State estimation method based on novel adaptive high-order unscented Kalman filter

An unscented Kalman and state estimation technology, applied in radio wave measurement systems, instruments, etc., to solve problems such as the need to improve accuracy

Inactive Publication Date: 2019-11-26
HARBIN ENG UNIV
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  • State estimation method based on novel adaptive high-order unscented Kalman filter
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  • State estimation method based on novel adaptive high-order unscented Kalman filter

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Embodiment approach 1

[0078] The specific implementation method can be divided into the following steps:

[0079] Step 1: Establish target tracking nonlinear discrete state model and measurement model;

[0080] Step 2: Select the optimal free parameter κ according to the state dimension of the target tracking system;

[0081] Step 3: Establish the adoption point and weight of high-order UT acquisition status;

[0082] Step 4: Pass the sampling points through a nonlinear function, and perform weighting processing to obtain the state one-step prediction and the state one-step prediction covariance matrix;

[0083] Step 5: Bring the optimal adaptive factor into the state and predict the covariance matrix in one step;

[0084] Step 6: Establish high-level UT acquisition and measurement adoption points and weights;

[0085] Step 7: Transfer the sampling points through a nonlinear function, and perform weighting processing to obtain the measurement one-step prediction and measurement one-step predicti...

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Abstract

The invention discloses a state estimation method based on novel adaptive high-order unscented Kalman filter, which belongs to the field of high-speed carrier state estimation in passive radar tracking. The method provided by the invention comprises the steps that a non-linear discrete state model and a measurement model of a target tracking system are established; the optimal free parameter k isselected according to the state dimension of the target tracking system; a high-order UT is established to acquire state adoption points and weights; sampling points are transferred through a nonlinear function; the optimal adaptive factor is brought into a state one-step prediction covariance matrix; a high-order UT is established to acquire measurement adoption points and weights; the sampling points are transferred through the nonlinear function; a gain matrix is calculated; and posterior state estimation output and the output of the covariance matrix are carried out. According to the invention, the influence of a strong nonlinear maneuvering target and large mutations on a filter is effectively suppressed; the method has a good influence on different sampling intervals and different corner rates; and the influence of dynamic model errors is reduced.

Description

technical field [0001] The invention belongs to the field of state estimation for high-speed carriers in passive radar tracking, and is based on a novel self-adaptive high-order unscented Kalman filter state estimation method. Background technique [0002] State estimation is the most basic aspect in the field of digital signals, and nonlinear processing is a difficult problem in digital signals, and nonlinear filters are a favorable method for dealing with dynamic systems. Many contributions have been made to deal with nonlinearities. These include the most typical method extended Kalman filter (EKF), which is based on the idea of ​​nonlinear function approximation, and requires to ensure that the nonlinear function is continuously differentiable or differentiable. For this method, Jacobian (Jacobian) is required at the technical level. Matrix solution. In engineering applications, the complexity of solving the Jacobian matrix is ​​extremely high, which is difficult to re...

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Application Information

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IPC IPC(8): G01S7/41
CPCG01S7/415
Inventor 周卫东侯佳欣田园刘璐周中元单承豪邹涵宋啸宇张聪张杰
Owner HARBIN ENG UNIV
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