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Fault tolerant integrated radar/inertial altimeter based on Nonlinear Robust Adaptive Kalman filter

机译:基于非线性鲁棒自适应卡尔曼滤波器的容错雷达/惯性高度计

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摘要

The fault tolerant integrated navigation system, consisting of radar and inertial altimeters, is presented. In the open loop system, the inertial altimeter is the main source of information, and radar altimeter provides discrete aiding data to support the estimations. The integration is achieved by using a Nonlinear Robust Adaptive Kalman Filter with the filter gain correction based on the evaluation of the posterior probability of the normal operation of altimeter, given for current measurement. This probability is proposed to calculate via the posterior probability density of the normalized innovation sequence at the current estimation step. In the proposed filtration algorithm, the filter gain is corrected by multiplying with the mentioned posterior probability, which plays the role of the weight coefficients to the innovation vector. As a result, faults in the estimation system are corrected by the system, without affecting the good estimation behavior. The performance of the proposed fault tolerant integrated radar/inertial altimeter is tested for the different types of measurement faults; instantaneous abnormal measurements, continuous bias at measurements, measurement noise increment and fault of zero output.
机译:提出了一种由雷达和惯性高度计组成的容错组合导航系统。在开环系统中,惯性高度计是信息的主要来源,雷达高度计提供离散的辅助数据以支持估算。通过使用非线性鲁棒自适应卡尔曼滤波器和滤波器增益校正来实现积分,该滤波器增益校正基于对高度计正常运行的后验概率的评估(针对电流测量给出)。建议在当前估计步骤中通过归一化创新序列的后验概率密度来计算该概率。在所提出的滤波算法中,通过乘以上述后验概率来校正滤波器增益,后验概率起着权重系数对创新向量的作用。结果,估计系统中的故障被系统校正,而不影响良好的估计行为。针对不同类型的测量故障,测试了建议的容错集成雷达/惯性高度计的性能;瞬时异常测量,测量中的连续偏置,测量噪声增量和零输出故障。

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