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机动目标的跟踪问题一直是人们研究的重点，实现机动目标精确跟踪，首要解决的问题就是使所建立的目标运动模型与实际的目标运动模型匹配。目前常用的有多模型(MM)，交互式多模型(IMM)，切换模型等。多模型方法就是对一组具有不同机动模型分别进行Kalman滤波，最终的参数估计是各滤波器估计值的加权和；在多模型基础上，Shalo ...

在matlab环境下，实现kalman滤波器跟踪目标。

一片介绍双估计的很好的文章。同时估计动态系统的状态和模型参数，使用扩展kalman filter和ukf方法，很有参考价值

惯性导航和GPS的数据融合，基于模糊自适应kalman滤波的方法

Carrier-phase synchronization can be approached in a general manner by estimating the multiplicative distortion (MD) to which a baseband received signal in an RF or coherent optical transmission system is subjected. This paper presents a unified modeling and estimation of the MD in finite-alphabet d ...

Rao-Blackwellised Particle Filters (RBPFs) are a class of Particle Filters (PFs) that exploit conditional dependencies between parts of the state to estimate. By doing so, RBPFs can improve the estimation quality while also reducing the overall computational load in comparison to original PFs. Howev ...

The need for accurate monitoring and analysis of sequential data arises in many scientic, industrial and nancial problems. Although the Kalman lter is effective in the linear-Gaussian case, new methods of dealing with sequential data are required with non-standard models. Recently, there has been re ...

％ PURPOSE : Demonstrate the differences between the following filters on the same problem: ％ ％ 1) Extended Kalman Filter (EKF) ％ 2) Unscented Kalman Filter (UKF) ％ 3) Particle Filter (PF) ％ 4) PF with EKF proposal (PFEKF) ％ 5) PF with UKF proposal (PFUKF)

包括，kalman一步预测代码，kalman滤波器，以及kalman平滑等几个源代码。希望大家有用。

提供了子波域矩阵加权，标量加权，修正加权的方法对比，包括小波分解，kalman滤波，信息融合等内容，该程序论文已被IEEE期刊收录