Unmanned bee colony collaborative navigation multi-fault detection method

Abstract

The invention discloses an unmanned bee colony collaborative navigation multi-fault detection method. Unmanned bee colony collaborative information is utilized to assist in carrying out multi-fault detection and identification on an unmanned aerial vehicle navigation system. Cooperative fault-tolerant architecture design is performed by combining relative measurement information of each unmanned aerial vehicle and navigation observation information of the unmanned aerial vehicle, a multi-stage Kalman filter is constructed by using combination of different measurement information, fault states of an unmanned aerial vehicle navigation satellite and cooperative measurement information are detected through differences of solutions of different filters, and fault measurement is isolated to realize fault-tolerant reconstruction of the unmanned aerial vehicle collaborative navigation system. The possible multi-fault condition of the unmanned bee colony navigation system is considered, filters of different levels are constructed to realize separation of multiple pieces of fault measurement information, the number of the fault measurement information of the collaborative navigation system can be flexibly detected, a hierarchical filtering structure does not need to be changed, and the method has good adaptability; and the method is wide in applicability and is not limited by types and quantity of collaborative auxiliary information.

Description

technical field [0001] The invention belongs to the technical field of navigation, and in particular relates to a multi-fault detection method for unmanned swarm cooperative navigation. Background technique [0002] Unmanned swarms are often used to perform complex and challenging tasks. When they work in harsh environments, the navigation system of unmanned swarms is prone to multiple types of failures occurring at the same time, which greatly affects the unmanned swarms. Autonomous and reliable flight of swarms. The traditional fault diagnosis method mainly uses the information of the aircraft's own sensors to construct a fault detection model. In the case of complex and uncertain interference, the detection sensitivity may decrease, and even detection errors may occur. The collaborative information between multiple UAVs provides multi-scale redundant measurement information for the UAV navigation system, which can be used to monitor the health status of the UAV navigatio...

AI Technical Summary

Problems solved by technology

[0004] Purpose of the invention: In order to solve the problems of traditional fault detection methods such as decreased sensitivity to multiple fault detection, diagnostic failure or wrong diagnosis, the present invention proposes a multi-fault detection method for unmanned bee swarm cooperative navigation

Images