A SINS/BDS Integrated Navigation Method Based on Classified Weighted Adaptive Filtering

According to the trajectory specialty of hypersonic boost-glide vehicles, a strapdown inertial navigation system/BeiDou navigation satellite system (SINS/BDS) algorithm based on the launch-centered inertial (LCI) frame for hypersonic vehicles is proposed. First, the related frame system, especially the launch earth-centered inertial (LECI) frame, and the SINS mechanization in the LCI frame are introduced. Second, SINS discrete updating algorithms in the LCI frame for the compensation of coning, sculling, and scrolling effects are deduced in the attitude, velocity, and position updating algorithms, respectively. Subsequently, the Kalman filter of the SINS/BDS integrated navigation in the LCI frame is obtained. The method of converting BDS receiver position and velocity from the Earth-centered Earth-fixed (ECEF) frame to the LCI frame is deduced through the LECI frame. Finally, taking the typical hypersonic boost-glide vehicles as the object, the SINS/BDS algorithm vehicle field test and hardware-in-the-loop simulation are performed.

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“…where g r ′ is calculated by (8) and g ω e is calculated by (9). r 0 is the unit vector of r, and r is calculated by (10):…”

Section: Sins Mechanization In the Lci Framementioning

confidence: 99%

“…e X-43A used an INS/GPS integrated navigation system and the geography coordinate system navigation algorithm [9]. Kang et al studied an INS/BDS integrated navigation method in the ENU geography coordinate system [10]. Li studied the aerial alignment method of the integrated navigation system in the local horizontal coordinate system [11].…”

Section: Introductionmentioning

confidence: 99%

SINS/BDS Integrated Navigation for Hypersonic Boost-Glide Vehicles in the Launch-Centered Inertial Frame

Chen

Shen

Zhou

et al. 2020

Mathematical Problems in Engineering

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“…The robust estimation method can be added to the CKF filter (H∞CKF) to improve its robustness. A classified weighted adaptive filter-based integrated strap-down INS/Bei Dou navigation satellite system (SINS/BDS) was put forward to remove the declining CKF accuracy problem caused by modelling uncertainties (Kang et al, 2019). Pakki et al used Arasaratnam and Haykin (2010) to achieve a cubature rule-based third-degree spherical-radial filter (2011).…”

Section: Introductionmentioning

confidence: 99%

Low-cost integrated INS/GNSS using adaptive H∞ Cubature Kalman Filter

Taghizadeh

Safabakhsh

2023

J. Navigation

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We proposed an adaptive H-infinity Cubature Kalman Filter (AH∞CKF) to improve the navigation accuracy of a highly manoeuvrable unmanned aerial vehicle (UAV). AH∞CKF fuses the Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) measurements. Traditional state estimation filters like extended Kalman filters (EKF) and cubature Kalman filters (CKF) assume Gaussian noises. However, their performance degrades for non-Gaussian noises and system uncertainties encountered in real-world applications. Thus, designing filters robust to noise and distribution is crucial. AH∞CKF combines H∞CKF design with an added adaptive factor to adjust the state estimation covariance matrix according to measurements by exploiting the square root method to yield more numerically stable results (SrAH∞CKF). We conducted multiple dynamically rich flight tests to validate our claims using a UAV equipped with a commercially well-known GNSS solution. Results show that the SrAH∞CKF state estimation outperforms EKF and CKF methods on average by 90% in various statistical measures.

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“…In [12], in order to achieve better navigation capability of inertial navigation system, a new fault-tolerant filter is proposed. In [13], a class-based weighted adaptive filtering algorithm was proposed to address the degradation of model uncertainty and observation anomaly in integrated navigation system, which resulted in the decline of accuracy and stability. In [14], an adaptive federated filter was proposed to obtain distribution factors based on navigation performance and detect abnormal measured values of the filter.…”

Section: Introductionmentioning

confidence: 99%

In-Flight Alignment Method of SINS/GPS Integrated Navigation System Based on IUKF

You

Cao

Gao

2021

Lecture Notes in Electrical Engineering

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SINS (Strap-down Inertial Navigation System) and GPS (Global positioning system) integrated navigation system has been extensively applied in many areas. In-flight alignment (IFA) is one of the key technologies. In this paper, an iterative unscented Kalman filter (IUKF) for SINS/GPS integrated navigation system is proposed to achieve IFA approach. Firstly, the nonlinear error equation of SINS is established, and the difference between the position and velocity of the two navigation systems is taken as the observation variables. Then, an IUKF is proposed to minimize the truncation error caused by Taylor expansion and reduce the influence of initial state value on the system state. Finally, simulation results can prove that the IUKF improves the navigation precision and robustness of system compared with the counterpart of UKF.

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A SINS/BDS Integrated Navigation Method Based on Classified Weighted Adaptive Filtering

Cited by 5 publications

References 7 publications

SINS/BDS Integrated Navigation for Hypersonic Boost-Glide Vehicles in the Launch-Centered Inertial Frame

SINS/BDS Integrated Navigation for Hypersonic Boost-Glide Vehicles in the Launch-Centered Inertial Frame

Low-cost integrated INS/GNSS using adaptive H∞ Cubature Kalman Filter

In-Flight Alignment Method of SINS/GPS Integrated Navigation System Based on IUKF

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