雷达/红外双模制导背景下的模糊目标跟踪器

在雷达/红外双模制导背景下,对雷达/红外传感器的测量数据进行融合并提出了一种跟踪机动目标的模糊跟踪器。该跟踪器能够精确的获取目标机动的动态信息,应用一系列的模糊规则自适应的调整卡尔曼滤波器的过程噪声协方差矩阵,从而更适合用于实际的跟踪系统。通过对红外成像和雷达多传感器对目标跟踪系统的数字仿真表明所提出的模糊跟踪器性能良好。

基于GPS/BDS的通用型目标跟踪器设计

以STM32单片机为控制核心,设计了一款基于GPS(全球定位系统)/BDS(北斗卫星导航系统)和GPRS技术的通用型目标跟踪器,具备实时传输位置信息、电源监控、电话监听、报警求救等功能,与监控平台联网,可实现对车辆的运行监控、孤寡老人或孩童的防走失、宠物的找寻等。系统功耗低、响应速度快,具有很好的实用价值。

基于DSP的实时目标跟踪器

本文介绍了一套基于TMS32020数字信号处理器的实时目标跟踪器的硬件结构,对形心跟踪算法和模板匹配算法的特点和性质进行了初步的讨论,介绍了用TMS32020汇编语言实现这两种算法的一些具体问题。

基于颜色粒子滤波的多目标跟踪器设计

针对多目标跟踪中的目标遮挡和身份切换问题,在颜色粒子滤波的基础上,将单目标跟踪器扩展为多目标跟踪器。当目标轨迹彼此较接近时,利用自适应冲突预防模型分离临近轨迹。当目标发生遮挡时,跟踪器的整体模型会被分割成多个部分,使用可见部分执行跟踪和遮挡推理。当目标外观相似时,使用轨迹监测方法处理遮挡情况。当目标发生完全遮挡时,重新初始化遮挡者周围的粒子并采集目标,从而实现多目标跟踪。实验结果表明,与MIT和LSAM跟踪器相比,该跟踪器在假阴性率、假阳性率、误匹配率和多目标跟踪准确率方面均具有明显的性能优势。

一种H_∞次优滤波模糊跟踪器的设计与仿真

针对目标做高机动运动时跟踪误差增大的问题,提出了一种基于H∞次优滤波器的模糊鲁棒跟踪器。该跟踪器利用H∞次优滤波器的鲁棒性以快速减小由于目标机动产生的估计误差,实现对机动目标(尤其是高机动目标)的快速跟踪。同时,应用一系列的模糊规则在线自适应调整H∞次优滤波器的过程噪声协方差矩阵,使得该跟踪器可以精确跟踪非机动目标和机动目标。仿真结果表明,该跟踪器对机动目标和非机动目标的跟踪效果均很好,并且在目标从非机动到机动切换时,能够快速减小跟踪误差。

面向移动单摄像机的多目标跟踪算法

针对移动单摄像机采集的视频序列中的运动多目标,重点研究了基于目标间的相对运动信息和数据关联策略的在线多目标自动跟踪器。利用目标间相对运动模型实现目标轨迹的恢复,减少目标轨迹碎片。运用事件匹配算法改进当前帧的检测响应与过去轨迹的分配,并降低跟踪过程中的目标身份转换次数。实验结果表明:该改进算法较原算法能够对序列中目标跟踪定位得更加精确,减少了轨迹碎片和身份转换次数,在TUD-Campus序列上达到了与国际前沿多目标跟踪算法相当的效果。

基于有源像元传感器的多用途微型跟踪器

在恒星跟踪器和目标跟踪器等应用方面,一种新式的敏感光子的成像列阵,即有源像元传感器(APS),已成为CCD成像器的竞争对手。美国喷气推进实验室(JPL)承包了一个研制计划,即研制新一代高集成度的、基于有源像元传感器的多用途跟踪器——可编程智能微型跟踪器(PIM)。为了增强有源像元传感器所固有的优势,该实验室对用于可编程智能微型跟踪器的支持硬件进行了仔细的选择。为了执行恒星识别、恒星跟踪、姿态测定、空间对接、特征跟踪、用于着陆控制的下降成像、目标跟踪等功能,可编程智能微型跟踪器具有适当的计算能力。这种微型跟踪器的第一个模型使用的是由喷气推进实验室研制的256×256元有源像元传感器和一个先进的32bitRISC微控制器。由于有源像元传感器与微控制器的结合具有独特的优点,微型跟踪器的重量和功耗同具有目前工艺水平的恒星跟踪器相比将减小一个数量级。微型跟踪器还将增加可编程序的优点以便能够执行对各种恒星以及其它一些天体和目标的跟踪任务。可编程智能微型跟踪器已经证明其设计原理在空间应用方面的效用,现正在验证用这种集成方法来制造新一代高性能多用途跟踪仪器的功效以便用它们来执行未来的各种空间任务。

基于多功能动态像元敏感器APS的微型跟踪器

一种新型光敏图像阵列器件——动态像元敏感器APS,作为CCD成像器件的竞争对手,已经在星跟踪器和目标跟踪器应用领域崭露头角。喷气推进实验室(JPL)已经制订了一项开发基于APS器件的新一代、高集成度多功能跟踪器——可偏程智能微型跟踪器(PIM)的计划,仔细挑选了PIM的支持硬件,以充分发挥APS的固有优势。跟踪器的功能足以完成下列任务:恒星识别、恒星跟踪、姿态确定、空间对接、特征跟踪、用于着陆控制的降落成像以及目标跟踪等等。PIM的第一个方案采用JPL开发自的256×256像元APS器件和先进的32位RISC(精简指令系统计算机)微控制器。发挥APS珍奇性能及其与微控制器相结合的优势,这种微型跟踪器与当代恒星跟踪器相比,质量和功耗大约可减小一个数量级。它还增添了可编程的优点,因而可以探测各种各样的恒星和其他天体,并可执行目标跟踪任务。这种用于空间领域的PIM设计概念的有效性正在验证之中。采用这样一种集成化手段来建造新一代高性能通用跟踪设备的成效,将在未来多种多样空间任务的应用中得到证实。

位标器陀螺转子的动平衡

叙述了具有阿基米德螺旋线图案位标器的基本结构原理及其运动规律，说明了这种陀螺转子振动与“绕动”的平衡原理与方法。

Asynchronous Data Fusion of Two Different Sensors

An algorithm is presented for fusion of tracks created by radar and IR sensor which have different dimensional measurement data. It’s assumed that these sensors are asynchronous and the measurement data are transmitted to a central station at different rates. By means of the technique of time matching, two sets of asynchronous data are fused and then the filter is updated according to the fused information. The results show that the accuracy of the filter effect has been improved.

Maneuvering target tracking using threshold interacting multiple model algorithm

To avoid missing track caused by the target maneuvers in automatic target tracking system, a new maneuvering target tracking technique called threshold interacting multiple model （TIMM） is proposed. This algorithm is based on the interacting multiple model （IMM） method and applies a threshold controller to improve tracking accuracy. It is also applicable to other advanced algorithms of IMM. In this research, we also compare the position and velocity root mean square （RMS） errors of TIMM and IMM algorithms with two different examples. Simulation results show that the TIMM algorithm is superior to the traditional IMM alzorithm in estimation accuracy.

激光技术与海军

1982年的英阿马岛之战迄今已过去了12个年头,但其中有些事件却耐人寻味。特别是阿根廷有3架飞机种秘地坠毁,更使人们产生了种种疑问。直到近年,阿根廷飞机坠毁的原因才初露端倪。1989年11月,西班牙的一位新闻记者在参观英国一艘护卫舰时,发现舰桥两侧各有部分装备被遮盖。记者偷偷拍下了它的照片。原来这就是被叫作“激光致眩器”的激光武器。它通过发射激光照射人眼,可使人眼暂肘或永久性失明,从而导致飞机坠毁。

Using interacting multiple model particle filter to track airborne targets hidden in blind Doppler

In airborne tracking,the blind Doppler makes the target undetectable,resulting in tracking difficulties. In this paper,we studied most possible blind-Doppler cases and summed them up into two types:targets' intentional tangential flying to radar and unintentional flying with large tangential speed. We proposed an interacting multiple model(IMM) particle filter which combines a constant velocity model and an acceleration model to handle maneuvering motions. We compared the IMM particle filter with a previous particle filter solution. Simulation results showed that the IMM particle filter outperforms the method in previous works in terms of tracking accuracy and continuity.

Prediction-based energy-efficient target tracking protocol in wireless sensor networks

A prediction based energy-efficient target tracking protocol in wireless sensor networks(PET) was proposed for tracking a mobile target in terms of sensing and communication energy consumption.In order to maximize the lifetime of a wireless sensor network(WSN),the volume of messages and the time for neighbor discovery operations were minimized.The target was followed in a special region known as a face obtained by planarization technique in face-aware routing.An election process was conducted to choose a minimal number of appropriate sensors that are the nearest to the target and a wakeup strategy was proposed to wakeup the appropriate sensors in advance to track the target.In addition,a tracking algorithm to track a target step by step was introduced.Performance analysis and simulation results show that the proposed protocol efficiently tracks a target in WSNs and outperforms some existing protocols of target tracking with energy saving under certain ideal situations.

Dynamic cluster member selection method for multi-target tracking in wireless sensor network

Multi-target tracking(MTT) is a research hotspot of wireless sensor networks at present.A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member(CM) node selection method is put forward in the scheme.An energy efficiency model was proposed under consideration of both energy consumption and remaining energy balance in the network.A tracking accuracy model based on area-sum principle was also presented through analyzing the localization accuracy of triangulation.Then,the two models mentioned above were combined to establish dynamic cluster member selection model for MTT where a comprehensive performance index function was designed to guide the CM node selection.This selection was fulfilled using genetic algorithm.Simulation results show that this method keeps both energy efficiency and tracking quality in optimal state,and also indicate the validity of genetic algorithm in implementing CM node selection.

Maneuvering target tracking algorithm based on cubature Kalman filter with observation iterated update

Reasonable selection and optimization of a filter used in model estimation for a multiple model structure is the key to improve tracking accuracy of maneuvering target.Combining with the cubature Kalman filter with iterated observation update and the interacting multiple model method,a novel interacting multiple model algorithm based on the cubature Kalman filter with observation iterated update is proposed.Firstly,aiming to the structural features of cubature Kalman filter,the cubature Kalman filter with observation iterated update is constructed by the mechanism of iterated observation update.Secondly,the improved cubature Kalman filter is used as the model filter of interacting multiple model,and the stability and reliability of model identification and state estimation are effectively promoted by the optimization of model filtering step.In the simulations,compared with classic improved interacting multiple model algorithms,the theoretical analysis and experimental results show the feasibility and validity of the proposed algorithm.

Framed-Quadtree Path Planning for an Underwater Vehicle with the Task of Tracking a Moving Target

An autonomous underwater vehicle (AUV) must use an algorithm to plan its path to distant, mobile offshore objects. Because of the uneven distribution of obstacles in the real world, the efficiency of the algorithm decreases if the global environment is represented by regular grids with all of them at the highest resolution. The framed quadtree data structure is able to more efficiently represent the environment. When planning the path, the dynamic object is expressed instead as several static objects which are used by the path planner to update the path. By taking account of the characteristics of the framed quadtree, objects can be projected on the frame nodes to increase the precision of the path. Analysis and simulations showed the proposed planner could increase efficiency while improving the ability of the AUV to follow an object.

THE PROBABILITY HYPOTHESIS DENSITY FILTER WITH EVIDENCE FUSION

The original Probability Hypothesis Density (PHD) filter is a tractable algorithm for Multi-Target Tracking (MTT) in Random Finite Set (RFS) frameworks. In this paper,we introduce a novel Evidence PHD (E-PHD) filter which combines the Dempster-Shafer (DS) evidence theory. The proposed filter can deal with the uncertain information,thus it forms target track. We mainly discusses the E-PHD filter under the condition of linear Gaussian. Research shows that the E-PHD filter has an analytic form of Evidence Gaussian Mixture PHD (E-GMPHD). The final experiment shows that the proposed E-GMPHD filter can derive the target identity,state,and number effectively.

A novel multi-sensor multiple model particle filter with correlated noises for maneuvering target tracking

Aiming at the effective realization of particle filter for maneuvering target tracking in multi-sensor measurements,a novel multi-sensor multiple model particle filtering algorithm with correlated noises is proposed.Combined with the kinetic evolution equation of target state,a multi-sensor multiple model particle filter is firstly constructed,which is also used as the basic framework of a new algorithm.In the new algorithm,in order to weaken the adverse influence from random measurement noises in the measuring process of particle weight,a weight optimization strategy is introduced to improve the reliability and stability of particle weight.In addition,considering the correlated noise existing in the practical engineering,a decoupling method of correlated noise is given by the rearrangement and transformation of the state transition equation and measurement equation.Since the weight optimization strategy and noise decoupling method adopt respectively the center fusion structure and the off-line way,it improves the adverse effect effectively on computational complexity for increasing state dimension and sensor number.Finally,the theoretical analysis and experimental results show the feasibility and efficiency of the proposed algorithm.