Constrained multi-model filtering method based on L1 regular unscented transformation

An unscented transformation, multi-model technology, applied in the field of nonlinear filtering, which can solve problems such as slow error convergence speed

Active Publication Date: 2020-06-16
SUN YAT SEN UNIV
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Problems solved by technology

Although the filtering accuracy of the nonlinear system is improved when the nonlinear system is affected by the unkn...

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  • Constrained multi-model filtering method based on L1 regular unscented transformation
  • Constrained multi-model filtering method based on L1 regular unscented transformation
  • Constrained multi-model filtering method based on L1 regular unscented transformation

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Embodiment Construction

[0104] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0105] It should be noted that all directional indications (such as up, down, left, right, front, back...) in the embodiments of the present invention are only used to explain the relationship between the components in a certain posture (as shown in the accompanying drawings). Relative positional relationship, movement conditions, etc., if the specific posture changes, the directional indication will also change accordingly.

[0106] In addition, in t...

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Abstract

The invention discloses a constraint multi-model filtering method based on L1 regular unscented transformation, and the method comprises the steps: providing a first constraint for the measurement truncation of a system, and integrating the first constraint and the latest measurement sequence of the system into the prior updating process of the system; smoothing between system observation intervals providing a second constraint of the system, and weighting correction and compensation of the space-time constraint by a fuzzy logic algorithm; approximating a feasible region by a heuristic optimization method, wherein a low-dimensional manifold model is modeled through a constraint auxiliary particle filtering framework, and unscented Kalman smoothing filtering is carried out on a model statebased on L1 regularization.

Description

technical field [0001] The invention relates to the technical field of nonlinear filtering, in particular to a constrained multi-model filtering method based on L1 regular unscented transformation. Background technique [0002] In the model uncertainty problem of target tracking, H.A.P.Blom, Y.Bar-Shalom. "The interacting multiple model algorithm for system with Markovian switching coefficients," IEEE Transactions on Automatic Control, vol.33(8), pp.780-783, 1988 proposed a classic interactive multi-model filtering method. This classic method uses the model transition probability to automatically identify the currently used model and perform model switching, thereby realizing adaptive filter estimation under multiple models. But the disadvantage is that the estimation accuracy is not very high, and it depends on the setting of the model transition probability. When the value of the model-invariant transition probability is set to be large, although the error in the model-in...

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Application Information

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IPC IPC(8): G06F30/20
Inventor 张宏伟张小虎杨夏
Owner SUN YAT SEN UNIV
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