An improved nonlinear observability adaptive filtering method applied to pure azimuth tracking

Abstract

The invention relates to an improved nonlinear observability adaptive filtering method applied to pure azimuth tracking, and belongs to the field of observability adaptive filtering. In order to improve the pure azimuth tracking filtering performance, improve the observability theory of a nonlinear system and roughly evaluate the filtering precision of the pure azimuth system on the system beforefiltering, a new nonlinear observability calculation scheme is designed and established, and observation noise is considered; A self-adaptive adjustment factor based on the observability is designed;adding a regulation factor into the nonlinear filtering framework; The self-adaptive filtering effect under the mode is judged to be better by comparing the error covariance under different conditions, and the precision of self-adaptive filtering based on nonlinear observability can be further improved, so that the filtering performance of pure azimuth tracking is improved, and the pure azimuth tracking has better performance.

Description

technical field [0001] The invention relates to an improved non-linear observability self-adaptive filtering method applied to pure azimuth tracking, belonging to the field of observability self-adaptive filtering. Background technique [0002] Azimuth-only tracking is a commonly used technology in the field of target tracking. The Kalman filter method is often used to estimate it, and the purpose is to eliminate the error in tracking. Since the state space model of the pure bearing tracking system is mostly a nonlinear system in practical applications, the strong nonlinearity of the pure bearing tracking leads to a large error in linearizing the nonlinear system directly, that is, the unscented Kalman filter and the volumetric Kalman filter are often used . [0003] The modern control theory developed through the classical control theory, when Kalman proposed the Kalman filter, two important properties of observability and controllability were proposed, and then some schol...

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Problems solved by technology

However, noise is not taken into account in the current research on nonlinear observability, which will inevitably affect the evaluation of observability

[0004] When evaluating the observability in the azimuth-only target tracking system, the higher the observability, the higher the filtering accuracy, and the better the tracking performance of the target. On the contrary, the lower the observability of the azimuth-only tracking system, the lower the filtering accuracy is for the target. Tracking performance is poor

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