Least square method-based speed information outlier elimination method

A technique of least squares and speed information, applied in informatics, special data processing applications, instruments, etc., to achieve the effects of preprocessing, reducing filter divergence, and reducing errors

Inactive Publication Date: 2017-08-25
HARBIN ENG UNIV
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  • Abstract
  • Description
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Problems solved by technology

[0004] The purpose of the present invention is to provide a speed information outlier elimination method based on the least squares method that can solve the problem of elimination of the speed error value generated in the transmission process

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  • Least square method-based speed information outlier elimination method
  • Least square method-based speed information outlier elimination method
  • Least square method-based speed information outlier elimination method

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Embodiment Construction

[0026] The following examples describe the present invention in more detail.

[0027] combine figure 1 , first assume that the degree of trust is N. Then execute as follows:

[0028] Step 1. Obtain the speed information of the 4 moments before the current moment of the target;

[0029] Step 2, using the least squares algorithm to extrapolate the velocity estimate at the next moment;

[0030] Step 3, judging whether the difference between the speed measurement value and the speed estimation value satisfies the condition, and if so, the speed measurement value is accepted. Otherwise use the velocity estimate instead of the velocity measurement;

[0031] Step 4: When the number of consecutively received predicted values ​​exceeds the confidence level N, filter is re-established.

[0032] Assume that the target moves at a constant speed (v=2m / s) or at a uniform acceleration (v 0 =2m / s, a=0.02m / s 2 ), the velocity observations have a mean of 0 and a standard deviation σ v =...

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Abstract

The invention provides a least square method-based speed information outlier elimination method. Firstly a trust degree is set as N and then the method is implemented by the following steps of 1, obtaining speed measurement values of a target at four moments before a current moment; 2, extrapolating a speed estimation quantity of the next moment by using a least square algorithm; 3, judging whether difference values between the speed measurement values and the speed estimation quantity meet a condition or not, and if the condition is met, accepting the speed measurement values, otherwise, replacing the speed measurement values with the speed estimation quantity; and 4, when the frequency of continuously accepting the speed estimation quantity exceeds the trust degree N, reestablishing filtering. Through the method provided by the invention, preprocessing of speed measurement data is realized, and errors and filtering divergence caused by outliers are reduced, thereby facilitating subsequent filtering processing.

Description

technical field [0001] The invention relates to a speed information outlier elimination method. Background technique [0002] In practical engineering applications, due to reasons such as measurement systems or data transmission, outliers will appear in the measurement data, and their values ​​are often quite different from the actual measurement values. If they are directly applied to Kalman without screening The correction of the current state value by filtering will not only fail to correct the error existing in the state estimation, but will cause the filtering system to be unstable, and there will be a large deviation between the filtering result and the real state, and in severe cases, the filtering will diverge. Therefore, preprocessing the measurement information can reduce the positioning error and filter divergence caused by outliers. [0003] For speed information, carriers such as AUVs have weak mobility and small acceleration, and usually run at a constant spee...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
CPCG16Z99/00
Inventor 韩云峰孙大军崔宏宇张居成郑翠娥王永恒史春昊
Owner HARBIN ENG UNIV
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