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self-adaptive fault-tolerant cubature Kalman filtering method applied to target tracking

A Kalman filter and target tracking technology, applied in the field of target tracking, can solve the problems of reduced filtering accuracy and affecting adaptive filter estimation, etc.

Active Publication Date: 2019-05-31
HANGZHOU DIANZI UNIV
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Problems solved by technology

The occurrence of faults will affect the estimation of the statistical characteristics of the measurement noise by the adaptive filter, thereby reducing the filtering accuracy

Method used

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  • self-adaptive fault-tolerant cubature Kalman filtering method applied to target tracking
  • self-adaptive fault-tolerant cubature Kalman filtering method applied to target tracking
  • self-adaptive fault-tolerant cubature Kalman filtering method applied to target tracking

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Embodiment Construction

[0071] The present invention proposes an adaptive fault-tolerant volumetric Kalman filter method applied to target tracking. Firstly, a system model is established according to the motion state of the actual target tracking. Secondly, the steps of the adaptive fault-tolerant volumetric Kalman filter method are given. Finally, slowly changing faults are introduced. detection algorithm, its flow chart is as follows figure 1 shown, including the following steps:

[0072] Step 1: System modeling, considering the discrete-time nonlinear system model, the state equation and measurement equation of the tracking target are as follows:

[0073]

[0074] Where: x k+1 ∈ R n is the system state vector at time k+1, which is composed of displacement and velocity in the x direction and displacement and velocity in the y direction, f and h are known functions, z k+1 ∈ R m is the measurement vector of the system at time k+1, which is composed of the target movement distance and angle me...

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Abstract

The invention relates to a self-adaptive fault-tolerant cubature Kalman filtering method applied to target tracking. The present invention generally includes three parts of content. Wherein the firstpart performs system modeling according to an actual moving target; Secondly, estimating noise statistical characteristics according to an improved adaptive filtering method; And a third part, detecting a fault according to a chi-square test, and carrying out weighting processing on the information part during state estimation according to a detection result. The method not only can dynamically estimate the process noise covariance and the measurement noise covariance at the same time, but also can cope with the condition that data measured by the radar break down, and achieves the effective tracking of a target.

Description

technical field [0001] The invention relates to an adaptive fault-tolerant volumetric Kalman filter method applied in target tracking, belonging to the field of target tracking. Background technique [0002] In target tracking, Kalman filter is often used to estimate the target state. Through Kalman filter, the measurement noise in the sensor data can be eliminated to achieve the effect of precise target tracking. However, the traditional Kalman filter is based on the fact that the system model is accurate and linear, the process noise and measurement noise obey the Gaussian distribution with zero mean and fixed variance, and its statistical characteristics are known. However, in actual target tracking, most system models are nonlinear, and the statistical characteristics of system noise are not completely known or even unknown. At this time, using Kalman filter to estimate it will cause inaccurate or even divergent estimation results. . [0003] In order to solve the prob...

Claims

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Application Information

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IPC IPC(8): G06T7/277
Inventor 马中骋葛泉波何红丽
Owner HANGZHOU DIANZI UNIV
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