Multi-source positioning information fusion method applied to long-endurance unmanned aerial vehicle load

Abstract

The invention belongs to the technical field of unmanned aerial vehicle loads, and provides a multi-source positioning method for a long-endurance unmanned aerial vehicle load. The method comprises the following steps of: firstly, acquiring initial calculation information of an unmanned aerial vehicle integrated navigation system and a load system, judging an outlier of the unmanned aerial vehicle integrated navigation system, and if a result is an outlier, enabling a load positioning system to calculate position information at the current moment by the positioning system of the load positioning system itself; otherwise, transmitting the calculation information at the current moment to a positioning system carried by a load; carrying out outlier judgment on the load positioning system, and if the obtained calculation information of the load positioning system is an outlier, carrying out forecasting by only using the information transmitted by the unmanned aerial vehicle integrated navigation system to obtain the position at the current moment; if the two values of the unmanned aerial vehicle integrated navigation system and the load positioning system are not outliers, carrying out information fusion on the two values, fusing the position information calculated by the unmanned aerial vehicle integrated navigation system and the position information calculated by the load positioning system, Thus, the load position estimation precision is enhanced, and the working performance of the load is improved.

Description

technical field [0001] The invention belongs to the technical field of unmanned aerial vehicles, and in particular relates to a multi-source positioning method for long-endurance unmanned aerial vehicles. Background technique [0002] Aeronautical earth observation technology is widely used. With the development of UAVs and various payloads, the use of UAVs to carry payloads for earth observation can achieve higher-precision three-dimensional mapping, wind and wave measurement and other functions. The realization of the above functions needs to solve the position information of the load itself, complete the splicing of the measurement information, and form the measurement results of the target area. There are currently two ways to obtain the location information of the payload. One is to use the integrated navigation system information of the UAV, and the other is to use the information of the payload's own positioning system. But both have certain limitations: For the firs...

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Problems solved by technology

But both have certain limitations: for the first method, although the payload is fixedly connected to the UAV, the position information calculated by the integrated navigation system of the UAV can theoretically be equivalent to the position information of the payload, but the second method is The first method does not use the same set of time systems, and there will be deviations; for the second method, due to factors such as size and power consumption, the load generally cannot carry a high-performance positioning system, and the position estimation accuracy is not high

However, the above methods either bring extra consumption and bring a great burden to the UAV, or lack real-time performance and can only rely on post-processing

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