Multi-target multi-sensor information amalgamation method based on convex optimized algorithm

Abstract

The invention discloses an information fusion method which has multiple targets and multiple sensors and is based on a convex optimization algorithm, and relates to an information fusion method of a combined navigation system of strapdown inertia, a GPS, an atmospheric data computer and a three-shaft magnetometer. Firstly, the information fusion method uses the speed and posture data of the atmospheric data computer and the three-shaft magnetometer for stabilizing an inertia navigation system, thus forming a combined internal navigation system of the strapdown inertia, the atmospheric data computer and the three-shaft magnetometer with high reliability and high independence; secondly, according to the optimal control idea of the modern control theory, the information fusion method uses the convex optimization algorithm for designing a robust multi-target filter for the fusion of high-precision position of the GPS and speed measurement information, thus forming an external system to implement the hybrid H2 / H infinity / performance guarantee multi-target filtering on the internal system, thus improving the navigation precision of the whole system. The information fusion method completely exerts high reliability and usability of traditional navigation means and high precision of satellite navigation, and finally achieves the combined navigation technique with high reliability and high precision based on multiple sensors.

Description

technical field [0001] The invention relates to a multi-objective multi-sensor information fusion method, in particular to a multi-objective multi-sensor information fusion method based on a convex optimization algorithm, which is applicable to the technical field of aviation navigation, applicable to aircraft multi-sensor navigation, and also applicable to air navigation. Base and sea-based navigation and positioning. Background technique [0002] With the development of the national economy, navigation and positioning technology has increasingly become an indispensable technical means in traffic control, disaster relief, logistics management, land survey, survey and other fields; the realization of the efficiency of weapon launch platforms in the military field and the precise strike of fire weapons Rely on high-precision, high-reliability navigation means. At present, there are many navigation means, but none of them can meet the requirements alone. Combining multiple te...

AI Technical Summary

Problems solved by technology

Most of the existing integrated navigation research focuses on the kalman filter design of inertial / GPS integrated navigation. The navigation error is estimated through the Kalman filter, but the Kalman filter effect is poor due to the uncertainty of the model and noise. Although there are EKF, UKF and other improved methods, but still subject to too strong assumptions that make the actual application situation unsatisfactory

The GPS signal is unstable, susceptible to interference, and the GPS signal cannot be received at certain altitudes in the atmosphere. The Kalman filter does not perform well when the GPS signal has dead pixels.

Particle filter can solve the filtering problem under nonlinear and non-Gaussian conditions and has a strong tolerance for bad points in observations, but it still requires prior knowledge of noise, which is difficult to obtain in practical engineering applications, and The amount of calculation is too large, and the real-time performance cannot be guaranteed

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