毕业论文

打赏
当前位置: 毕业论文 > 自动化 >

基于IMM的机动目标跟踪算法研究

时间:2017-05-25 22:08来源:毕业论文
对不同的模型集,进行了蒙特卡洛(Monte Carlo)仿真分析,并分析了其优缺点及适用范围。结果表明IMM算法具有良好的滤波效果,且由于模型集具有多重选择性,IMM算法的适用范围较广

摘要目标跟踪通过对来自目标的测量值进行处理,以保持对目标现实状态的估计,目标跟踪的核心是滤波算法。本课题在了解国内外目标跟踪现状的基础上,重点对基于交互式多模型(IMM)的机动目标跟踪算法进行了研究。本文首先概述了目标跟踪原理,介绍了适合描述不同机动目标情况的运动模型。然后,阐述了机动检测与机动辨识的含义。对于处理非线性问题的滤波方法,本文详细介绍了IMM滤波技术,对不同的模型集,进行了蒙特卡洛(Monte Carlo)仿真分析,并分析了其优缺点及适用范围。结果表明IMM算法具有良好的滤波效果,且由于模型集具有多重选择性,IMM算法的适用范围较广。最后,本文对IMM算法的不足之处提出改进。关键词  目标跟踪;滤波算法;IMM算法;模型集;Monte Carlo仿真9228
毕业设计说明书(论文)外文摘要
Title  Maneuvering  Target  Tracking  Based  on    Interacting  Multiple  Model  Algorithm       
Abstract
Target tracking is a technology of estimating the target's real state by processing the measured values from the object, the core of target tracking is the filtering algorithm. This article focuses on the study of maneuvering target tracking algorithm based on interacting multiple model algorithm on the basis of learning the target tracking situation at home and abroad. Firstly, the principle of target tracking is outlined, and some different motion models which is appropriating to represent the motion of maneuvering target are introduced. Then, the meaning of detection and identification of maneuvering is retrospect. For the filtering method of dealing with nonlinear issue, the Interacting Multiple Model filtering algorithm is presented in detail, afterwards, we summarize some advantages and disadvantages of these algorithms with different model sets by compare the Monte Carlo simulation results, meanwhile, the limits of application are also acquired. The simulation result shows that IMM algorithm has a good filtering performance and a broader scope of application as a result of its multiple selective in model sets. Finally, some improvements directing at the inadequacies of the IMM algorithm are put forwarded.
Keywords  Target tracking; filtering algorithm; IMM algorithm;
 Monte Carlo simulation   
目次

1    引言    1
1.1    课题研究背景    1
1.2    目标跟踪算法的发展及研究现状    2
1.3    本文主要内容及结构安排    3
1.3.1    主要研究内容    3
1.3.2    论文结构安排    4
2    机动目标运动模型    4
2.1    匀速(CV)模型    4
2.2    匀加速(CA)模型    5
2.3    辛格(Singer)模型    6
2.4    “当前”统计(CS)模型    8
2.5    交互式多模型    10
2.5.1    复合系统    10
2.5.2    交互式多模型原理    11
3    目标跟踪滤波    11
3.1    目标跟踪基本原理    11
3.2    几种常用滤波算法    12
3.2.1    线性滤波算法    12
3.2.2    非线性滤波算法    15
3.2.3    自适应滤波算法    15
3.3    机动检测与机动辨识    16 基于IMM的机动目标跟踪算法研究:http://www.youerw.com/zidonghua/lunwen_7868.html
------分隔线----------------------------
推荐内容