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Asynchronous multi-sensor space-time deviation joint estimation and compensation method and device

A multi-sensor, joint estimation technology, applied in complex mathematical operations and other directions, can solve the problem of effective estimation method and device for asynchronous sensor space-time deviation, etc., and achieve the effect of effective estimation and compensation

Active Publication Date: 2018-07-24
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In the prior art, there is no method and device that can effectively estimate the space-time deviation of the asynchronous sensor and the target state

Method used

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  • Asynchronous multi-sensor space-time deviation joint estimation and compensation method and device
  • Asynchronous multi-sensor space-time deviation joint estimation and compensation method and device
  • Asynchronous multi-sensor space-time deviation joint estimation and compensation method and device

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Embodiment 1

[0066] Such as figure 1 As shown, wherein the joint estimation and compensation method of the space-time deviation of the asynchronous sensor includes:

[0067] Step a, use the filtering algorithm to estimate the target state, determine the estimated state and the estimated state error covariance matrix at k-1 fusion time, and calculate the state sampling points and corresponding weights at k-1 fusion time;

[0068] In this step, the UKF filter algorithm is used to estimate the target state, which has high precision and good stability.

[0069] UKF (Unscented Kalman Filter), the Chinese interpretation is lossless Kalman filter, unscented Kalman filter or dearomatic Kalman filter. It is a combination of lossless transformation (UT) and standard Kalman filtering system, through lossless transformation, the nonlinear system equation is suitable for the standard Kalman filtering system under the linear assumption.

[0070] Among them, the insensitive transformation is used to ca...

Embodiment 2

[0080] As described above, the asynchronous multi-sensor space-time deviation joint estimation and compensation method, the difference of this embodiment is that in the step a, the specific calculation formula of the state sampling point at k-1 fusion time and the corresponding weight value for:

[0081]

[0082] Among them, the number of state sampling points is 2m in total,

[0083] In the formula, ξ is the state sampling point, G is the weight; ξ j (k-1|k-1) and G j They are the jth state sampling point and weight at the k-1th fusion moment, k represents the serial number of the current fusion moment, m is the dimension of the state vector, and λ is the estimated value used to determine the k-1 fusion moment The scale parameter of the distribution state of the surrounding state sampling point ξ, and satisfy (m+λ)≠0; for The jth row or jth column of ; and P(k-1|k-1) are the estimated state and estimated state error of the expanded dimension state vector A(k-1) an...

Embodiment 3

[0096] The difference between this embodiment and the asynchronous multi-sensor space-time bias joint estimation and compensation method described above is that in the step b, for the predicted state sampling point ξ j (k|k-1), predicted state and predicted state error covariance matrix P(k|k-1); where the predicted state sampling point ξ j (k|k-1) represents the state sampling point ξ based on the k-1 fusion moment j(k-1|k-1) Prediction of the state sampling point at the kth fusion moment, predicting the state Represents the state estimation based on the k-1th fusion moment For the prediction of the state at the kth fusion moment, the predicted state error covariance matrix P(k|k-1) means that the covariance matrix estimation P(k-1|k-1) based on the k-1th fusion moment Prediction of the state error covariance matrix at k fusion moments; the left side of the vertical line represents that the prediction process is based on the conditions at the k-1th fusion moment, and th...

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Abstract

The invention discloses an asynchronous multi-sensor space-time deviation joint estimation and compensation method and device. The method includes the steps of a, calculating a state sampling point and a corresponding weight value at a k-1 fusion moment; b, calculating a prediction state sampling point, a prediction state and a prediction state deviation covariance matrix at a k fusion moment; c,calculating a predicted measurement sampling point and a predicted measurement vector; d, calculating an innovation covariance matrix and a cross covariance matrix between states and observation; e, determining an estimation state and an estimation state deviation covariance matrix at the k fusion moment; f, reading target state estimation, space deviation estimation and time deviation estimation;g, making k equal to the sum of k and 1 and repeating the procedures above to form a closed-loop cyclic operation, wherein the device corresponds to the method. In this way, under the situation thatthe data rates of sensors are different, state vectors after dimensional expansion are estimated, and the target state estimation is obtained through iteration while effective estimation and compensation of space-time deviations are achieved.

Description

technical field [0001] The invention relates to the technical field of target tracking and positioning, in particular to an asynchronous multi-sensor space-time deviation joint estimation and compensation method and device. Background technique [0002] Eliminating the systematic error of sensor measurement data and completing the time synchronization of sensor information are the basis for realizing the correct fusion of multi-sensor information. At present, most researches on algorithms focus on the problems of time alignment and spatial deviation registration. [0003] Dana M P.Registration:A prerequisite for multiple sensor tracking[J].Multitarget-Multisensor Tracking:Advanced Applications,1990,1:155-185. A generalized least squares method is proposed to solve the spatial deviation registration problem. This method uses each The corresponding measurement equations are derived from the time measurement data and spatial deviation in the two-dimensional plane, and the corre...

Claims

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Application Information

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IPC IPC(8): G06F17/16
CPCG06F17/16
Inventor 周共健卜石哲
Owner HARBIN INST OF TECH
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