Multi-sensor space-time deviation compensation method and device with any period

Abstract

The invention relates to a multi-sensor space-time deviation compensation method with arbitrary period. The method comprises: calculating the state sampling point data of the k-1th moment and correspondingly according to the dimension expansion state data of the k-1th time, using the insensitive transformation The weight of the state;acquiring the state prediction data of the kth time according tothe state sample point data of the k-1th time and the corresponding weight; and acquiring the kth state according to the state prediction data of the kth time and the corresponding weight Observing and predicting the sampling point and the observation prediction vector at each moment; obtaining the innovation matrix and the cross-covariance matrix between the state and the observation according to the observation prediction vector at the kth moment, the observation prediction sampling point and the corresponding weight, and updating the Karl Manner gain; according to state prediction data, observation prediction vector and innovation matrix and cross-covariance matrix, update the dimension state estimation and the expansion state error covariance matrix at the kth time to obtain multi-sensor space-time deviation estimation and Target state estimation.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a multi-sensor space-time deviation compensation method, device, computer equipment and readable storage medium with arbitrary periods. Background technique [0002] Multi-sensor data fusion is an important part of the target tracking field. By fusing observation data from multiple sensors, a multi-sensor system can achieve better tracking performance than a single sensor. In an actual multi-sensor system, due to signal processing, data transmission, and filtering delays, there is a fixed delay between the time stamp of the observed data and the real measurement time, and there is a time deviation problem in the system. At the same time, due to the imperfect structure of the sensor, there will be fixed spatial deviation in the sensor observation data. Therefore, in order to achieve accurate fusion of observation data, it is necessary to estimate and compensate the syst...

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Problems solved by technology

[0003] Most of the existing algorithms focus on the research of spatial deviation registration, and some algorithms consider the problem of time deviation, but only solve the problem of time deviation estimation when the sensor observation period is known, and do not solve the problem of spatial deviation under any situation of sensor observation period. Research on Simultaneous Estimation of Time Offset and Target State

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