scholarly journals SINS/CNS Nonlinear Integrated Navigation Algorithm for Hypersonic Vehicle

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Yong-jun Yu ◽  
Jin-fa Xu ◽  
Zhi Xiong
Keyword(s):  
Navigation System ◽  
Nonlinear Filtering ◽  
Inertial Navigation System ◽  
Hypersonic Vehicle ◽  
Measurement Information ◽  
Horizontal Position ◽  
Integrated Navigation ◽  
Navigation Algorithm ◽  
Celestial Navigation ◽  
Positioning Algorithm

Celestial Navigation System (CNS) has characteristics of accurate orientation and strong autonomy and has been widely used in Hypersonic Vehicle. Since the CNS location and orientation mainly depend upon the inertial reference that contains errors caused by gyro drifts and other error factors, traditional Strap-down Inertial Navigation System (SINS)/CNS positioning algorithm setting the position error between SINS and CNS as measurement is not effective. The model of altitude azimuth, platform error angles, and horizontal position is designed, and the SINS/CNS tightly integrated algorithm is designed, in which CNS altitude azimuth is set as measurement information. GPF (Gaussian particle filter) is introduced to solve the problem of nonlinear filtering. The results of simulation show that the precision of SINS/CNS algorithm which reaches 130 m using three stars is improved effectively.

A Design of MIMU/GPS Integrated Navigation System

2013 ◽  
Vol 278-280 ◽  
pp. 1719-1722 ◽  
Author(s):  
Xiao Yu Zhang ◽  
Chun Lei Song
Keyword(s):  
Navigation System ◽  
Inertial Measurement Unit ◽  
High Performance ◽  
Inertial Navigation System ◽  
Measurement Unit ◽  
Integrated Navigation ◽  
Test Results ◽  
Simulation Test ◽  
Integrated Navigation System ◽  
Navigation Algorithm

A new scheme of small integrated navigation system based on micro inertial measurement unit (MIMU), global position system (GPS) is presented. The characteristic of these sensors and the structure of system are introduced respectively. The TI high performance floating point DSP TMS320C6713B is used as core processor, which is designed to realize both the data collecting and the navigation calculating. According to the error models of inertial navigation system, an integrated navigation algorithm used Kalman filter is proposed to fuse the information from all of the sensors. The simulation test results show the feasibility of the system design.

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 Based on Grid Reference Frame for SINS/CNS Integrated Navigation System in the Polar Regions

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Song Lijun ◽  
Zhao Wanliang ◽  
Cheng Yuxiang ◽  
Chen Xiaozhen
Keyword(s):  
Reference Frame ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Polar Regions ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Celestial Navigation ◽  
Low Latitudes ◽  
And Performance

As the inertial navigation system cannot meet the precision requirements of global navigation in the special geographical environment of the Polar Regions, this paper presents Strapdown Inertial Navigation System (SINS)/Celestial Navigation System (CNS) integrated navigation system of airborne based on Grid Reference Frame (GRF) and the simulation is carried out. The result of simulation shows that the SINS/CNS integrated navigation system is superior to the single subsystem in precision and performance, which not only effectively inhibits the error caused by gyro drift but also corrects the navigation parameters of system without delay. Comparing the simulation in the middle and low latitudes and in the Polar Regions, the precision of SINS/CNS integrated navigation system is the same in the middle and low latitudes and in the Polar Regions.

scholarly journals SINS/Landmark Integrated Navigation Based on Landmark Attitude Determination

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2917
Author(s):  
Shuqing Xu ◽  
Haiyin Zhou ◽  
Jiongqi Wang ◽  
Zhangming He ◽  
Dayi Wang
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Attitude Determination ◽  
Feature Matching ◽  
Integrated Navigation ◽  
Basic Scheme ◽  
Integrated Navigation System ◽  
Celestial Navigation ◽  
Landmark Navigation ◽  
Navigation Method

Based on the situation that the traditional SINS (strapdown inertial navigation system)/CNS (celestial navigation system) integrated navigation system fails to realize all-day and all-weather navigation, this paper proposes a SINS/Landmark integrated navigation method based on landmark attitude determination to solve this problem. This integrated navigation system takes SINS as the basic scheme and uses landmark navigation to correct the error of SINS. The way of the attitude determination is to use the landmark information photographed by the landmark camera to complete feature matching. The principle of the landmark navigation and the process of attitude determination are discussed, and the feasibility of landmark attitude determination is analyzed, including the orthogonality of the attitude transform matrix, as well as the influences of the factors such as quantity and geometric position of landmarks. On this basis, the paper constructs the equations of the SINS/Landmark integrated navigation system, testifies the effectiveness of landmark attitude determination on the integrated navigation by Kalman filter, and improves the navigation precision of the system.

Research on outdoor AGV precise navigation based on BDS/INS data fusion

2021 ◽  
pp. 1-12
Author(s):  
Yongwei Tang ◽  
Huijuan Hao ◽  
Jun Zhou ◽  
Yuexiang Lin ◽  
Zhenzhen Dong
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Navigation System ◽  
Integrated Navigation ◽  
Complex Environments ◽  
Assisted Navigation ◽  
Precise Control ◽  
Bee Colony ◽  
Navigation Algorithm ◽  
Navigation Error

AGV (Automated Guided Vehicle) technology has attracted increasing attention. Precise control of AGV position and attitude information in complex operating environment is a key part of smart factories. With outdoor AGV as a platform, this study uses BDS/INS combined navigation system combining Beidou positioning system and inertial navigation system and takes the velocity and position difference between BDS and INS as a model. An integrated navigation method is proposed to improve bee colony algorithm and optimize the BP neural network-assisted Kalman filtering to achieve accurate positioning. Moreover, the optimization of BP neural network navigation using INS navigation, network-assisted navigation and bee colony algorithm is simulated. Results demonstrate that the integrated navigation algorithm has effectiveness and feasibility, and can solve the problems of BDS misalignment and large INS navigation error in complex environments.

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.

scholarly journals Correction Algorithm for the Navigation System of an Autonomous Unmanned Underwater Vehicle

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2365
Author(s):  
Danhe Chen ◽  
K. A. Neusypin ◽  
M. S. Selezneva
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Underwater Vehicle ◽  
Measurement Information ◽  
Nonlinear Controller ◽  
Unmanned Underwater Vehicle ◽  
Measuring Complex ◽  
Nonlinear Kalman Filter

More accurate navigation systems are always required for autonomous unmanned underwater vehicles (AUUV)s under various circumstances. In this paper, a measuring complex of a heavy unmanned underwater vehicle (UUV) was investigated. The measuring complex consists of an inertial navigation platform system, a Doppler lag (DL) and an estimation algorithm. During a relatively long-term voyage of an UUV without surfacing and correction from buoys and stationary stations, errors of the measuring complex will increase over time. The increase in errors is caused by an increase in the deviation angles of the gyro platform relative to the accompanying trihedron of the selected coordinate system. To reduce these angles, correction is used in the structure of the inertial navigation system (INS) using a linear regulator. To increase accuracy, it is proposed to take into account the nonlinear features of INS errors; an adaptive nonlinear Kalman filter and a nonlinear controller were used in the correction scheme. Considering that, a modified nonlinear Kalman filter and a regulator in the measuring complex are proposed to improve the accuracy of the measurement information, and modification of the nonlinear Kalman filter was performed through a genetic algorithm, in which the regulator was developed by the State Dependent Coefficient (SDC) method of the formulated model. Modeling combined with a semi-natural experiment with a real inertial navigation system for the UUV demonstrated the efficiency and effectiveness of the proposed algorithms.

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