An iterative volume point unscented Kalman filter method

Abstract

The invention discloses an iterative volume point unscented Kalman filter method, which comprises the following steps: selecting a sigma point of an iterative volume point untraceable Kalman filter algorithm; Redefining the weighting coefficients of sigma points; The flow chart of volume point unscented Kalman filter algorithm is given. Iterative computation of volume point unscented Kalman filteralgorithm. The invention can be effectively applied in a system with high degree of freedom and strong nonlinearity containing random noise, and can solve the problems of computational load, nonlinear filter divergence and negative weight through cooperative processing, and can effectively improve the estimation accuracy and real-time performance of the state quantity, and can not diverge the filtering result. Compared with the volume Kalman filter, the invention can better fit the statistical characteristics of the nonlinear system function, and can avoid the non-positive definiteness of thesigma point weights compared with the untraceable Kalman filter.

Description

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AI Technical Summary

Benefits of technology

This patents describes an improved method for estimating states from noisy signals that are highly dynamic or have complex dynamics such as those caused by randomly distributed sources like radioactive particles (radiations) or other harmful agents. These methods help reduce errors associated with these systems while improving their ability to estimate unknown quantities accurately over time without being affected by external factors affecting them.

Problems solved by technology

This patents describes different methods called extended kalman or volumetrically-based algorithms (VKA) to estimate systems states accurately even when they have unknown environmental factors like temperature changes over time due to their operation at sea level. However these existing approaches may result in poor performance under certain types of environments where sensor measurements change frequently.

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