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Two-Stage Volumetric Kalman Filtering Method Based on Nonlinear Unknown Random Bias

A technology of Kalman filtering and random deviation, applied in impedance networks, digital technology networks, electrical components, etc., can solve problems such as large amount of calculation, and achieve the effect of avoiding dimensional disaster and excessive computer calculation.

Inactive Publication Date: 2017-05-17
WUHAN UNIV OF TECH
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  • Abstract
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  • Application Information

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Problems solved by technology

This leads to the augmented state Kalman filter, but its application also has the problem of relatively large amount of calculation

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  • Two-Stage Volumetric Kalman Filtering Method Based on Nonlinear Unknown Random Bias
  • Two-Stage Volumetric Kalman Filtering Method Based on Nonlinear Unknown Random Bias
  • Two-Stage Volumetric Kalman Filtering Method Based on Nonlinear Unknown Random Bias

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Embodiment Construction

[0013] The following firstly establishes a model for the motion state of the tracking target, and then gives the filtering formula of the two-stage volumetric strong filter, which is divided into two steps: unbiased estimation and biased estimation, combined below figure 1 The implementation process of the present invention is introduced in detail.

[0014] 1 System Modeling

[0015] 1.1 Given the following nonlinear system dynamic model

[0016] x k =f k-1 (x k-1 )+w k,k-1

[0017] z k = h k (x k )+v k

[0018] where k≥1 is the moment index, x k ∈ R n×1 Indicates the system state (R n×1 is the complete set of n×1-dimensional column vectors), z k ∈ R n×1 is a column vector of measured values, f k-1 ( ) and h k (·) are all differentiable functions. initial state x 0 obey is the mean value, P 0 is the variance and is independent of w k and v k Random Variables. w k ∈ R n×1 and v k ∈ R m×1 are Gaussian white noise with zero mean, where δ ij is the ...

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Abstract

The invention relates to a two-stage cubature kalman filtering method based on nonlinearity unknown random deviation. For the portion which does not contain the unknown deviation, the one-step prediction value, the one-step prediction variance and the one-step prediction convariance are calculated. Thus, the gain array, the estimated value and the estimated error variance are calculated. For the portion which contains the unknown deviation, the one-step deviation estimation, the one-step deviation estimation variance and the one-step deviation estimated convariance are calculated. The deviation gain array, the one-step gain array of the deviation to the state variable and the estimated gain array are then calculated. Through the values calculated for the two portions, the one-step prediction value, the one-step prediction error variance, the estimated value and the estimated error variance of the nonlineary system which contains the unknown deviation are calculated. While filtering is completed, the calculation amount and the curse of dimensionality which are large for a computer are avoided.

Description

technical field [0001] The invention belongs to the filtering field of nonlinear systems, in particular to a two-order volumetric Kalman filtering method for dealing with nonlinear systems containing unknown random variables. Background technique [0002] Nonlinear filtering is one of the hot topics in the field of signal processing, target tracking and control. In particular, the research on nonlinear filtering under the framework of Kalman filtering is still a very hot issue, which has received more and more attention in recent years. attention and research. . [0003] The Kalman filter "provides an efficient solution for the state of position under minimum mean square error in a linear Gaussian system". However, in the real world, systems are always plagued by both nonlinear and non-Gaussian aspects. It is difficult to get a good idea of ​​state estimation. Extended Kalman is then widely used, and Untraced Kalman is another method that uses samples to solve nonlinear ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H03H17/02
Inventor 张露饶文碧
Owner WUHAN UNIV OF TECH