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Research on Direction Cooperative Localization Model and Error Analysis for Manned–Unmanned Aircraft
Research on Direction Cooperative Localization Model and Error Analysis for Manned–Unmanned Aircraft
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Research on Direction Cooperative Localization Model and Error Analysis for Manned–Unmanned Aircraft
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Research on Direction Cooperative Localization Model and Error Analysis for Manned–Unmanned Aircraft
Research on Direction Cooperative Localization Model and Error Analysis for Manned–Unmanned Aircraft
Journal Article

Research on Direction Cooperative Localization Model and Error Analysis for Manned–Unmanned Aircraft

2025
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Overview
To achieve cooperative reconnaissance and localization of manned and unmanned aircraft, based on the traditional direction‐finding cross‐localization method, a direction cooperative localization model has been developed based on different baseline criteria. Compared with the traditional methods which require the reconnaissance platforms locating at the same fixed baseline, the proposed model can adapt to different conditions. In this model, the manned electronic reconnaissance aircraft can conduct tasks at a greater distance from the target, while the unmanned electronic reconnaissance aircraft cruises closer to the target. Moreover, the localization error is analyzed by using the circular error probable method, geometric approximation method, and the geometric dilution of precision method. In addition, through simulations, the affecting factors are studied. Simulation results demonstrate that a smaller direction‐finding error leads to a smaller localization error and the closer the unmanned electronic reconnaissance aircraft is to the target, the smaller the localization error. Moreover, simulation results demonstrate the existence of optimal direction‐finding angles that minimize localization error. These optimal angles are determined by the vertical distance between the reconnaissance aircraft′s cruise route and the target, as well as the direction‐finding error. These findings validate that the proposed model can offer better localization accuracy than the traditional method and can be applied in practical cooperative localization tasks.