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介绍几何定位过程,并对其定位误差进行仿真分析。针对几何定位误差很大且与下视角大小密切相关的问题,采用扩展卡尔曼滤波算法(EKF)抑制测量噪声的影响,提高飞行器的定位精度。建立飞行器运动的状态空间模型,针对测量方程的非线性特点,对其进行线性化处理。在此基础上,采用EKF算法实时估计飞行器的空间位置坐标;通过数字仿真对滤波算法的定位效果进行检验;对影响滤波算法定位精度的因素进行分析并对不同飞行高度下的定位误差进行数字仿真。结果表明,算法收敛速度快,定位精度高,可显著减小测量噪声的影响,具有一定的工程应用价值。
Geometry positioning process is introduced, and its positioning error is simulated. Aiming at the problem that the geometrical positioning error is very big and closely related to the size of the lower viewing angle, the extended Kalman filter algorithm (EKF) is used to suppress the influence of measurement noise and improve the positioning accuracy of the aircraft. The state space model of the aircraft movement is established. According to the nonlinear characteristics of the measurement equation, the model is linearized. On this basis, the EKF algorithm is used to estimate the space position coordinates of the aircraft in real time. The digital simulation is used to test the localization effect of the filtering algorithm. The factors affecting the positioning accuracy of the filtering algorithm are analyzed and the positioning errors at different flight altitudes are digitally simulated . The results show that the algorithm has the advantages of fast convergence and high positioning accuracy, which can significantly reduce the impact of measurement noise and has certain engineering application value.