Fundamentals of Kalman Filtering: A Practical Approach

高清PDF电子书， 关于卡尔曼滤波和小波的，经典书籍，第四版了 Kalman filtering is an optimal state estimation process applied to a dynamic system that involves random perturbations. More precisely, the Kalman filter gives a linear, unbiased, and minimum error variance recursive algorithm to optimally estimate the unknown state of a dynamic system from noisy data taken at discrete real-time. It has been widely used in many areas of industrial and government applications such as video and laser tracking systems, satellite navigation, ballistic missile trajectory estimation, radar, and fire control. With the recent development of high-speed computers, the Kalman filter has become more useful even for very complicated real-time applications. In spite of its importance, the mathematical theory of Kalman filtering and its implications are not well understood even among many applied mathematicians and engineers. In fact, most practitioners are just told what the filtering algorithms are without knowing why they work so well. One of the main objectives of this text is to disclose this mystery by presenting a fairly thorough discussion of its mathe- matical theory and applications to various elementary real-time problems

随即过程滤波的经典教材，Jazwinski的代表作，欢迎大家下载

Item based collaborative filtering recommendation algorithms 协同过滤推荐算法的基础论文

Stochastic Processes and Filtering Theory.pdf

Tracking and Kalman Filtering Made Easy

Moore的optimal filtering的中文版，翻译得很严谨，可以对照英文版一起看。

书中讲述了卡尔曼滤波的原理，并在相应章节配有matlab代码。

之前一直说要上传多维CKF滤波的例子，一直没时间，这次上传的是一个多维函数，在你的仿真中直接调用运行即可，程序都是自己一个一个敲出来的，并且经过测试的。

一个BOT的四维模型，内有容积卡尔曼滤波算法(CKF)和本人所提的嵌入式容积卡尔曼滤波(ECKF)算法的比较