Generating method of correlated data sequences

Abstract

The invention discloses a method for generating related data sequences. The method includes: using the given standard error σx, standard error σy and correlation coefficient ρxy to construct the covariance matrix P1 and the invertible matrix P; calculate the contract transformation matrix P2 of the covariance matrix P1; calculate the n The standard error σx' of the dimensional data sequence X' and the standard error σy' of the n-dimensional data sequence Y'; according to the standard error σx', use the random function to generate the n-dimensional data sequence X'; according to the standard error σy', use the random function , to generate n-dimensional data sequence Y'; according to n-dimensional data sequence X', n-dimensional data sequence Y' and reversible matrix P, n-dimensional data sequence X and n-dimensional data sequence Y are obtained. The invention achieves the purpose of accurately and simply generating data meeting the requirements of relevant standard errors from independent non-correlated sequences through numerical calculation.

Description

technical field [0001] The invention relates to data sequence generation technology, in particular to a method for generating related data sequences. Background technique [0002] The accuracy of the inertial navigation system can be expressed by the degree of consistency with the standard error. The most commonly used method of measuring the accuracy of the inertial navigation system is the circular error probability (CEP) based on the two-dimensional plane. This accuracy metric provides a simple measure of ballistic missile impact location accuracy, which is defined as the radius of a circle around the actual target that contains 50% of the missile warhead impact, with the center of the CEP circle being the location of the actual horizontal plane. [0003] For the navigation landing point, the distance between the projection point of the actual landing point on the shooting plane and the target point is called the longitudinal deviation; the distance between the landing po...

AI Technical Summary

Problems solved by technology

[0011] At this time, the data of (x, y) has zero mean and standard error is σ x , σ y , but cannot satisfy the ρ in formula (2) xy ≠0 requirements

[0012] At present, due to the fact that the actual flight landing point data is a small sample, it is difficult to comprehensively evaluate the accuracy of the missile landing point. There is an urgent need for a method to generate data for simulated shooting and make high-precision analysis of the missile landing point. Therefore, it is necessary to carry out circular probability error Generation method of correlation data sequence for calculation

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