State estimation and data fusion method for multi-rate observation data

A technology of observation data and state estimation, which is applied in the fields of electrical digital data processing, special data processing applications, calculations, etc., and can solve problems such as distributed data fusion and energy saving issues that are not considered

Inactive Publication Date: 2015-02-04
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

In the past few years, there have been many articles combining the transmission rate method with the distrib

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  • State estimation and data fusion method for multi-rate observation data
  • State estimation and data fusion method for multi-rate observation data
  • State estimation and data fusion method for multi-rate observation data

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Embodiment Construction

[0036] The following examples illustrate the present invention:

[0037] Hardware environment: computer; correlator

[0038]Software configuration: Windows 2000 / XP; any language environment software such as matlab or C language or C++.

[0039] The block diagram of centralized, sequential and distributed state estimation and data fusion methods for multi-rate observation data in wireless sensor networks is shown in figure 1 , as shown in 2, 3.

[0040] A multi-rate sensor, discrete-time linear dynamical system with N sensors observing the same target can be described as

[0041] x(k i+1 )=A p x(k i )+B p w p (k i ), i=0,1,2,...

[0042] the y l (k i )=C pl x(k i )+v pl (k i ),l=1,2,...,N

[0043] Among them, x(k i )∈R n is k i The state of the system at time. A p ∈R n×n is the system transition matrix, B p ∈R n is the system noise matrix; w p (k i ) is the system noise, modeled as a Gaussian distribution.

[0044] is sensor l at time k i Measureme...

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Abstract

The invention provides a centralized state estimation and data fusion method for multi-rate observation data. By applying the lift technique, a multi-rate estimation system is modeled into a single-rate discrete time system with multiple random parameters; upon an obtained system model, a centralized fusion estimation algorithm, a sequential fusion estimation algorithm and a distributed fusion estimation algorithm are respectively proposed.

Description

technical field [0001] The invention belongs to the technical field of multi-sensor information fusion in the aspect of information processing, and relates to a state estimation and data fusion method of multi-rate observation data. Background technique [0002] In dynamic systems, filtering is an estimate of the current state. The word "filter" is used because the process of obtaining an optimal estimate from noisy data amounts to "filtering out" the noise. The term filtering therefore has the meaning of eliminating interfering signals, that is, noise. In the control system, the controller also needs to filter the signal to obtain the state estimation in the dynamic system. Signal filtering is often used in signal processing in the frequency and space domains. In the spatial domain, e.g. selecting signals coming from a certain direction. Navigation is an evaluation platform for detecting the position of sensors. [0003] In the sensor network, the state estimation can ...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 闫莉萍姜露夏元清付梦印
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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