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A Square Root Volumetric Kalman Filter Method in Nonlinear Target Tracking System

A technology of Kalman filtering and target tracking, which is applied in the direction of radio wave measurement system, general control system, control/regulation system, etc., can solve the problem that the system is difficult to obtain the mathematical model and noise statistical characteristics, the state of the hull motion cannot be completely stable, the mathematical It is difficult to accurately specify the statistical characteristics of the model and noise, so as to improve the accuracy of the algorithm, reduce the amount of calculation, and improve the real-time performance

Active Publication Date: 2019-06-11
WUHAN UNIV OF TECH
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Problems solved by technology

[0004] (1) Under normal circumstances, many factors such as environmental changes will make it difficult for the system to obtain accurate mathematical models and noise statistical characteristics. It is impossible to be completely stable. At this time, the mathematical model of system motion and the statistical characteristics of noise are difficult to accurately give

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  • A Square Root Volumetric Kalman Filter Method in Nonlinear Target Tracking System
  • A Square Root Volumetric Kalman Filter Method in Nonlinear Target Tracking System
  • A Square Root Volumetric Kalman Filter Method in Nonlinear Target Tracking System

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[0023] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0024] For the analysis of general nonlinear target tracking system, its mathematical model can be described as:

[0025] x k =f(x k-1 )+w k-1 (1);

[0026] z k =h(x k )+v k (2);

[0027] In formula (1), x k is the system state vector at the kth sampling time, f(x) is the system transfer function, w k-1 is the system noise vector at the k-1th sampling time.

[0028] In formula (2), z k is the system measurement vector at the kth sampling time, h(x) is the system measurement function, v k Measure the noise vector for the kth sampling instant.

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Abstract

The invention discloses a square root volume Kalman filtering method in a non-linear target tracking system, which aims to an adaptive square cubature Kalman filtering (ASCKF) algorithm, improves the time updating link and the Sage-Husa noise estimator link and forms an ASCKFNS algorithm. The method of the invention is suitable for a non-linear discrete system and further increases the algorithm accuracy on the premise of ensuring the stability of the algorithm. In addition, computation amount is reduced and the real-time performance is increased.

Description

technical field [0001] The invention belongs to the technical fields of data fusion and filtering algorithms, and relates to a square root volumetric Kalman filtering method, in particular to a square root volumetric Kalman filtering method in a nonlinear target tracking system. Background technique [0002] The sensor will be disturbed by random noise when monitoring the target tracking system. The Kalman filter algorithm can use the state equation and measurement equation of the discrete system to optimally estimate the system and reduce the impact of random noise interference (Reference 1). The conventional Kalman filter algorithm is only suitable for linear discrete systems. Two scholars, Arasaratnam and Haykin, proposed a square root volumetric Kalman filter (Square-root Cubature Kalman Filter, SCKF) algorithm for nonlinear discrete systems, which improves the stability of the filter and Accuracy (Reference 2), but in an environment where the statistical properties of t...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S13/66G01S7/292G01S7/35G01S5/02G05B13/04
CPCG01S5/0294G01S7/292G01S7/354G01S13/66G05B13/042
Inventor 刘小珠林仕文冉凡松邓燕妮赵东明
Owner WUHAN UNIV OF TECH