scholarly journals Complexed navigation system based on a strapdown inertial navigation system and correlation meter speed and drift

2015 ◽  
pp. 74-81
Author(s):  
Yu. A. Ivanov
Keyword(s):  
Correlation Functions ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Moving Average ◽  
Inertial Navigation ◽  
Correlation Method ◽  
Strapdown Inertial Navigation System ◽  
Doppler Velocity ◽  
Speed Up ◽  
Strapdown Inertial Navigation

Integration of data and correlation meter speed strapdown inertial navigation system built by analogy with the Doppler velocity and drift, results in strong disturbances in the control loop movement of the aircraft in the horizontal plane. A method of aggregation, which takes into account the correlation method for measuring the speed, is the need to calculate the long periods of correlation functions of signals received by antennas spaced. This corrected the error strapdown inertial navigation system to speed up, speed and coordinates, eliminating the need for a moving average of the correlation functions and information retrieval speed navigation in every cycle.

On In Situ Calibration of SINS and Doppler Dead Reckoning Navigation System

2012 ◽  
Vol 479-481 ◽  
pp. 2610-2615
Author(s):  
Kai Yao ◽  
Qi Dan Zhu ◽  
Bo Zhang
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Dead Reckoning ◽  
Strapdown Inertial Navigation System ◽  
Doppler Velocity ◽  
Navigation Algorithm ◽  
Calibration Algorithm ◽  
Strapdown Inertial Navigation

This paper addresses a practical problem arising in the calibration of bottom-lock doppler velocity log for the navigation of surface ships. Firstly, a dead reckoning navigation algorithm and briefly error analyze are proposed. Then, employing ship’s true trajectory and calculated trajectory, the rotational alignment offset between a bottom-lock doppler velocity log and a strapdown inertial navigation system as well as the scale factor error of the doppler velocity log can be experimentally determined using sensors commonly deployed with a vehicle in the field. It requires velocity values from the vehicle's doppler log and strapdown inertial navigation system, and absolute vehicle position fixes from a GPS receiver. Lake experiment results show that the calibration algorithm can calibrate the error parameters effectively, thus the position error decreases significantly after compensating the error parameters.

Observability and Estimation Error Analysis of the Initial Fine Alignment Filter for Nonleveling Strapdown Inertial Navigation System

2012 ◽  
Vol 135 (2) ◽  
Author(s):  
Seong Yun Cho ◽  
Hyung Keun Lee ◽  
Hung Kyu Lee
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
The State ◽  
State Model ◽  
Low Grade ◽  
State Variables ◽  
Estimation Errors ◽  
Strapdown Inertial Navigation

In this paper, performance of the initial fine alignment for the stationary nonleveling strapdown inertial navigation system (SDINS) containing low-grade gyros is analyzed. First, the observability is analyzed by conducting a rank test of an observability matrix and by investigating the normalized error covariance of the extended Kalman filter based on the ten-state model. The results show that the accelerometer biases on horizontal axes are unobservable. Second, the steady-state estimation errors of the state variables are derived using the observability equation. It is verified that the estimates of the state variables have errors due to the unobservable state variables and nonleveling attitude angles of a vehicle containing the SDINS. Especially, this paper shows that the larger the attitude angles of the vehicle are, the greater the estimation errors are. Finally, it is shown that the performance of the eight-state model excluding the two unobservable state variables is better than that of the ten-state model in the fine alignment by a Monte Carlo simulation.

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