Robust adaptive Kalman filter for strapdown inertial navigation system dynamic alignment

To improve the navigation precision of autonomous underwater vehicles, a terrain-aided strapdown inertial navigation based on Improved Unscented Kalman Filter (IUKF) is proposed in this paper. The characteristics of strapdown inertial navigation system and terrain-aided navigation system are described in this paper, and improved UKF method is applied to the information fusion. Simulation experiments of novel integrated navigation system proposed in the paper were carried out comparing to the traditional Kalman filtering methods. The experiment results suggest that the IUKF method is able to greatly improve the long-time navigation precision, relative to the traditional information fusion method.

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Computer simulation of control contour of unmanned aviation complex to provide robustness and controllability

Proceedings of the National Academy of Sciences of Belarus Physical-Technical Series ◽

10.29235/1561-8358-2018-63-3-368-380 ◽

2018 ◽

Vol 63 (3) ◽

pp. 368-380 ◽

Cited By ~ 1

Author(s):

Y. F. Yatsyna ◽

Y. V. Gridnev

Keyword(s):

Computer Simulation ◽

Kalman Filter ◽

Control System ◽

Navigation System ◽

Inertial Navigation System ◽

Inertial Navigation ◽

Strapdown Inertial Navigation System ◽

Feedback Systems ◽

Standard Atmosphere ◽

Strapdown Inertial Navigation

The article describes an approach to ensuring stability and controllability of unmanned aerial vehicle (UAV) with unknown aerodynamic characteristics by computer simulation of the airplane flight along a given route in the meteorological standard atmosphere. This computer model takes into account the programmed flight of an unmanned aerial vehicle in the meteorological atmosphere along a given route with waypoints. For this purpose the model incorporates 5 feedback systems (FS) with autopilot (AP) that ensure the stability and controllability of an airplane. Besides the autopilot and the airplane glider the control system encompasses the Kalman filter and a strapdown inertial navigation system. The appropriate structure and parameters of the control system of the model were chosen on the basis of practical technical solutions of the de veloped UAVs. The closed control systems of the model are developed according to the equations considering generation of aerodynamic forces and moments, a model of the standard atmosphere, the routing scheme and the feedback system with autopilot. The stability and controllability of the model were analyzed according to the theory of feedback systems with the graphic plotting of Bode magnitude plot and Bode phase plot. With a view to the assessment of dynamic and fluctuation errors of the control systems the model is represented by stochastic differential control system with the Kalman filter and the strapdown inertial navigation system in quaternions. The results of the computer simulation showed that the Kalman filter estimates the measured parameters with the noise reduction under 10 dB. The strapdown inertial navigation system influences the general dynamics of the control system during the assessment of its stability and controllability. Changing the band of the control system at the expense of external perturbations affecting the plane can lead to instability, and in order to avoid it the robust autopilot is recommended.

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A fast alignment of marine strapdown inertial navigation system based on adaptive unscented Kalman Filter

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331220934293 ◽

2020 ◽

pp. 014233122093429 ◽

Cited By ~ 1

Author(s):

Hossein Rahimi ◽

Amir Ali Nikkhah ◽

Kaveh Hooshmandi

Keyword(s):

Kalman Filter ◽

Navigation System ◽

Inertial Navigation System ◽

Unscented Kalman Filter ◽

Inertial Navigation ◽

Strapdown Inertial Navigation System ◽

Initial Alignment ◽

External Perturbations ◽

Adaptive Unscented Kalman Filter ◽

Strapdown Inertial Navigation

This study has presented an efficient adaptive unscented Kalman filter (AUKF) with the new measurement model for the strapdown inertial navigation system (SINS) to improve the initial alignment under the marine mooring conditions. Conventional methods of the accurate alignment in the ship’s SINS usually fail to succeed within an acceptable period of time due to the components of external perturbations caused by the movement of sea waves and wind waves. To speed up convergence, AUKF takes into account the impact of the dynamic acceleration on the filter and its gain adaptively tuned by considering the dynamic scale sensed by accelerometers. This approach considerably improved the corrections of the current residual error on the SINS and decreased the influence due to the external perturbations caused by the ship’s movement. Initial alignment algorithm based on AUKF is designed for large misalignment angles and verified by experimental data. The experimental test results show that the proposed algorithm enhanced the convergence speed of SINS initial alignment compared with some state-of-the-art existing approaches.

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Integration of a Multi-Camera Vision System and Strapdown Inertial Navigation System (SDINS) with a Modified Kalman Filter

Sensors ◽

10.3390/s100605378 ◽

2010 ◽

Vol 10 (6) ◽

pp. 5378-5394 ◽

Cited By ~ 17

Author(s):

Neda Parnian ◽

Farid Golnaraghi

Keyword(s):

Kalman Filter ◽

Navigation System ◽

Inertial Navigation System ◽

Vision System ◽

Inertial Navigation ◽

Strapdown Inertial Navigation System ◽

Modified Kalman Filter ◽

Strapdown Inertial Navigation

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Strapdown inertial navigation system alignment based on marginalised unscented Kalman filter

IET Science Measurement & Technology ◽

10.1049/iet-smt.2012.0071 ◽

2013 ◽

Vol 7 (2) ◽

pp. 128-138 ◽

Cited By ~ 48

Author(s):

Lubin Chang ◽

Fangjun Qin ◽

Baiqing Hu ◽

An Li

Keyword(s):

Kalman Filter ◽

Navigation System ◽

Inertial Navigation System ◽

Unscented Kalman Filter ◽

Inertial Navigation ◽

Strapdown Inertial Navigation System ◽

Strapdown Inertial Navigation

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Kalman Filter Design for Initial Precision Alignment of a Strapdown Inertial Navigation System on a Rocking Base

Journal of Navigation ◽

10.1017/s0373463314000575 ◽

2014 ◽

Vol 68 (1) ◽

pp. 184-195 ◽

Cited By ~ 13

Author(s):

Hanzhou Li ◽

Quan Pan ◽

Xiaoxu Wang ◽

Xiangjun Jiang ◽

Lin Deng

Keyword(s):

Kalman Filter ◽

Navigation System ◽

Inertial Navigation System ◽

Filter Design ◽

Inertial Navigation ◽

Strapdown Inertial Navigation System ◽

Alignment Algorithm ◽

Attitude Tracking ◽

Alignment Process ◽

Strapdown Inertial Navigation

In this paper, a conventional Strapdown Inertial Navigation System (SINS) alignment method on a disturbed base is analysed. A novel method with an attitude tracking idea is proposed for the rocking base alignment. It is considered in this method that the alignment algorithm should track the rocking base attitude real changes in the alignment process, but not excessively restrain disturbance. According to this idea, a rapid alignment algorithm is devised for the rocking base. In the algorithm, coarse alignment is carried out within 30 s in the inertial frame with alignment precision less than 2°, which meets Kalman filter linearization conditions well. Then a Kalman filter with ten state vectors and four measurement vectors is applied for the fine alignment to improve the capability of the algorithm in tracking the vehicle attitude. A turntable rotation experiment is carried out to validate the capability of the fine algorithm in tracing the large magnitude change during alignment. It is shown that the repeated alignment precision is about 0·04° by the alignment experiment on a rocking vehicle, with alignment time of 180 s. The Laser Strapdown Inertial Navigation System (LINS) ground navigation experiment suggests that the algorithm proposed by this paper can be satisfied without the need of high precision SINS alignment.

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