Abstract
Due to the high maneuverability of a hypersonic vehicle, the measurements for tightly coupled INS/GNSS (inertial navigation system/global navigation satellite system) integration system inevitably involve errors. The typical measurement errors include outliers in pseudorange observations and non-Gaussian noise distribution. This paper focuses on the nonlinear state estimation problem in hypersonic vehicle navigation. It presents a new innovation orthogonality-based robust unscented Kalman filter (IO-RUKF) to resist the disturbance of measurement errors on navigation performance. This IO-RUKF detects measurement errors by use of the hypothesis test theory. Subsequently, it introduces a defined robust factor to inflate the covariance of predicted measurement and further rescale the Kalman gain such that the measurements in error are less weighted to ensure the filtering robustness against measurement errors. The proposed IO-RUKF can not only correct the UKF sensitivity to measurement errors, but also avoids the loss of accuracy for state estimation in the absence of measurement errors. The efficacy and superiority of the proposed IO-RUKF have been verified through simulations and comparison analysis.
Highlights
Hypersonic vehicle refers to a vehicle at the speed of Mach 5 or above
The above simulations and analysis demonstrate that the proposed innovation orthogonality-based robust unscented Kalman filter (IO-robust UKF (RUKF)) can effectively inhibit the influences of the measurement errors on system state estimation by using the robust factor to adjust the Kalman gain matrix, leading to the higher navigation performance than derivative UKF (DUKF) and RUKF for tightly coupled INS/GNSS integration for hypersonic vehicle navigation
It addresses the disturbance on system state from measurement errors caused by highly dynamic maneuvers of a hypersonic vehicle
Summary
Hypersonic vehicle refers to a vehicle at the speed of Mach 5 or above. Due to the merits such as large flight envelope, high maneuverability and speedy global reach, hypersonic vehicle has received great attention in the recent years in both aeronautic and astronautic fields for various civil and military applications [1], [2]. Hu et al.: Robust Unscented Kalman Filtering With Measurement Error Detection unsuitable for hypersonic vehicle navigation This problem can be addressed by the tightly coupled integration in which the raw GNSS pseudorange measurements is directly used as measurements to update the navigation filtering. As to the INS/GNSS integrated system for hypersonic vehicle navigation, because the GNSS receiver is affected by abnormal interference during highly dynamic maneuvers, the measurements inevitably involve errors such as typical outliers in pseudorange observations and non-Gaussian characteristics of noise statistics [12], [19]. It requires UKF to counteract the above measurement errors involved in INS/GNSS integration for hypersonic vehicle navigation. This paper presents a novel innovation orthogonality-based robust UKF (IO-RUKF) for tightly coupled INS/GNSS integration for hypersonic vehicle navigation. The mathematical model of tightly coupled INS/GNSS integration is established for the sake of INS error estimation
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