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Research on Adaptive Multi-Source Information Fault-Tolerant Navigation Method Based on No-Reference System Diagnosis

机译:基于无参​​考系统诊断的自适应多源信息容错导航方法研究

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摘要

In order to obtain accurate and optimized navigation sensor information, it is necessary to study information fusion and fault diagnosis with high reliability, high precision and high autonomy, and then to propose a rapid and accurate intelligent decision-making scheme based on multi-source and heterogeneous navigation information. In view of the existing fault-tolerant navigation federated filter structure, the method of assuming the reference system (inertial navigation system) to be fault-free and then diagnosing the measuring sensor fault is generally adopted. Considering that the structure of the filter can’t detect and isolate the faults of the inertial navigation system, the performance of the MEMS inertial navigation system declines due to complex environments resulting from vibrations and temperature changes; additionally, external interference may lead to the direct failure of the MEMS inertial device. Therefore, this paper studies a fault-tolerant navigation method based on a no-reference system. For the sensor sub-system of a custom micro air vehicle (MAV), a fault detection method based on a reference-free system is proposed. Based on the fault type analysis, some improvements have been made to the existing residual chi-square detection method, and an interactive residual fault detection method with distributed states is proposed. On this basis, aiming at the characteristics of a reference-free system, the weight distribution scheme of the reference system and the tested systems are studied, and a self-regulation filter fusion and fault detection method based on reference-free system is designed.
机译:为了获得准确,优化的导航传感器信息,有必要研究具有高可靠性,高精度和高度自治性的信息融合和故障诊断,然后提出一种基于多源和多目标的快速准确的智能决策方案。异构导航信息。鉴于现有的容错导航联合滤波器结构,通常采用以下方法:假设参考系统(惯性导航系统)无故障,然后对测量传感器故障进行诊断。考虑到滤波器的结构无法检测和隔离惯性导航系统的故障,由于振动和温度变化导致的复杂环境,MEMS惯性导航系统的性能下降;另外,外部干扰可能导致MEMS惯性设备直接失效。因此,本文研究了一种基于无参考系统的容错导航方法。针对定制微型飞机(MAV)的传感器子系统,提出了一种基于无参考系统的故障检测方法。在故障类型分析的基础上,对现有的残差卡方检测方法进行了一些改进,提出了一种具有分布状态的交互式残差故障检测方法。在此基础上,针对无参考系统的特点,研究了参考系统和被测系统的权重分配方案,设计了一种基于无参考系统的自调节滤波器融合与故障检测方法。

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