检索结果-内蒙古大学图书馆

aircraft dynamics model Augmentation for RPAS Navigation and Guidance

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2018年第3-4期91卷 709-723页

作者： Cappello, Francesco Bijjahalli, Suraj Ramasamy, Subramanian Sabatini, Roberto Sch Engn Aerosp & Aviat Discipline Melbourne Vic 3000 Australia

An aircraft dynamics model (ADM) augmentation scheme for Remotely Piloted aircraft System (RPAS) navigation and guidance is presented. The proposed ADM virtual sensor is employed in the RPAS navigation system to enhance continuity and accuracy of positioning data in case of Global Navigation Satellite System (GNSS) data degradations/losses, and to improve attitude estimation by vision based sensors and Micro-Electromechanical System Inertial Measurement Unit (MEMS-IMU) sensors. The ADM virtual sensor is essentially a knowledge-based module that predicts RPAS flight dynamics (aircraft trajectory and attitude motion) by employing a rigid body 6-Degree of Freedom (6-DoF) model. Two possible schemes are studied for integration of the ADM module in the aircraft navigation system employing an Extended Kalman Filter (EKF) and an Unscented Kalman Filter (UKF). Additionally, the synergy between the navigation systems and an Avionics-Based Integrity Augmentation (ABIA) module is examined and a sensor-switching framework is proposed to maintain the Required Navigation Performance (RNP) in the event of single and multiple sensor degradations. The ADM performance is assessed through simulation of an RPAS in representative fight operations. Sensitivity analysis of the errors caused by perturbations in the input parameters of the aircraft dynamics is performed to demonstrate the robustness of the proposed approach. Results confirm that the ADM virtual sensor provides improved performance in terms of data accuracy/continuity, and an extension of solution validity time, especially when pre-filtered and employed in conjunction with a UKF.

关键词： Remotely piloted aircraft system Aerospace navigation aircraft dynamics model Virtual sensor Knowledge-based module Integrity augmentataion Multi-sensor data fusion

来源：评论

学校读者我要写书评

暂无评论

aircraft dynamics model Augmentation for RPAS Navigation and Guidance

Aircraft Dynamics Model Augmentation for RPAS Navigation and...

引用

International Conference on Unmanned aircraft Systems (ICUAS)

作者： Cappello, Francesco Sabatini, Roberto Ramasamy, Subrarnanian RMIT Univ Sch Engn Aerosp Mech & Mfg Melbourne Vic 300 Australia

ISBN: (纸本)9781467393331

In this paper, aircraft dynamics model (ADM) augmentation for Remotely Piloted aircraft System (RPAS) navigation and guidance is presented. This approach provides additional information suitable to compensate for the shortcomings of vision based navigation sensors and Micro-Electromechanical System Inertial Measurement Unit (MEMS-IMU) sensors for attitude determination tasks. The ADM virtual sensor is essentially a knowledge-based module and is used to augment the navigation state vector by predicting RPAS flight dynamics (aircraft trajectory and attitude motion). The ADM employs a rigid body 6-Degree of Freedom (6-DoF) model and is implemented in integrated multi-sensor data fusion architectures. The integration is accomplished with an Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). After introducing the key mathematical models describing the 6-DoF ADM, the sensor and integrated system performance are compared in a small RPAS integration scheme (i.e., AEROSONDE RPAS platform) exploring a representative cross-section of the aircraft operational flight envelope and a preliminary sensitivity analysis is performed. In addition to a centralised filter, a dedicated ADM processor (i.e., a local pre-filter) is adopted to account for the RPAS manoeuvring envelope in different flight phases, in order to extend the ADM validity time across all segments of the RPAS trajectory. Sensitivity analysis of the errors caused by perturbations in the input parameters of the aircraft dynamics is performed to demonstrate the robustness of the proposed approach. Results verify that the ADM virtual sensor provides improved performance in terms of attitude data accuracy and a significant extension of the ADM validity time is achieved by pre-filtering.

关键词： aircraft dynamics model Virtual Sensor Knowledge-Based Sesnor Multi-Sensor Data Fusion

来源：评论

学校读者我要写书评

暂无评论

Low-Cost Sensors based Multi-sensor Data Fusion Techniques for RPAS Navigation and Guidance

Low-Cost Sensors based Multi-sensor Data Fusion Techniques f...

引用

International Conference on Unmanned aircraft Systems (ICUAS)

作者： Cappello, Francesco Ramasamy, Subramanian Sabatini, Roberto Liu, Jing RMIT Univ Sch Aerosp Mech & Mfg Engn Melbourne Vic 3000 Australia

ISBN: (纸本)9781479960101

In order for Remotely Piloted aircraft Systems (RPAS) to coexist seamlessly with manned aircraft in non-segregated airspace, enhanced navigational capabilities are essential to meet the Required Navigational Performance (RNP) levels in all flight phases. A Multi-Sensor Data Fusion (MSDF) framework is adopted to improve the navigation capabilities of an integrated Navigation and Guidance System (NGS) designed for small-sized RPAS. The MSDF architecture includes low-cost and low weight/volume navigation sensors suitable for various classes of RPAS. The selected sensors include Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical System (MEMS) based Inertial Measurement Unit (IMU) and Vision Based Sensors (VBS). A loosely integrated navigation architecture is presented where an Unscented Kalman Filter (UKF) is used to combine the navigation sensor measurements. The presented UKF based VBS-INS-GNSS-ADM (U-VIGA) architecture is an evolution of previous research performed on Extended Kalman Filter (EKF) based VBS-INS-GNSS (E-VIGA) systems. An aircraft dynamics model (ADM) is adopted as a virtual sensor and acts as a knowledge-based module providing additional position and attitude information, which is pre-processed by an additional/local UKF. The E-VIGA and U-VIGA performances are evaluated in a small RPAS integration scheme (i.e., AEROSONDE RPAS platform) by exploring a representative cross-section of this RPAS operational flight envelope. The position and attitude accuracy comparison shows that the E-VIGA and U-VIGA systems fulfill the relevant RNP criteria, including precision approach in CAT-II. A novel Human Machine Interface (HMI) architecture is also presented, whose design takes into consideration the coordination tasks of multiple human operators. In addition, the interface scheme incorporates the human operator as an integral part of the control loop providing a higher level of situational awareness.

关键词： Remotely Piloted aircraft Systems aircraft dynamics model Unscented Kalman Filter Low-cost sensors Navigation and Guidance System Multi-sensor Data Fusion Human Machine Interface

来源：评论

学校读者我要写书评

暂无评论

Particle Filter based Multi-sensor Data Fusion Techniques for RPAS Navigation and Guidance 2

Particle Filter based Multi-sensor Data Fusion Techniques fo...

引用

2nd IEEE International Workshop on Metrology for Aerospace

作者： Cappello, Francesco Sabatini, Roberto Ramasamy, Subramanian Marino, Matthew RMIT Univ Sch Aerosp Mech & Mfg Engn Melbourne Vic 3000 Australia

ISBN: (纸本)9781479975693

This paper presents a Particle Filter (PF) based Multi-Sensor Data Fusion (MSDF) technique in an integrated Navigation and Guidance System (NGS) design based on low-cost avionics sensors. The performance of PF based MSDF method is compared with other previously implemented data fusion architectures for small-sized Remotely Piloted aircraft Systems (RPAS). The sensor suite of the implemented NGS includes;Global Navigation Satellite System (GNSS) sensor, which is adopted as the primary means of navigation, Micro-Electro-Mechanical System (MEMS) based Inertial Measuring Unit (IMU) and Vision-Based Navigation (VBN) sensor. Additionally, an aircraft dynamics model (ADM) is used as a virtual sensor to compensate for the MEMS-IMU sensor shortcomings in high-dynamics attitude determination tasks. The PF is specifically implemented to increase the accuracy of navigation solution obtained from the inherently inaccurate, low-cost Commercial-Off-The-Shelf (COTS) sensors. Simulations are carried out on the AEROSONDE RPAS performing high-dynamics manoeuvres representative of the RPAS operational flight envelope. The Extended Kalman Filter (EKF) based VBN-IMU-GNSS-ADM (E-VIGA) system, Unscented Kalman Filter (UKF) based U-VIGA system and the PF based P-VIGA system performances are evaluated and compared. Additionally, an error covariance analysis is performed on the centralised filter using Monte Carlo simulation. Results indicate that the PF is computationally expensive as the number of particles is increased. Compared to E-VIGA and U-VIGA systems, P-VIGA system shows an improvement of accuracy in the position, velocity and attitude measurements.

关键词： Remotely Piloted aircraft Systems aircraft dynamics model Particle Filter Unscented Kalman Filter Low-Cost Avionics Sensors Global Navigation Satellite System

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：