Nonlinear observability analysis method based on conditional number fusion

Abstract

The invention relates to a nonlinear observability analysis method based on conditional number fusion, which belongs to the field of nonlinear system observability. The method comprises the followingsteps of: calculating a pseudo-state transition matrix and a pseudo-observation matrix by using a Lie derivative, secondly, calculating a pseudo-state transition matrix and a pseudo-observation matrixby utilizing cubature Kalman filtering, fusing to obtain a new pseudo-state transition matrix and a new observation matrix, and finally, calculating the nonlinear observability in combination with the Cramer-Rao bound. According to the method, a nonlinear observability calculation scheme fusing the Lie derivative and the cubature Kalman filtering is established, process noise and measurement noise are both considered in the nonlinear observability calculation scheme, and the nonlinear observability theory is further perfected.

Description

technical field [0001] The invention relates to a nonlinear observability analysis method based on condition number fusion, which belongs to the field of nonlinear system observability. Background technique [0002] Observability and observability are important concepts in the field of modern control. Since Kalman proposed the Kalman filter in the 1960s, the control theory has been continuously improved. Observability mentioned in modern control theory has become a hot issue studied by many scholars and experts. In fact, the analysis and calculation of the observability has attracted more and more attention from the engineering community. Some scholars have combined the observability with the strapdown inertial navigation system to analyze practical problems. There is an overall evaluation, so the filtering accuracy can be further improved. There are literatures that combine observability with Kalman filtering and transfer alignment and target tracking in three-dimensional ...

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