scholarly journals One approach to the integration of inertial and visual navigation systems

2005 ◽  
Vol 18 (3) ◽  
pp. 479-491
Author(s):  
Stevica Graovac
Keyword(s):  
Inertial Sensors ◽  
Angular Position ◽  
Visual Navigation ◽  
The Body ◽  
Moving Object ◽  
Coordinate Frame ◽  
Simultaneous Estimation ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Integrated Navigation System

The algorithm of simultaneous estimation of motion parameters and scene structure using the integrated navigation system consisting from inertial sensors (three rate gyros and three accelerometers) and TV camera has been presented. All mentioned sensors are rigidly fixed to the body of a moving object. It is assumed that the inertial sensors are characterized by constant biases. The recognizable landmarks existing in the scene on known locations in the reference coordinate frame are assumed also. It is enabled by parallel processing of information in two independent navigation systems that they may correct each other, in order to estimate moving object?s linear and angular position relative to the landmark as well as it?s linear and angular velocities in an optimal fashion.

Studies of the integrated navigation system correction in the absence of a satellite signal

2021 ◽  
Author(s):  
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Operation Mode ◽  
Satellite System ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Correction Signal ◽  
Satellite Signal ◽  
Navigation Information

The schemes of navigation systems correction are considered. The operation mode of the aircraft during navigation is analyzed. An adaptive modification of the linear Kalman filter is used to correct the navigation information. An algorithm for predicting a correction signal based on a neural network in the event of a loss of a SNS correction signal is formed. Experimental results show the effectiveness of the algorithm. Keywords aircraft; inertial navigation system; satellite system; Kalman filter; neural networks; genetic algorithm

scholarly journals Multi-Radio Integrated Navigation System M&S Software Design for GNSS Backup under Navigation Warfare

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 188 ◽  
Author(s):  
Heyone Kim ◽  
Junhak Lee ◽  
Sang Heon Oh ◽  
Hyoungmin So ◽  
Dong-Hwan Hwang
Keyword(s):  
Software Design ◽  
Navigation System ◽  
Design Method ◽  
Satellite System ◽  
Navigation Satellite ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Very High Frequency ◽  
Integrated Navigation System ◽  
Function Modules

To avoid degradation of navigation performance in the navigation warfare environment, the multi-radio integrated navigation system can be used, in which all available radio navigation systems are integrated to back up Global Navigation Satellite System (GNSS) when the GNSS is not available. Before real-time multi-radio integrated navigation systems are deployed, time and cost can be saved when the modeling and simulation (M&S) software is used in the performance evaluation. When the multi-radio integrated navigation system M&S is comprised of independent function modules, it is easy to modify and/or to replace the function modules. In this paper, the M&S software design method was proposed for multi-radio integrated navigation systems as a GNSS backup under the navigation warfare. The M&S software in the proposed design method consists of a message broker and function modules. All the messages were transferred through the message broker in order to be exchanged between the function modules. The function modules in the M&S software were independently operated due to the message broker. A message broker-based M&S software was designed for a multi-radio integrated navigation system. In order to show the feasibility of the proposed design method, the M&S software was implemented for Global Positioning System (GPS), Korean Navigation Satellite System (KNSS), enhanced Long range navigation (eLoran), Loran-C, and Distance Measuring Equipment/Very high-frequency Omnidirectional Radio range (DME/VOR). The usefulness of the proposed design method was shown by checking the accuracy and availability of the GPS only navigation and the multi-radio integrated navigation system under the attack of jamming to GPS.

scholarly journals The Availability Of Automatic Identification System (AIS) Based On Latency Position Reports In The Gulf Of Gdansk

2014 ◽  
Vol 21 (1) ◽  
pp. 59-74 ◽  
Author(s):  
Krzysztof Jaskólski
Keyword(s):  
Global Scale ◽  
Digital Data ◽  
Automatic Identification ◽  
Identification System ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Gulf Of Gdańsk ◽  
Integrated Navigation System ◽  
Navigation Data ◽  
Gulf Of Gdansk

AbstractThe problem of determining geographic position considered only in terms of measurement error, seems to be solved on a global scale. In view of the above, from the nineties, the operational characteristics of radio-navigation systems are equally important. The integrated navigation system operate in a multi-sensor environment and it is important to determinate a temporal validity of data to make it usable in data fusion process. In the age of digital data processing, the requirements for continuity, availability, reliability and integrity information are already grown. This article analyses the problem of time stamp discrepancies of dynamic position reports. For this purpose, the statistical summary of Latency Position Reports has been presented. The navigation data recordings were conducted during 30 days of March 2014 from 19 vessels located in area of Gulf of Gdansk. On the base of Latency Position Reports it is possible to designate the availability of AIS system.

scholarly journals Multiple Model Adaptive Rank Estimation for Integrated Navigation During Mars Entry

2016 ◽  
Vol 70 (2) ◽  
pp. 291-308 ◽  
Author(s):  
Qiang Xiao ◽  
Huimin Fu ◽  
Zhihua Wang ◽  
Yongbo Zhang
Keyword(s):  
Navigation System ◽  
Uncertain System ◽  
Measurement Unit ◽  
Filter Method ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Multiple Model ◽  
Integrated Navigation System ◽  
Rank Estimation ◽  
Three Degree Of Freedom

Accurate navigation systems are required for future pinpoint Mars landing missions. A radio ranging augmented Inertial Measurement Unit (IMU) integrated navigation system concept is considered for the Mars entry navigation. The uncertain system parameters associated with the Three Degree-Of-Freedom (3-DOF) dynamic model, and the measurement systematic errors are considered. In order to improve entry navigation accuracy, this paper presents the Multiple Model Adaptive Rank Estimation (MMARE) filter of radio beacons/IMU integrated navigation system. 3-DOF simulation results show that the performances of the proposed navigation filter method, 70·39 m estimated altitude error and 15·74 m/s estimated velocity error, fulfill the need of future pinpoint Mars landing missions.

Integrated Navigation System Safety Assessment Methodology

2000 ◽  
Vol 53 (3) ◽  
pp. 425-435
Author(s):  
A. Raffetti ◽  
F. Marangon ◽  
F. Zuccarelli
Keyword(s):  
Risk Assessment ◽  
Navigation System ◽  
Safety Assessment ◽  
Hazard Identification ◽  
Navigation Systems ◽  
Assessment Methodology ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Industrial Sectors ◽  
Formal Safety Assessment

This paper was first presented at the NAV99/ILA28 Conference on ‘Loran-C, Satellite and Integrated Systems for the 21st Century’ held at Church House, Westminster, London from 1–3 November 1999.The introduction of modern navigation systems highlights the need for efficient tools to assess the possible impact of these systems on the safety levels currently associated with the operation of a ship. In recent years this has led to investigation of the advanced safety/risk assessment techniques already applied in other industrial sectors, with encouraging results. The scope of this paper is to show a quantified safety assessment methodology that can be applied while designing or retrofitting navigation systems. The methodology adopted is the result of the review of the IMO Formal Safety Assessment (FSA) technique and comprises the development of a functional analysis, a hazard identification analysis and a risk assessment. The paper provides details on a specific application of this model to an integrated navigation system. This application is included in the work performed under the ATOMOS II research project, partly funded by the DGVII Directorate of the European Commission within the 4th Framework Programme in the field of Maritime Transport.

Studies on an Integrated Navigation Method on the Basis of Adaptive Neuro-Fuzzy Inference System

2012 ◽  
Vol 433-440 ◽  
pp. 4065-4070
Author(s):  
Qiang Gao ◽  
Shan Jin ◽  
Tie Liu Wang
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Integrated System ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Inference System ◽  
Integrated Navigation System ◽  
Gps Satellites ◽  
Neuro Fuzzy ◽  
Range Rate

The GPS / INS integrated navigation system performance will significantly decrease during GPS outages. In this paper, we study an new integrated navigation algorithm based on Adaptive Neural- fuzzy Inference System (ANFIS). The algorithm adopted Kalman filter with pseudo-range and pseudo-range rate observations when the number of GPS satellites was not less 4. Otherwise, ANFIS was used to estimate the navigation errors and restrain the increasing INS errors to achieve integrated navigation. The new algorithm can improve the performance of integrated system effectively and enhance the horizontal position accuracy than traditional tight integration algorithms. Especially, the method is applicable to the complex work environment of navigation systems of ships.

Federated Particle Filter Technology Based on JIDS/SINS/GPS Integrated Navigation System

2013 ◽  
Vol 347-350 ◽  
pp. 1544-1548
Author(s):  
Zi Yu Li ◽  
Yan Liu ◽  
Ping Zhu ◽  
Cheng Ying
Keyword(s):  
Kalman Filter ◽  
Particle Filter ◽  
Navigation System ◽  
Integrated System ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Fusion Algorithm ◽  
Integrated Navigation System ◽  
Non Linear ◽  
Federated Kalman Filter

In multi-sensor integrated navigation systems, when sub-systems are non-linear and with Gaussian noise, the federated Kalman filter commonly used generates large error or even failure when estimating the global fusion state. This paper, taking JIDS/SINS/GPS integrated navigation system as example, proposes a federated particle filter technology to solve problems above. This technology, combining the particle filter with the federated Kalman filter, can be applied to non-linear non-Gaussian integrated system. It is proved effective in information fusion algorithm by simulated application, where the navigation information gets well fused.

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.

scholarly journals A Low-Cost Method of Improving the GNSS/SINS Integrated Navigation System Using Multiple Receivers

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1079 ◽  
Author(s):  
Di Liu ◽  
Hengjun Wang ◽  
Qingyuan Xia ◽  
Changhui Jiang
Keyword(s):  
Navigation System ◽  
Low Cost ◽  
Field Tests ◽  
Measurement Unit ◽  
Filter Method ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Integration System ◽  
Integrated Navigation System ◽  
Multiple Receivers

GNSS (global navigation satellite system) and SINS (strap-down inertial navigation system) integrated navigation systems have been the apparatus for providing reliable and stable position and velocity information (PV). Commonly, there are two solutions to improve the GNSS/SINS integration navigation system accuracy, i.e., employing GNSS with higher position accuracy in the integration system or utilizing the high-grade inertial measurement unit (IMU) to construct the integration system. However, technologies such as RTK (real-time kinematic) and PPP (precise point positioning) that improve GNSS positioning accuracy have higher costs and they cannot work under high dynamic environments. Also, an IMU with high accuracy will lead to a higher cost and larger volume, therefore, a low-cost method to enhance the GNSS/SINS integration accuracy is of great significance. In this paper, multiple receivers based on the GNSS/SINS integrated navigation system are proposed with the aim of providing more precise PV information. Since the chip-scale receivers are cheap, the deployment of multiple receivers in the GNSS/SINS integration will not significantly increase the cost. In addition, two different filtering methods with central and cascaded structure are employed to process the multiple receivers and SINS integration. In the centralized integration filter method, measurements from multiple receivers are directly processed to estimate the SINS errors state vectors. However, the computation load increases heavily due to the rising dimension of the measurement vector. Therefore, a cascaded integration filter structure is also employed to distribute the processing of the multiple receiver and SINS integration. In the cascaded processing method, each receiver is regarded as an individual “sensor”, and a standard federated Kalman filter (FKF) is implemented to obtain an optimal estimation of the navigation solutions. In this paper, a simulation and a field tests are carried out to assess the influence of the number of receivers on the PV accuracy. A detailed analysis of these position and velocity results is presented and the improvements in the PV accuracy demonstrate the effectiveness of the proposed method.

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