The estimation of wing flexure deformation in transfer alignment based on inertial sensors network

Si, Fan; Zhao, Yan; Zhang, Xiaolei

doi:10.1109/aero.2017.7943568

Cited by 2 publications

(3 citation statements)

References 21 publications

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“…Through theoretical analysis and simulations, they concluded that the positioning accuracy could be improved under both normal operating conditions and fault conditions. Si [ 21 ] integrated the main INS positioning information and the INS positioning information of airborne weapons of fighter aircraft, thus improving the positioning accuracy of the weapon.…”

Section: Introductionmentioning

confidence: 99%

Experimental Research of Triple Inertial Navigation System Shearer Positioning

et al. 2023

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In order to improve the positioning accuracy of shearers, the overground experimental device based on the positioning model of TINS (Triple Inertial Navigation System) was built. The influence of TINS installation parameters on positioning accuracy was discussed through two sets of experiments: the inter-INS (Inertial Navigation System) distances influence experiments and the tri-INS plane spatial position influence experiments. The results show that the positioning accuracy of the shearer is improved to a different extent under the two sets of experimental conditions. When the inter-INS distances are 0.2 m, the positioning accuracy is the highest and the positioning accuracy improvement effect is also the best. When the negative plane α3 is 45°, the positioning accuracy is the highest, and the positioning accuracy improvement effect is also the best. The analysis shows that the main factor affecting the positioning accuracy is the precision of the evaluated values outputs of TINS from EKF (Extended Kalman Filter). Considering the positioning accuracy, equipment installation convenience and so on, the optimum installation parameters are 90° (horizontal installation) α3 for the positive plane and 0.2 m inter-INS distances.

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Section: Introductionmentioning

confidence: 99%

Experimental Research of Triple Inertial Navigation System Shearer Positioning

et al. 2023

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“…At present, the research about north-seeker includes basic inertial navigation error model [ 1 , 2 ], observability analysis [ 3 , 4 ], in-drilling alignment with general dynamic error model [ 5 ], alignment algorithms based on gyro-compassing mode [ 6 , 7 ], alignment based on the interacting multiple model and the Huber methods [ 8 ], rapid fine alignment under marine mooring condition [ 9 ], alignment for SINS (strapdown inertial navigation system) in vehicular environment [ 10 ], alignment based on Riccati Equation and EM (expectation-maximization) convergence [ 11 ], alignment based on adjustment on separate-bias Kalman filter [ 12 ], application of nonlinear filtering in alignment [ 13 ], initial attitude estimation of tactical grade inertial measurement [ 14 ], alignment with robust adaptive unscented Kalman filter [ 15 ], alignment based on a group of double direct spatial isometries [ 16 ], alignment with state-dependent extended Kalman filter [ 17 ], application of redundant technology in north-finding [ 18 ], two-position algorithm [ 19 , 20 ], multi-position algorithm [ 21 , 22 ], rotary-modulation algorithm [ 23 , 24 , 25 ], nonlinear filter model for large misalignment angle [ 26 ], transfer north-seeking algorithm [ 27 , 28 , 29 ], transfer alignment based on cubature Kalman filter (CKF) method [ 30 ], north-finding based on the neural network technology [ 31 , 32 ], transfer algorithm based on sensors network and estimation of wing flexure deformation [ 33 ], fast stationary initial alignment based on extended measurement information [ 34 ], accurate fine alignment based on adaptive extended Kalman filters [ 35 ], compact north-seeker technology [ 36 ], north-seeking based on the information fusion technology [ ...…”

Section: Introductionmentioning

confidence: 99%

“…Ref. [ 33 ] proposed a transfer alignment based on inertial sensors network. The accuracy of this transfer algorithm is very high.…”

Section: Introductionmentioning

confidence: 99%

A Fast North-Finding Algorithm on the Moving Pedestal Based on the Technology of Extended State Observer (ESO)

Bai

Zhang

et al. 2022

Sensors

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We propose a kind of fast and high-precision alignment algorithm based on the ESO technology. Firstly, in order to solve the problems of rapid, high-accuracy, and anti-interference alignment on the moving pedestal in the north-seeker, the ESO technology in control theory is introduced to improve the traditional Kalman fine-alignment model. This method includes two stages: the coarse alignment in the inertial frame and fine alignment based on the ESO technology. By utilizing the ESO technology, the convergence speed of the heading angle can be greatly accelerated. The advantages of this method are high-accuracy, fast-convergence, strong ability of anti-interference, and short time-cost (no need of KF recursive calculation). Then, the algorithm model, calculation process, and the setting initial-values of the filter are shown. Finally, taking the shipborne north-finder based on the FOG (fiber-optic gyroscope) as the investigated subject, the test on the moving ship is carried out. The results of first off-line simulation show that the misalignment angle of the heading angle of the proposed (traditional) method is ≤2.1′ (1.8′) after 5.5 (10) minutes of alignment. The results of second off-line simulation indicate that the misalignment angle of the heading angle of the proposed (traditional) method is ≤4.8′ (14.2′) after 5.5 (10) minutes of alignment. The simulations are based on the ship-running experimental data. The measurement precisions of Doppler velocity log (DVL) are different in these two experiments.

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The estimation of wing flexure deformation in transfer alignment based on inertial sensors network

Cited by 2 publications

References 21 publications

Experimental Research of Triple Inertial Navigation System Shearer Positioning

Experimental Research of Triple Inertial Navigation System Shearer Positioning

A Fast North-Finding Algorithm on the Moving Pedestal Based on the Technology of Extended State Observer (ESO)

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