基于卡爾曼濾波的道路目標檢測與跟蹤研究，采用交互多模(IMM)算法
上傳時間： 2014-01-04
上傳用戶：731140412
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 digital communication systems. A simple form of MD is the camer phase exp GO) which has to be estimated and compensated for in a coherent receiver. A more general case with fading must, however, allow for amplitude as well as phase variations of the MD. We assume a state-variable model for the MD and generally obtain a nonlinear estimation problem with additional randomly-varying system parameters such as received signal power, frequency offset, and Doppler spread. An extended Kalman filter is then applied as a near-optimal solution to the adaptive MD and channel parameter estimation problem. Examples are given to show the use and some advantages of this scheme.
標簽： synchronization Carrier-phase multiplicativ approached
上傳時間： 2013-11-28
上傳用戶：windwolf2000
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. However, the computational complexity is still too high for many real-time applications. In this paper, we propose a modified RBPF that requires a single Kalman Filter (KF) iteration per input sample. Comparative experiments show that while good convergence can still be obtained, computational efficiency is always drastically increased, making this algorithm an option to consider for real-time implementations.
標簽： Particle Filters Rao-Blackwellised exploit
上傳時間： 2016-01-02
上傳用戶：refent
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 renewed interest in simulation-based techniques. The basic idea behind these techniques is that the current state of knowledge is encapsulated in a representative sample from the appropriate posterior distribution. As time goes on, the sample evolves and adapts recursively in accordance with newly acquired data. We give a critical review of recent developments, by reference to oil well monitoring, ion channel monitoring and tracking problems, and propose some alternative algorithms that avoid the weaknesses of the current methods.
標簽： monitoring sequential industria accurate
上傳時間： 2013-12-17
上傳用戶：familiarsmile
％ 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)
標簽： the Demonstrate differences following
上傳時間： 2016-01-07
上傳用戶：yiwen213
包括，kalman一步預測代碼，kalman濾波器，以及kalman平滑等幾個源代碼。希望大家有用。
標簽：
上傳時間： 2013-11-26
上傳用戶：
提供了子波域矩陣加權，標量加權，修正加權的方法對比，包括小波分解，kalman濾波，信息融合等內容，該程序論文已被IEEE期刊收錄
上傳時間： 2013-12-21
上傳用戶：ZJX5201314
The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application. For details, please refer to Rao-Blackwellised Particle Filtering for Fault Diagnosis and On Sequential Simulation-Based Methods for Bayesian Filtering After downloading the file, type "tar -xf demo_rbpf_gauss.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab and run the demo.
標簽： filtering particle Blackwellised conditionall
上傳時間： 2014-12-05
上傳用戶：410805624
matlab實現的粒子濾波器源代碼，多若干實例并有與Kalman濾波器性能的比較
上傳時間： 2014-12-04
上傳用戶：ghostparker
三維目標跟蹤，采用擴展KALMAN濾波~效果還算不錯。
標簽： 目標跟蹤
上傳時間： 2016-05-13
上傳用戶：xiaodu1124
