Multi-source data fusion positioning monitoring method and system for low-altitude aircraft

By using a multi-source data fusion positioning and monitoring method, the problem of positioning accuracy and continuity of low-altitude aircraft in complex environments has been solved, achieving high-precision low-altitude airspace monitoring and safety assurance, and providing highly robust positioning adaptable to scenarios such as urban obstruction and multi-path in mountainous areas.

CN121297860APending Publication Date: 2026-01-09ZHEJIANG SCI RES INST OF TRANSPORT
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Patent Information

Application Number
CN202511599965.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-04
Publication Date
2026-01-09

AI Technical Summary

Technical Problem

Existing low-altitude aircraft positioning and monitoring technologies are difficult to achieve high-precision and high-continuity positioning and monitoring in complex environments. Single data sources are easily subject to interference, drift, or failure, and cannot meet the high-precision requirements of low-altitude operations.

Method used

A multi-source data fusion positioning and monitoring method is adopted, which includes collecting BeiDou absolute position data of low-altitude aircraft, pose data relative to local maps, and broadcast data from surrounding aircraft or ground stations. Through anomaly data processing, spatiotemporal alignment, scene area division, and weight configuration, the method achieves preliminary fusion of multi-source data and state space fusion, and dynamically adjusts the weights to adapt to different environments.

Benefits of technology

It improves the positioning accuracy and continuity of aircraft in complex environments, ensures high-reliability surveillance and safety in low-altitude airspace, and adapts to dynamic mission requirements in diverse environments.

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Abstract

The invention discloses a multi-source data fusion positioning monitoring method and system for a low-altitude aircraft. The method comprises the following steps: collecting multi-source data, carrying out abnormal data processing, and then carrying out space-time alignment; dividing the Beidou absolute position data into different scene regions, preliminarily fusing the aligned multi-source data in the scene regions, configuring basic weights of the multi-source data in different flight scenes, and calculating dynamic weights of the multi-source data in real time based on equivalent variances of the multi-source data to obtain real-time comprehensive weights of the multi-source data; and performing state space fusion based on the preliminary fusion positioning information and the real-time comprehensive weight of each piece of multi-source data. According to the method, the pain point that a single data source is easily interfered, drifted or invalid is solved, and meanwhile, the real-time weight of each multi-source data can be intelligently optimized according to a task environment, real-time data quality and a task instruction, so that a fusion positioning result is corrected, and reliable monitoring in dynamic tasks such as emergency search and rescue, logistics transportation and the like is guaranteed.
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