## 自适应跟踪算法设计+文献综述

Abstract
With the development of communications and positioning technologies in modern society, target tracking has been applied in both military and people's livelihood. The usually used filters for maneuvering target tracking have   filter, Kalman filter and particle filter etc. They are applied to communication, radar, navigation, automation and so on.
When the target’s motion state changed, the tracking performance of a single model will be decreased. In this thesis a adaptive filter is designed which can realize both high accuracy, real-time tracking and automatic model transformation.

Firstly， the principle of target tracking was summarized, including how to choose target model and coordinate system. Details of Kalman filter are discussed. Secondly, the maneuver detection and adaptive filtering algorithm are researched. Then, the Kalman filtering programs with Matlab are developed to simulate constant-velocity model and constant-acceleration model. Finally, to the transformation issues between above two models, model switching algorithm is put forward. The simulation results showed that the proposed algorithm with model switching has high precision and outstanding performance compared with conventional filters.
Keywords  Target tracking; Kalman filtering; Adaptive filtering; Model transformation

1  绪论    1
1．1  研究背景    1
1．2  国内外发展现状    1
1．3  本文主要研究及结构    2
2  目标跟踪滤波原理与方法    3
2．1  跟踪坐标系选择    3
2．2  目标模型    4
2．3  基本的跟踪滤波与预测方法    9
3  卡尔曼滤波    13
3．1  卡尔曼滤波的发展    13
3．2  卡尔曼滤波基本算法    15
3．3  卡尔曼滤波的性质    17
4  机动目标跟踪中的自适应滤波    18
4．1  自适应滤波算法    18
4．2  CV模型自适应滤波    20
4．3  CA模型自适应滤波    22
5  算法设计与仿真    24
5．1  CV模型代码及仿真    24
5．2  CA模型代码及仿真    28 源自/六^维:论"文;网(加7位QQ3249~114 www.lwfree.cn
5．3  自适应模型切换设计    30

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