Error compensation method for pollution emission remote sensing measurement based on transfer entropy and adaptive fusion

Abstract

The invention discloses an error compensation method for mobile source emission gas remote sensing measurement based on transfer entropy and adaptive fusion estimation. The error compensation method organically combines priori knowledge and an optimal estimation theory of a measured object and can obtain the optimal estimation of a true value from a noisy observation sequence. The error compensation method comprises the following steps: firstly, establishing a remote sensing measurement error prediction model under multiple interferences through an over-limit learning machine method; then, providing a virtual observation decomposition model and performing multi-sequence decomposition on the observation sequence by utilizing a virtual observation decomposition model; after that, transforming the actual measurement process into the multi-sensor virtual observation process and establishing a mathematical model for the multi-sensor virtual observation process; finally, performing fusion and reconstruction on multiple virtual observation sequences through introducing a transfer entropy and an adaptive Kalman filter to obtain the optimal estimation of a measurement sequence. The error compensation method disclosed by the invention can effectively compensate measurement errors caused by external environment interference and improve the environment applicability and the anti-interference ability of a remote sensing detection technology.

Description

technical field [0001] The invention relates to an error compensation method for remote sensing measurement of mobile source exhaust gas based on transfer entropy and adaptive fusion estimation, and belongs to the technical field of error compensation for gas remote sensing measuring instruments. Background technique [0002] Air pollution can be caused by stationary sources such as factory exhaust, or by mobile sources such as emissions from motor vehicles, mobile construction machinery, ships and aircraft. For stationary pollution source detection technology, biological methods can be used to reflect the degree of air pollution or chemical detection methods can be used to determine the concentration of pollutants, but these technologies are not directly applicable to mobile pollution sources. To address this challenge, remote sensing using optics has been proposed. This technique can retrieve the gas concentration based on the absorption characteristics of gas components ...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem that the remote sensing measurement of mobile source exhaust gas is easily interfered by the external environment, the present invention proposes an error compensation method based on transfer entropy causal analysis and adaptive Kalman fusion estimation

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