Study on tightly-coupled GPS/SINS integrated navigation system by using software GPS receiver

2011 ◽  
Author(s):  
Xiyuan Chen ◽  
Jing Yu ◽  
Mingwu Gu
Keyword(s):  
Navigation System ◽  
Integrated Navigation ◽  
Gps Receiver ◽  
Integrated Navigation System ◽  
Tightly Coupled

scholarly journals SINS/BDS Tightly-Coupled Integrated Navigation Algorithm for Hypersonic Vehicle

2021 ◽  
Author(s):  
kai chen ◽  
Sen-sen PEI ◽  
Cheng-zhi ZENG ◽  
Gang DING
Keyword(s):  
Navigation System ◽  
Maximum Velocity ◽  
Field Tests ◽  
Hypersonic Vehicle ◽  
Integrated Navigation ◽  
State Equations ◽  
Integrated Navigation System ◽  
Near Space ◽  
Navigation Algorithm ◽  
Tightly Coupled

Abstract A tightly-coupled integrated navigation system (TCINS) for hypersonic vehicles is proposed when the satellite signals are disturbed. Firstly, the architecture of the integrated navigation system for the hypersonic vehicle is introduced. This system applies fiber SINS, BeiDou satellite receiver (BDS) and SOPC missile-born computer. Subsequently, the SINS mechanization for hypersonic vehicle is presented. The J2 model is employed for the normal gravity of the near space. An algorithm for updating the attitude, velocity and position is designed. State equations and measurement equations of SINS/BDS tightly-coupled integrated navigation for hypersonic vehicle are given, and a scheme of validity for satellite data is designed. Finally, the SINS/BDS tightly-coupled vehicle field tests and hardware-in-the-loop (HWIL) simulation tests are carried out. The vehicle field test and HWIL simulation results show that the heading angle error of tightly-coupled integrated navigation is within 0.2°, the pitch and roll angle errors are within 0.05°, the maximum velocity error is 0.3m/s, and the maximum position error is 10m.

scholarly journals Design and Simulation of the Integrated Navigation System based on Extended Kalman Filter

Open Physics ◽  
2017 ◽  
Vol 15 (1) ◽  
pp. 182-187 ◽  
Author(s):  
Weidong Zhou ◽  
Jiaxin Hou ◽  
Lu Liu ◽  
Tian Sun ◽  
Jing Liu
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Navigation System ◽  
Inertial Sensors ◽  
Integrated Navigation ◽  
Gps Receiver ◽  
Noisy Environment ◽  
Integrated Navigation System ◽  
Error Covariance ◽  
Time Update

AbstractThe integrated navigation system is used to estimate the position, velocity, and attitude of a vehicle with the output of inertial sensors. This paper concentrates on the problem of the INS/GPS integrated navigation system design and simulation. The structure of the INS/GPS integrated navigation system is made up of four parts: 1) GPS receiver, 2) Inertial Navigation System, 3) Extended Kalman filter, and 4) Integrated navigation scheme. Afterwards, we illustrate how to simulate the integrated navigation system with the extended Kalman filter by measuring position, velocity and attitude. Particularly, the extended Kalman filter can estimate states of the nonlinear system in the noisy environment. In extended Kalman filter, the estimation of the state vector and the error covariance matrix are computed by steps: 1) time update and 2) measurement update. Finally, the simulation process is implemented by Matlab, and simulation results prove that the error rate of statement measuring is lower when applying the extended Kalman filter in the INS/GPS integrated navigation system.

scholarly journals A LiDAR-Aided Indoor Navigation System for UGVs

2014 ◽  
Vol 68 (2) ◽  
pp. 253-273 ◽  
Author(s):  
Shifei Liu ◽  
Mohamed Maher Atia ◽  
Tashfeen B. Karamat ◽  
Aboelmagd Noureldin
Keyword(s):  
Navigation System ◽  
Error Model ◽  
Indoor Navigation ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Model Errors ◽  
Integrated Navigation System ◽  
Tightly Coupled ◽  
Indoor Navigation System ◽  
Sensor Errors

Autonomous Unmanned Ground Vehicles (UGVs) require a reliable navigation system that works in all environments. However, indoor navigation remains a challenge because the existing satellite-based navigation systems such as the Global Positioning System (GPS) are mostly unavailable indoors. In this paper, a tightly-coupled integrated navigation system that integrates two dimensional (2D) Light Detection and Ranging (LiDAR), Inertial Navigation System (INS), and odometry is introduced. An efficient LiDAR-based line features detection/tracking algorithm is proposed to estimate the relative changes in orientation and displacement of the vehicle. Furthermore, an error model of INS/odometry system is derived. LiDAR-estimated orientation/position changes are fused by an Extended Kalman Filter (EKF) with those predicted by INS/odometry using the developed error model. Errors estimated by EKF are used to correct the position and orientation of the vehicle and to compensate for sensor errors. The proposed system is verified through simulation and real experiment on an UGV equipped with LiDAR, MEMS-based IMU, and encoder. Both simulation and experimental results showed that sensor errors are accurately estimated and the drifts of INS are significantly reduced leading to navigation performance of sub-metre accuracy.

A Ship GPS/DR Integrated Navigation System

2012 ◽  
Vol 591-593 ◽  
pp. 1818-1821
Author(s):  
Yuan Liang Zhang
Keyword(s):  
Data Fusion ◽  
Navigation System ◽  
Global Economy ◽  
Dead Reckoning ◽  
Fusion Method ◽  
Integrated Navigation ◽  
Gps Receiver ◽  
Integrated Navigation System ◽  
Ship Navigation ◽  
Navigation Information

The development of the global economy stimulates the exploitation of the ocean. A precise and stable ship navigation system is very important for people to explore the ocean. Dead reckoning (DR) system is a frequently used navigation system for sailing in the ocean. It can provide precise short term navigation information but the error of DR system can accumulate over time without limitation. GPS can be used for localization and navigation in outside environment. Although the SA policy was removed the accuracy of GPS for civilian use is still big. But the errors of GPS are bounded. Since the complementarity of DR and GPS system the integrated GPS/DR system can provide good navigation results. In this paper a new Kalman filter based DR/GPS data fusion method is proposed. This method is designed based on the characteristic of the GPS receiver. By using this data fusion method the cheap GPS receiver can cooperate with DR system to provide precise navigation information for ships. Simulation is conducted to validate the proposed fusion method. The good result shows the potential of this fusion method for the ship navigation.

Design and Implementation of the Tightly-Coupled SINS / GPS Integrated Navigation System Based on FPGA for Target Missile

2013 ◽  
Vol 313-314 ◽  
pp. 287-290 ◽  
Author(s):  
Jing Jie Guo ◽  
Xiao Feng Cai ◽  
Chao He
Keyword(s):  
Navigation System ◽  
Integrated Control ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Nios Ii ◽  
Navigation Data ◽  
Design And Implementation ◽  
Control Computer ◽  
Tightly Coupled ◽  
Fpga Chip

A novel architecture of tightly-coupled SINS/ GPS integrated navigation system based on FPGA for target missile is proposed in this paper.The whole system is built on a single single FPGA chip containing a Nios II soft-core processor. In addition, the embedded real-time operating system μC/OS-IIis transplanted to the Nios II processor for managing each module in the system. The system can still provide the high-precision navigation data to integrated control computer of target missile when the number of available satellites is less than 4 by means of processing the pseudorange and pseudorange rate seprately. Therefore, the system has the strong application significance in terms of reducing the route shortcut of target missile.

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