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无人机的移动定位是应对无人机机动性和应用环境复杂性的关键技术。为解决无人机中的全球定位系统(GPS)信号失效问题,提出了一种通过机载无线射频的接收信号强度解决定位问题的技术,分别采用扩展卡尔曼滤波方法估计距离和最小二乘方法估计路径损耗因子两种处理方法。理论分析和实验测试结果证实所提算法对有色噪声干扰下的接收信号有较好的增强效果,基于80%的置信水平,新算法相对于白噪声模型将估算误差从9.5 m减少到了4 m,还进一步提供了融合惯性导航的算法。
UAV mobile positioning is the key technology to deal with the UAV mobility and application environment complexity. In order to solve the problem of global positioning system (GPS) signal failure in UAVs, this paper proposes a technique of locating the problem by using the received signal intensity of airborne radio frequency. The extended Kalman filter method is used to estimate the distance and least square method Estimation of path loss factor two processing methods. The theoretical analysis and experimental results show that the proposed algorithm can enhance the received signal under the interference of colored noise. Based on the confidence level of 80%, the new algorithm reduces the estimation error from 9.5 m to 4 m with respect to the white noise model. It further provides an algorithm for blending inertial navigation.