scholarly journals Implementation of Parallel Cascade Identification at Various Phases for Integrated Navigation System

2021 ◽  
Vol 13 (8) ◽  
pp. 191
Author(s):  
Umar Iqbal ◽  
Ashraf Abosekeen ◽  
Jacques Georgy ◽  
Areejah Umar ◽  
Aboelmagd Noureldin ◽  
...  
Keyword(s):  
Navigation System ◽  
Inertial Sensor ◽  
Integrated System ◽  
Experimental Results ◽  
Integrated Navigation ◽  
Navigation Solution ◽  
Parallel Cascade Identification ◽  
Non Linear ◽  
Tightly Coupled ◽  
Non Linear System

Global navigation satellite systems (GNSS) are widely used for the navigation of land vehicles. However, the positioning accuracy of GNSS, such as the global positioning system (GPS), deteriorates in urban areas due to signal blockage and multipath effects. GNSS can be integrated with a micro-electro-mechanical system (MEMS)–based inertial navigation system (INS), such as a reduced inertial sensor system (RISS) using a Kalman filter (KF) to enhance the performance of the integrated navigation solution in GNSS challenging environments. The linearized KF cannot model the low-cost and small-size sensors due to relatively high noise levels and compound error characteristics. This paper reviews two approaches to employing parallel cascade identification (PCI), a non-linear system identification technique, augmented with KF to enhance the navigational solution. First, PCI models azimuth errors for a loosely coupled 2D RISS integrated system with GNSS to obtain a navigation solution. The experimental results demonstrated that PCI improved the integrated 2D RISS/GNSS performance by modeling linear, non-linear, and other residual azimuth errors. For the second scenario, PCI is utilized for modeling residual pseudorange correlated errors of a KF-based tightly coupled RISS/GNSS navigation solution. Experimental results have shown that PCI enhances the performance of the tightly coupled KF by modeling the non-linear pseudorange errors to provide an enhanced and more reliable solution. For the first algorithm, the results demonstrated that PCI can enhance the performance by 77% as compared to the KF solution during the GNSS outages. For the second algorithm, the performance improvement for the proposed PCI technique during the availability of three satellites was 39% compared to the KF solution.

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.

An Enhanced 3D Multi-Sensor Integrated Navigation System for Land-Vehicles

2014 ◽  
Vol 67 (4) ◽  
pp. 651-671 ◽  
Author(s):  
Mohamed Maher Atia ◽  
Tashfeen Karamat ◽  
Aboelmagd Noureldin
Keyword(s):  
Navigation System ◽  
Urban Areas ◽  
Inertial Sensor ◽  
Dynamic Error ◽  
Error Model ◽  
Integrated System ◽  
Accurate Estimation ◽  
Integration Scheme ◽  
Integrated Navigation ◽  
Signal Degradation

In urban areas, Global Positioning System (GPS) accuracy deteriorates due to signal degradation and multipath effects. To provide accurate and robust navigation in such GPS-denied environments, multi-sensor integrated navigation systems are developed. This paper introduces a 3D multi-sensor navigation system that integrates inertial sensors, odometry and GPS for land-vehicle navigation. A new error model is developed and an efficient loosely coupled closed-loop Kalman Filter (Extended KF or EKF) integration scheme is proposed. In this EKF-based integration scheme, the inertial/odometry navigation output is continuously corrected by EKF-estimated errors, which keeps the errors within acceptable linearization ranges which improves the prediction accuracy of the linearized dynamic error model. Consequently, the overall performance of the integrated system is improved. Real road experiments and comparison with earlier works have demonstrated a more reliable performance during GPS signal degradation and accurate estimation of inertial sensor errors (biases) have led to a more sustainable performance reliability during long GPS complete outages.

scholarly journals A Novel Method of Fault Detection and Identification in a Tightly Coupled, INS/GNSS-Integrated System

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2922
Author(s):  
Fan Zhang ◽  
Ye Wang ◽  
Yanbin Gao
Keyword(s):  
Fault Detection ◽  
Parametric Bootstrap ◽  
Integrated System ◽  
Range Data ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Multiple Faults ◽  
Detection And Identification ◽  
Fault Detection And Identification ◽  
Tightly Coupled

Fault detection and identification are vital for guaranteeing the precision and reliability of tightly coupled inertial navigation system (INS)/global navigation satellite system (GNSS)-integrated navigation systems. A variance shift outlier model (VSOM) was employed to detect faults in the raw pseudo-range data in this paper. The measurements were partially excluded or included in the estimation process depending on the size of the associated shift in the variance. As an objective measure, likelihood ratio and score test statistics were used to determine whether the measurements inflated variance and were deemed to be faulty. The VSOM is appealing because the down-weighting of faulty measurements with the proper weighting factors in the analysis automatically becomes part of the estimation procedure instead of deletion. A parametric bootstrap procedure for significance assessment and multiple testing to identify faults in the VSOM is proposed. The results show that VSOM was validated through field tests, and it works well when single or multiple faults exist in GNSS measurements.

Optimising the Transfer Alignment of Weapon INS

2003 ◽  
Vol 56 (2) ◽  
pp. 323-335 ◽  
Author(s):  
Paul D. Groves
Keyword(s):  
Inertial Sensor ◽  
Integrated Navigation ◽  
Velocity Measurements ◽  
Transfer Alignment ◽  
Navigation Solution ◽  
Alignment Technique ◽  
Alignment Process ◽  
Using Data ◽  
Design Options ◽  
Better Than

Transfer alignment is the process of initialising and calibrating a weapon INS using data from the host aircraft's navigation system. To determine which transfer alignment technique performs best, different design options have been assessed, supported by simulation work. The dependence of transfer alignment performance on environmental factors, such as manoeuvres, alignment duration, lever arm and inertial sensor quality has also been studied. ‘Rapid’ alignment, using attitude as well as velocity measurements was found to perform better than ‘conventional’ techniques using only velocity. Innovative developments include the estimation of additional acceleration and gyro states and estimation of force dependent relative orientation, which has enabled robust alignment using wing rock manoeuvres, which do not require the pilot to change trajectory. Transfer alignment has been verified in real-time by flight trials on a Tornado aircraft. In addition, techniques have been developed to prevent transients in the aircraft integrated navigation solution following GPS re-acquisition after an outage of several minutes from disrupting the transfer alignment process.

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.

A Single Chip Integrated Navigation System

1993 ◽  
Vol 46 (1) ◽  
pp. 95-104 ◽  
Author(s):  
Eric Aardoom ◽  
André Nieuwland
Keyword(s):  
Navigation System ◽  
System Integration ◽  
Cost Effective ◽  
Integrated System ◽  
Integrated Navigation ◽  
Single Chip ◽  
Integrated Navigation System ◽  
System Integrity ◽  
Cost Effective Approach ◽  
Application Specific

Recently, integration of different radionavigation systems has become very popular, since it improves system integrity, availability, accuracy and reliability. This paper discusses a new, flexible and cost-effective approach to system integration, centred on a single-chip application specific processor (ASP). An overview of this integrated system is presented and the application of the ASP for the implementation of a six-channel GPS, OMEGA, Loran-C and MLS receiver is given. The ASP is currently being implemented on a 180000 transistor 1·6μ, m CMOS Sea of Gates chip, and is expected to run at 100 MHz clock speed.

scholarly journals Robust INS/SFPPP-BDS tightly coupled navigation algorithm with adaptive cycle slip compensation model

2019 ◽  
Vol 13 ◽  
pp. 174830181983304
Author(s):  
Hangshuai Ma ◽  
Rong Wang ◽  
Zhi Xiong ◽  
Jianye Liu ◽  
Chuanyi Li
Keyword(s):  
Navigation System ◽  
Carrier Phase ◽  
Low Cost ◽  
Integrated System ◽  
Single Frequency ◽  
Cycle Slip ◽  
Phase Measurements ◽  
Satellite Navigation System ◽  
Tightly Coupled ◽  
Robust Adaptive

The application of Beidou Satellite Navigation System (BDS) is developing rapidly. To satisfy the increasing demand for positioning performance, single-frequency precise point positioning (SFPPP) has been a focus in recent years. By introducing the SFPPP technique into the INS/BDS integrated system, higher navigation accuracy can be obtained. Cycle slip, which is caused by signal blockage during the measurement of the carrier phase, is a challenge for SFPPP application. In the INS/SFPPP-BDS integrated system, cycle slip can cause serious bias in BDS carrier phase measurements. In this paper, a new INS/SFBDS-PPP tightly coupled navigation system and a robust adaptive filtering method are proposed. Using a low-cost single-frequency receiver integrated with INS, an observation model was built based on the pseudo range and carrier phase by PPP preprocessing. The cycle slip was introduced into the state vector to improve the estimation precision. The test statistics, comprising the innovation and its covariance, were used to estimate the time at which cycle slip occurred and its amplitude to compensate for its effect on the observation. Finally, the proposed system model and algorithm are validated by simulation.

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