Integration of Navigation Data

1995 ◽  
Vol 48 (1) ◽  
pp. 114-135 ◽  
Author(s):  
A. Svensson ◽  
J. Holst
Keyword(s):  
Measurement System ◽  
Navigation System ◽  
Measurement Errors ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Measuring Instruments ◽  
Extended Kalman Filtering ◽  
Satellite Navigation System ◽  
Navigation Data ◽  
System A

This article treats integration of navigation data from a variety of sensors in a submarine using extended Kalman filtering in order to improve the accuracy of position, velocity and heading estimates. The problem has been restricted to planar motion. The measurement system consists of an inertial navigation system, a gyro compass, a passive log, an active log and a satellite navigation system. These subsystems are briefly described and models for the measurement errors are given.Four different extended Kalman filters have been tested by computer simulations. The simulations distinctly show that the passive subsystems alone are insufficient to improve the estimate of the position obtained from the inertial navigation system. A log measuring the velocity relative to the ground or a position determining system are needed. The improvement depends on the accuracy of the measuring instruments, the extent of time the instrument can be used and which filter is being used. The most complex filter, which contains fourteen states, eight to describe the motion of the submarine and six to describe the measurement system, including a model of the inertial navigation system, works very well.

scholarly journals Multi-Instance Inertial Navigation System for Radar Terrain Imaging

2020 ◽  
Vol 12 (21) ◽  
pp. 3639
Author(s):  
Michal Labowski ◽  
Piotr Kaniewski
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Navigation Systems ◽  
Time Duration ◽  
Navigation Data ◽  
Positioning Errors ◽  
Measurement Session ◽  
Single Aperture ◽  
Gps System

Navigation systems used for the motion correction (MOCO) of radar terrain images have several limitations, including the maximum duration of the measurement session, the time duration of the synthetic aperture, and only focusing on minimizing long-term positioning errors of the radar host. To overcome these limitations, a novel, multi-instance inertial navigation system (MINS) has been proposed by the authors. In this approach, the classic inertial navigation system (INS), which works from the beginning to the end of the measurement session, was replaced by short INS instances. The initialization of each INS instance is performed using an INS/GPS system and is triggered by exceeding the positioning error of the currently operating instance. According to this procedure, both INS instances operate simultaneously. The parallel work of the instances is performed until the image line can be calculated using navigation data originating only from the new instance. The described mechanism aims to perform instance switching in a manner that does not disturb the initial phases of echo signals processed in a single aperture. The obtained results indicate that the proposed method improves the imaging quality compared to the methods using the classic INS or the INS/GPS system.

A Monocular Vision Measurement Algorithm Based on the Underwater Robot

2014 ◽  
Vol 532 ◽  
pp. 165-169 ◽  
Author(s):  
Tao Liu ◽  
Lei Wan ◽  
Xing Wei Liang
Keyword(s):  
Measurement System ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Mathematic Model ◽  
Monocular Vision ◽  
Underwater Robot ◽  
Visual Measurement ◽  
Vision Measurement ◽  
Measurement Algorithm

A monocular vision measurement system was proposed based on the underwater robot, which used a single camera as visual sensor and used inertial navigation system to measure position and attitude. In this paper, the processing of underwater target images and the parameter calibration algorithm for visual measurement system were discussed, and then the visual measurement mathematic model of underwater robot was derived using the pose information of the inertial navigation system. Vision measuring principle validation tests for underwater robot have been carried out to detect underwater targets. The experiments verify that the monocular vision measurement algorithm proposed for underwater robot is effective with a preferably accuracy.

Researching of the low-precision SINS research for an unmanned vehicle

2020 ◽  
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Adaptive Estimation ◽  
Inertial Navigation ◽  
Estimation Algorithm ◽  
Satellite Navigation ◽  
Accuracy Class ◽  
Unmanned Vehicle ◽  
Satellite Navigation System ◽  
Algorithmic Support

A small-sized inertial navigation system (SINS) Gyrolab GL VG 109 is researched. It is shown that this system has low accuracy; therefore it cannot be used to determine the parameters of an unmanned vehicle in an autonomous mode. Correction of the system from the satellite navigation system significantly increases the accuracy of determining the parameters of an unmanned vehicle, but only under conditions of stable signals from the satellite navigation system (SNS). The algorithmic support for the correction facility of the navigation system based on the scalar adaptive estimation algorithm and identification procedure is formed. The use of algorithmic correction of SINS from SNS using an estimation algorithm allows achieving an accuracy that corresponds to systems of the third accuracy class. Keywords inertial navigation system without platform; unmanned vehicle; correction; satellite navigation system; scalar estimation algorithm; scalar identification; analysis of accuracy

The Design of Vehicle Integrated Navigation System Based on FPGA

2012 ◽  
Vol 442 ◽  
pp. 441-445
Author(s):  
Yong Sen Wei
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Gps Data ◽  
Integrated Navigation ◽  
Good Balance ◽  
Integrated Navigation System ◽  
Navigation Data ◽  
Navigation Algorithms ◽  
The Cost

A GPS/inertial navigation system design scheme is introduced. Combination of DSP and FPGA is used on the navigation board, and micro inertial navigation measuring element --ADIS16405 is used to sample required navigation data. DSP mainly implements navigation calculating based on navigation data, and realizes different navigation algorithms; FPGA in the system plays centeral control role, and not only samples IMU and GPS data, but also synchronize IMU and GPS in the real time, and preprocess and packet the navigation data. This paper also introduces the design of the software on FPGA. Practice proves that the scheme is feasible, and achieves the good balance between the cost, reliability and efficiency.

scholarly journals Unified Registration Model for Both Stationary and Mobile 3D Radar Alignment

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Lei Chen ◽  
G. H. Wang ◽  
Ilir F. Progri
Keyword(s):  
Navigation System ◽  
Measurement Errors ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Radar Measurement ◽  
Radar Network ◽  
Radar Measurements ◽  
System Variables ◽  
Analytical Expressions

For mobile radar, offset biases and attitude biases influence radar measurements simultaneously. Attitude biases generated from the errors of the inertial navigation system (INS) of the platform can be converted into equivalent radar measurement errors by three analytical expressions (range, azimuth, and elevation, resp.). These expressions are unique and embody the dependences between the offset and attitude biases. The dependences indicate that all the attitude biases can be viewed as and merged into some kind of offset biases. Based on this, a unified registration model (URM) is proposed which only contains radar “offset biases” in the form of system variables in the registration equations, where, in fact, the “offset biases” contain the influences of the attitude biases. URM has the same form as the registration model of stationary radar network where no attitude biases exist. URM can compensate radar offset and attitude biases simultaneously and has minor computation burden compared with other registration models for mobile radar network.

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.

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.

GNSS/IMU integration algorithm experimental evaluation

2021 ◽  
pp. 52-64
Author(s):  
I.A. Nagin ◽  
A.Yu. Shatilov ◽  
T.A. Muhamedzyanov ◽  
Yu.M. Inchagov
Keyword(s):  
Navigation System ◽  
Experimental Evaluation ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Satellite Navigation ◽  
Integration Algorithm ◽  
Satellite Navigation System ◽  
Navigation Solution ◽  
Inertial Measuring Unit ◽  
Measuring Unit

To improve the reliability and accuracy of navigation solution, the integration of the satellite navigation receiver with the inertial navigation system is used. These systems have complementary characteristics. An important part of the combined systems is the integration algorithm, which largely determines the final characteristics. The synthesis of such an algorithm for velocity, attitude and the errors of the inertial measuring unit estimation has been carried out. The algorithm is implemented in the software of the prototype of the inertial-satellite navigation system. The results of the experimental evaluation of algorithm’s characteristics for automotive dynamics are shown.

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