Real-Time Implementation of GPS Aided Low-Cost Strapdown Inertial Navigation System

2010 ◽  
pp. 527-544 ◽  
Author(s):  
L. R. Sahawneh ◽  
M. A. Al-Jarrah ◽  
K. Assaleh ◽  
Mamoun F. Abdel-Hafez
2012 ◽  
Vol 182-183 ◽  
pp. 1090-1094
Author(s):  
Wei Gao ◽  
Lei Zhang

In inertial navigation system, gyro is used to measure the angular velocity of carrier relative to inertial space for achieve attitude matrix updated in real time. Gyro difficult to eliminate the error, results in strapdown inertial navigation system precision decrease with time. Star sensor is a high-precision attitude measuring instrument and don’t require any priori information, the attitude date can be provided by star sensor. Thus, gyro is simulated by star sensor in order to improve the precision of strapdown inertial navigation system.


Aiming at the real-time problems of signal acquisition, attitude calculation and data exchange of strapdown inertial navigation system, the data exchange between the core device of three-axis screw instrument and three-axis accelerometer sensor inertial unit (IMU) is analyzed. The RS-232 serial interface and can bus interface are adopted, which can not meet the requirements of high-speed sampling and real-time data transmission of each sensor. A new method based on FPGA dual port RAM and dual DSP is proposed Speed data access mode, through the main control CPU clock synchronization, can effectively solve the bottleneck problem of data communication between IMU attitude data and core equipment, and realize the rapid response ability of vehicle navigation system. Experiments and simulations show that the highest frequency attitude update rate of the method can reach 2000kHz, which can effectively solve the input and output data and navigation calculation ability, and improve the maneuverability of the carrier.


2017 ◽  
Vol 70 (4) ◽  
pp. 907-926 ◽  
Author(s):  
Milad Bayat ◽  
MA Amiri Atashgah

This paper offers an algorithm for enhancement of positioning accuracy of a quad-rotor flying robot, based on jerk and jounce of motion. The suggested method utilises the first and second numerical derivatives of the vehicle's acceleration and augments the mathematical model in the estimation process. For this purpose, the Kalman Filter (KF) is implemented for integration of a Strapdown Inertial Navigation System (SINS) and Global Navigation Satellite System (GNSS). The required data are collected from a low-cost/quality Micro Electromechanical Sensors (MEMS) during an assisted flight. For increasing the precision and accuracy of the collected data, all instruments including accelerometers, gyroscopes and magnetometers are calibrated before the experiments. Moreover, to reduce and limit the measurement noises of the MEMS sensor, a low-pass filter is applied; this is while sensors in the autopilot are affected by high levels of noise and drift, which makes them inappropriate for accurate positioning. The experimental results exhibit an improvement in positioning and altitude sensing through augmentation of the loosely coupled SINS/GNSS navigation method.


2012 ◽  
Vol 433-440 ◽  
pp. 3746-3752 ◽  
Author(s):  
Jian Hui Tian ◽  
Jia Sheng Zhao ◽  
Yan Cao ◽  
Wei Wang ◽  
Wei Xu ◽  
...  

To improve the hit probability and damage probability of guided projectile, made the strapdown inertial navigation technology better application in guided projectile, based on the feature of short range and short flying time of guided projectile, a simplification model of SINS (strapdown inertial navigation system) was proposed. The optimal 3-subsample rotation vector simulation platform was founded based on the tradition method, and this system was also checked by simulation using three-channel databases from simulator testing. The results show that this system not only can satisfy the requirement of real-time and precision, but also can improve the relative error to 10-6. The influence of direction draft to the guided projectile is also reduced.


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