scholarly journals Inertial Navigation Position and Orientation Estimation with Occasional Galileo Satellite Position Fixes and Stereo Camera Measurements

2012 ◽  
Vol 19 (2) ◽  
pp. 131-153
Author(s):  
Ranjan Vepa ◽  
Kanella Petrakou
Keyword(s):  
Navigation System ◽  
Carrier Phase ◽  
Inertial Navigation System ◽  
Unscented Kalman Filter ◽  
Inertial Navigation ◽  
Navigation Systems ◽  
Initial Alignment ◽  
Stereo Camera ◽  
Satellite Navigation System ◽  
Representative Points

Abstract In this paper an adaptive unscented Kalman filter based mixing filter is used to integrate kinematic satellite aided inertial navigation system with vision based measurements of five representative points on a runway in a modern receiver that incorporates carrier phase smoothing and ambiguity resolution. Using high resolution multiple stereo camera based measurements of five points on the runway, in addition to a set of typical pseudo-range estimates that can be obtained from a satellite navigation system such GPS or GNSS equipped with a carrier phase receiver, the feasibility of generating high precision estimates of the typical outputs from an inertial navigation system is demonstrated. The methodology may be developed as a stand-alone system or employed in conjunction with a traditional strapped down inertial navigation systems for purposes of initial alignment. Moreover the feasibility of employing adaptive mixing was explored as it facilitates the possibility of using the system for developing a vision based automatic landing controller.

High-Precision Kinematic Satellite and Doppler Aided Inertial Navigation System

2010 ◽  
Vol 64 (1) ◽  
pp. 91-108 ◽  
Author(s):  
Ranjan Vepa ◽  
Amzari Zhahir
Keyword(s):  
High Precision ◽  
Navigation System ◽  
Carrier Phase ◽  
Inertial Navigation System ◽  
Unscented Kalman Filter ◽  
Inertial Navigation ◽  
Satellite Navigation ◽  
Initial Alignment ◽  
Phase Measurements ◽  
Satellite Navigation System

In this paper an adaptive unscented Kalman filter based mixing filter is used to develop a high-precision kinematic satellite aided inertial navigation system with a modern receiver that incorporates carrier phase smoothing and ambiguity resolution. Using carrier phase measurements with multiple antennas, in addition to a set of typical pseudo-range estimates that can be obtained from a satellite navigation system such as GPS or GLONASS, the feasibility of generating high precision estimates of the typical outputs from an inertial navigation system is demonstrated. The methodology may be developed as a stand-alone system or employed in conjunction with a traditional strapped down inertial navigation system for purposes of initial alignment. Moreover the feasibility of employing adaptive mixing facilitates the possibility of using the system in an interoperable fashion with satellite navigation measurements.

Initial Alignment of a Moving Inertial Navigation System

1960 ◽  
Vol 13 (3) ◽  
pp. 301-315
Author(s):  
Richard B. Seeley ◽  
Roy Dale Cole
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Local Level ◽  
Inertial Navigation ◽  
Navigation Systems ◽  
Velocity Measurements ◽  
Initial Alignment ◽  
Inertial Navigation Systems ◽  
Error Sources ◽  
China Lake

This paper describes and discusses some of the techniques by which a moving inertial platform may be aligned by using external velocity measurements and also presents some of the major problems and error sources affecting such alignment. It is based upon the results of a 3-year study, of inertial and doppler-inertial navigation at the Naval Ordnance Test Station, China Lake, California, and, in general, applies to inertial navigation systems which erect to either the local level or the mass-attraction vertical. Although rudimentary derivations are made of the alignment techniques, the paper is largely nonmathematical for ease of reading. Emphasis is placed upon the major errors affecting the alignment. This paper describes and discusses some of the techniques by which a moving inertial platform may be aligned by using external velocity measurements and also presents some of the major problems and error sources affecting such alignment. It is based upon the results of a 3-year study, of inertial and doppler-inertial navigation at the Naval Ordnance Test Station, China Lake, California, and, in general, applies to inertial navigation systems which erect to either the local level or the mass-attraction vertical. Although rudimentary derivations are made of the alignment techniques, the paper is largely nonmathematical for ease of reading. Emphasis is placed upon the major errors affecting the alignment.

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

2020 ◽  
pp. 014233122093429 ◽  
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.

An Improved and Efficient Algorithm for SINS/GPS/Doppler Integrated Navigation Systems

2012 ◽  
Vol 245 ◽  
pp. 323-329 ◽  
Author(s):  
Muhammad Ushaq ◽  
Jian Cheng Fang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Sensor ◽  
Inertial Navigation ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Efficient Manner ◽  
Position Errors

Inertial navigation systems exhibit position errors that tend to grow with time in an unbounded mode. This degradation is due, in part, to errors in the initialization of the inertial measurement unit and inertial sensor imperfections such as accelerometer biases and gyroscope drifts. Mitigation to this growth and bounding the errors is to update the inertial navigation system periodically with external position (and/or velocity, attitude) fixes. The synergistic effect is obtained through external measurements updating the inertial navigation system using Kalman filter algorithm. It is a natural requirement that the inertial data and data from the external aids be combined in an optimal and efficient manner. In this paper an efficient method for integration of Strapdown Inertia Navigation System (SINS), Global Positioning System (GPS) and Doppler radar is presented using a centralized linear Kalman filter by treating vector measurements with uncorrelated errors as scalars. Two main advantages have been obtained with this improved scheme. First is the reduced computation time as the number of arithmetic computation required for processing a vector as successive scalar measurements is significantly less than the corresponding number of operations for vector measurement processing. Second advantage is the improved numerical accuracy as avoiding matrix inversion in the implementation of covariance equations improves the robustness of the covariance computations against round off errors.

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