracy for estimating the structural mean response.However,the method proposed herein is more effective in reducing the variability of the structural responses.Also,the proposed method is more advantageous for the time-history analysis of long-period structures or structures with more severe nonlinear responses under strong seismic excitations.

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.

Constrained auxiliary particle filtering for bearings-only maneuvering target tracking

To track the nonlinear,non-Gaussian bearings-only maneuvering target accurately online,the constrained auxiliary particle filtering(CAPF)algorithm is presented.To restrict the samples into the feasible area,the soft measurement constraints are implemented into the update routine via the1 regularization.Meanwhile,to enhance the sampling diversity and efficiency,the target kinetic features and the latest observations are involved into the evolution.To take advantage of the past and the current measurement information simultaneously,the sub-optimal importance distribution is constructed as a Gaussian mixture consisting of the original and modified priors with the fuzzy weighted factors.As a result,the corresponding weights are more evenly distributed,and the posterior distribution of interest is approximated well with a heavier tailor.Simulation results demonstrate the validity and superiority of the CAPF algorithm in terms of efficiency and robustness.

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.

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.

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.

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.

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.

Adaptive Extended Kalman Filtering for Bearings-Only Targets Tracking Problem

An adaptive extended Kalman filtering (AEKF) is proposed for nonlinear control systems. For bearingsonly targets tracking problem, we present an adaptive extended Kalman filter which suits a nonlinear observation model and a linear dynamical model. Simulation results have shown that the adaptive extended Kalman filter for the passivetracking problem performs better than the original extended Kalman filter (EKF).

Ant colony optimization for bearings-only maneuvering target tracking in sensors network

In this paper, the problem of bearings-only maneuvering target tracking in sensors network is investigated. Two objectives are proposed and optimized by the ant colony optimization （ACO）, then two kinds of node searching strategies of the ACO algorithm are presented. On the basis of the nodes determined by the ACO algorithm, the interacting multiple models extended Kalman filter （IMMEKF） for the multi-sensor bearings-only maneuvering target tracking is introduced. Simulation results indicate that the proposed ACO algorithm performs better than the Closest Nodes method. Furthermore, the Strategy 2 of the two given strategies is preferred in terms of the requirement of real time.

Posterior Cramer-Rao lower bounds for multitarget bearings-only tracking

Usually, only the Cramer-Rao lower bound （CRLB） of single target is taken into consideration in the state estimate of passive tracking systems. As for the case of multitarget, there are few works done due to its complexity. The recursion formula of the posterior Cramer-Rao lower bound （PCRLB） in multitarget bearings-only tracking with the three kinds of data association is presented. Meanwhile, computer simulation is carried out for data association. The final result shows that the accuracy probability of data association has an important impact on the PCRLB.

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。

用于多目标跟踪的高斯混合轨迹预测模型

针对视频中目标之间的遮挡会增加轨迹关联难度的问题,提出了一种高斯混合轨迹预测模型来改善遮挡情况下的关联效果.该模型采用Transformer结构,从对象的历史运动信息中提取更长的时间依赖性,以便更准确地预测跟踪对象在未来的轨迹分布;同时,将模型的输出设置为高斯混合分布,采用多个高斯分布相加来定义跟踪对象在未来的轨迹分布,以利用轨迹分布来计算检测目标和跟踪对象之间的空间相似性.实验结果表明:该模型能够改善跟踪性能,在MOT17数据集上HOTA达到了56.3%.

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。

基于三维激光点云的序列运动图像点目标快速跟踪方法

由于现有方法未充分考虑小目标和遮挡目标检测的问题,导致目标跟踪效果不佳,由此针对点目标跟踪较为困难的问题,提出基于三维激光点云的序列运动图像点目标快速跟踪方法。首先下采样序列运动图像三维激光点云并去除其中的地面数据,通过动态阈值改进欧式聚类方法,分割图像为目标和背景,然后改进SECOND算法,在目标检测阶段融入自适应空间特征融合模块和二维卷积神经网络,同时采用3D DIoU替代Smooth L1作为损失函数,提升SECOND算法的目标检测性能,最后在激光雷达坐标系中构建各点目标的三维中心,利用3D卡尔曼滤波器连续跟踪目标,以交并比和欧式距离为度量标准,通过贪婪算法匹配最近邻目标,实现序列运动图像点目标快速跟踪。实验结果表明,所提方法IoU值更高,可达到0.971,且对目标的跟踪更理想。

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。

基于特征识别的群体运动轨迹分析算法

针对群体运动轨迹分析算法存在的执行时间长、预测准确率低等问题,基于高斯混合模型、均值漂移算法和LSTM模型提出一种具有较高预测准确率的群体运动轨迹分析算法。通过回顾和分析主流的群体目标跟踪算法,设计和构建基于粒子滤波的均值漂移算法,并在此基础上引入具有时空预测功能的LSTM模型和高斯混合模型,从而实现视频环境下群体目标运动轨迹的抗扰识别、跟踪和预测。仿真实验采用相同的篮球运动视频数据集作为样本,其统计结果表明,与传统的群体识别和跟踪算法相比,基于特征识别的群体运动轨迹分析算法具有更高的预测准确率和更少的平均执行时间,群体运动轨迹的预测准确率提升了14.9个百分点,算法的平均执行时间降低了21.6个百分点。

一种联合TDCM和PFA的空间目标大转角ISAR成像方法

空间目标态势感知是当前航天技术领域的研究热点,逆合成孔径雷达(Inverse Synthetic Aperture Radar, ISAR)是空间目标感知的一种有效手段。为了得到利于目标鉴别的高分辨二维ISAR图像,需要通过增大积累转角来提高方位向分辨率。但是,随着转角的增大,平动与转动之间的耦合增大,使得传统的先平动补偿、后利用转动成像的两步式成像方法不再适用。本文提出了一种结合时域信号共轭相乘(Time Domain Conjugate Multiplication, TDCM)处理与极坐标格式算法(Polar Format Algorithm, PFA)的成像算法,首先利用雷达回波的二维相干性,通过TDCM处理进行平动粗补偿,然后借助PFA的插值操作校正大转角引起的散射点越分辨单元走动(Motion Through Resolution Cell, MTRC)并估计目标相对转动参数。通过迭代处理,持续对平动和转动参数进行优化,提升运动补偿效果。仿真验证了所提成像算法的有效性,与传统算法相比,成像聚焦性更好。