3D Object Tracking Method Based on Unbiased Transformation Measurement Based on Decorrelation

Abstract

The present invention provides a three-dimensional target tracking method based on de-correlation unbiased transformation measurement, including: obtaining the unbiased transformation measurement under the Cartesian coordinate system from the measurement value and measurement noise variance of the maneuvering target at the current moment in the spherical coordinate system value; obtain the one-step prediction error of the unbiased conversion measurement value as the first prediction error; use the predicted estimated value and prediction variance of the characteristic parameters to obtain the covariance matrix of the unbiased conversion measurement error; based on the covariance matrix and the second prediction Error autocorrelation matrix to obtain the Kalman gain; based on the Kalman gain and the second prediction error autocorrelation matrix, the state estimation error autocorrelation matrix is ​​obtained; based on the Kalman gain, the first prediction error and the one-step prediction state vector, the state estimation vector is obtained ; Obtain the reduced state estimation vector by using the reduction factor; obtain the reduced state estimation vector and the state estimation error autocorrelation matrix at each acquisition time through the recursion of the acquisition time, so as to realize the tracking of the maneuvering target.

Description

technical field [0001] The invention relates to the field of radar target tracking, in particular to a three-dimensional target tracking method based on decorrelation unbiased conversion measurement. Background technique [0002] In the radar target tracking system, the state equation of the target is generally established in the Cartesian coordinate system, and the measurement equation is generally established in the polar (spherical) coordinate system, and the measurement value is generally obtained in the polar (spherical) coordinate system. In order to linearize the measurement equation, the method of conversion measurement is usually used, that is, the measurement value is converted from the polar (spherical) coordinate system to the rectangular coordinate system. Therefore, in the target tracking method involving conversion measurement, how to ensure the unbiased conversion measurement value and eliminate the correlation between the conversion measurement error covaria...

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Problems solved by technology

[0005] The first method is based on the unbiased decorrelation conversion measurement Kalman filter method (DCMKFwU), which uses the conversion measurement error covariance matrix of the previous moment to replace the conversion measurement error at this moment on the basis of UCMKF The covariance matrix is ​​used to calculate the Kalman filter gain, which can eliminate the dependence between the Kalman gain and the measurement noise, obtain an unbiased state estimate, and also ensure the unbiased conversion of the measured value, but this method Also, the correlation between the conversion measurement error covariance matrix and the measurement noise is not eliminated, so when this method is used to track the target, the tracking accuracy is not high

[0006] The second method is the Kalman filter method based on unbiased transformation measurement based on decorrelation. This method uses the method of unbiased transformation measurement in two-dimensional space to obtain the unbiased transformation measurement value, and derives it based on the position prediction value Transforming the mean value and covariance matrix of the measurement error eliminates the correlation between the transformation measurement error covariance matrix and the measurement noise. However, this method is limited to the tracking of targets in two-dimensional space, and cannot realize target tracking

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