Description: A method is presented for augmenting an extended
Kalman filter with an adaptive element. The resulting estimator
provides robustness to parameter uncertainty and unmodeled
dynamics.-A method is presented for augmenting an ext Kalman ended with an adaptive filter element. T he resulting estimator provides robustness to parameter uncertainty and unmodeled dynamics . Platform: |
Size: 339059 |
Author:rifer |
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Description: 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. Platform: |
Size: 827601 |
Author:吴大亨 |
Hits:
Description: A method is presented for augmenting an extended
Kalman filter with an adaptive element. The resulting estimator
provides robustness to parameter uncertainty and unmodeled
dynamics.-A method is presented for augmenting an ext Kalman ended with an adaptive filter element. T he resulting estimator provides robustness to parameter uncertainty and unmodeled dynamics . Platform: |
Size: 338944 |
Author:rifer |
Hits:
Description: 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. Platform: |
Size: 827392 |
Author:吴大亨 |
Hits:
Description: 用于机动目标跟踪的交互式多模型算法完整实现程序，无BUG-For maneuvering target tracking interactive multiple model algorithm for the full realization of program, no BUG Platform: |
Size: 1024 |
Author:汪俊 |
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Description: 基于EKF的神经网络自适应在线学习算法，包含例子和文档。-We show that a hierarchical Bayesian modeling approach allows us to perform
regularization in sequential learning. We identify three inference
levels within this hierarchy: model selection, parameter estimation, and
noise estimation. In environments where data arrive sequentially, techniques
such as cross validation to achieve regularization or model selection
are not possible. The Bayesian approach, with extended Kalman filtering
at the parameter estimation level, allows for regularization within
a minimum variance framework. A multilayer perceptron is used to generate
the extended Kalman filter nonlinear measurements mapping. We
describe several algorithms at the noise estimation level that allow us to
implement on-line regularization.We also show the theoretical links between
adaptive noise estimation in extended Kalman filtering, multiple
adaptive learning rates, and multiple smoothing regularization coefficients. Platform: |
Size: 393216 |
Author:xiaochen |
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Description: This paper presents an adaptive information fusion method to improve the
accuracy and reliability of the altitude measurement information for small unmanned aerial
rotorcraft during the landing process. Focusing on the low measurement performance of
sensors mounted on small unmanned aerial rotorcraft, a wavelet filter is applied as a
pre-filter to attenuate the high frequency noises in the sensor output. Furthermore, to
improve altitude information, an adaptive extended Kalman filter based on a maximum a
posteriori criterion is proposed to estimate measurement noise covariance matrix in real
time. Finally, the effectiveness of the proposed method is proved by static tests, hovering
flight and autonomous landing flight tests. Platform: |
Size: 388096 |
Author:Clovis |
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Description: A new approach to improved filter design is presented for
the radar tracking problem. An idealized version of the
extended Kalman filter, which is unrealizable in practice,
is constructed using a universal linearization concept, and
then it is utilized for the development of a practical tracking
filter. The resulting filter tunes the measurement error variance
in an adaptive manner to account for the measurement
nonlinearities effectively. Platform: |
Size: 189440 |
Author:aida |
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Description: The Kalman filter has been widely used to solve different filtering problems especially in
tracking and estimation applications. Besides its simplicity, robustness and optimality,
the application of Kalman filter to nonlinear systems can be complicated. The most common
method is to use extended Kalman filter which linearizes the nonlinear model so that
the standard Kalman filter can be applied. In this paper, a new adaptive Kalman filtering
algorithm is designed and applied to a railway track geometry surveying system which
has been designed in the scope of a research project at Yildiz Technical University/Turkey.
Track gauge, super-elevation, gradient and track axis coordinates which are the railway
geometrical parameters can be instantly determined while making measurements by using
adaptive Kalman filtering algorithm integrated surveying system Platform: |
Size: 886784 |
Author:Gomaa Haroun |
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Search - adaptive extended Kalman filter