Low-cost RPAS navigation and guidance system using Square Root Unscented Kalman Filter

Multi-Sensor Data Fusion (MSDF) techniques involving satellite and inertial-based sensors are widely adopted to improve the navigation solution of a number of mission- and safety-critical tasks. Such integrated Navigation and Guidance Systems (NGS) currently do not meet the required level of performance in all flight phases of small Remotely Piloted Aircraft Systems (RPAS). In this paper an innovative Square Root-Unscented Kalman Filter (SR-UKF) based NGS is presented and compared with a conventional UKF governed design. The presented system architectures adopt state-of-the-art information fusion approach based on a number of low-cost sensors including; Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical System (MEMS) based Inertial Measurement Unit (IMU) and Vision Based Navigation (VBN) sensors. Additionally, an Aircraft Dynamics Model (ADM), which is essentially a knowledge based module, is employed to compensate for the MEMS-IMU sensor shortcomings in high-dynamics attitude determination tasks. The ADM acts as a virtual sensor and its measurements are processed with non-linear estimation in order to increase the operational validity time. An improvement in the ADM navigation state vector (i.e., position, velocity and attitude) measurements is obtained, thanks to the accurate modeling of aircraft dynamics and advanced processing techniques. An innovative SR-UKF based VBN-IMU-GNSS-ADM (SR-U-VIGA) architecture design was implemented and compared with a typical UKF design (U-VIGA) in a small RPAS (AEROSONDE) integration arrangement exploring a representative cross-section of the operational flight envelope. The comparison of position and attitude data shows that the SR-U-VIGA and U-VIGA NGS fulfill the relevant RNP criteria, including precision approach tasks

Low-cost sensors based multi-sensor data fusion techniques for RPAS navigation and guidance

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

GNSS avionics-based integrity augmentation for RPAS detect-and-avoid applications

Taking the move from our recent research on GNSS Avionics Based Integrity Augmentation (ABIA), this article investigates the synergies of ABIA with a novel Detect-and-Avoid (DAA) architecture for Remotely Piloted Aircraft System (RPAS). Based on simulation and experimental data collected on a variety of manned and unmanned aircraft, it was observed that the integration of ABIA with DAA has the potential to provide an integrity-augmented DAA for both cooperative and non-cooperative applications. The candidate DAA system uses various Forward-Looking Sensors (FLS) for the non-cooperative case and Automatic Dependent Surveillance-Broadcast (ADS-B) in addition to TCAS/ASAS for the cooperative case. Both in the cooperative and non-cooperative cases, the risk of collision is evaluated by setting a threshold on the Probability Density Function (PDF) of a Near Mid-Air Collision (NMAC) event over the separation area. So, if the specified threshold is exceeded, an avoidance manoeuvre is performed based on a heading-based Differential Geometry (DG) algorithm and optimized utilizing a cost function with minimum time constraints and fuel penalty criteria weighted as a function of separation distance. Additionally, the optimised avoidance trajectory considers the constraints imposed by the ABIA in terms of RPAS platform dynamics and GNSS constellation satellite elevation angles, preventing degradation or losses of navigation data during the whole DAA loop. This integration scheme allows real-time trajectory corrections to re-establish the Required Navigation Performance (RNP) when actual GNSS accuracy degradations and/or data losses take place (e.g., due to aircraft-satellite relative geometry, GNSS receiver tracking, interference, jamming or other external factors). Cooperative and non-cooperative simulation case studies were accomplished to evaluate the performance of this Integrity-Augmented DAA (IAS) architecture. The selected host platform was the AEROSONDE RPAS and the simulation cases were performed in a representative cross-section of the RPAS operational flight envelope. The simulation results show that the proposed IAS architecture is capable of performing high-integrity conflict detection and resolution when GNSS is the primary source of navigation data

GNSS avionics-based integrity augmentation for RPAS detect-and-avoid applications

Taking the move from our recent research on GNSS Avionics Based Integrity Augmentation (ABIA), this article investigates the synergies of ABIA with a novel Detect-and-Avoid (DAA) architecture for Remotely Piloted Aircraft System (RPAS). Based on simulation and experimental data collected on a variety of manned and unmanned aircraft, it was observed that the integration of ABIA with DAA has the potential to provide an integrity-augmented DAA for both cooperative and non-cooperative applications. The candidate DAA system uses various Forward-Looking Sensors (FLS) for the non-cooperative case and Automatic Dependent Surveillance-Broadcast (ADS-B) in addition to TCAS/ASAS for the cooperative case. Both in the cooperative and non-cooperative cases, the risk of collision is evaluated by setting a threshold on the Probability Density Function (PDF) of a Near Mid-Air Collision (NMAC) event over the separation area. So, if the specified threshold is exceeded, an avoidance manoeuvre is performed based on a heading-based Differential Geometry (DG) algorithm and optimized utilizing a cost function with minimum time constraints and fuel penalty criteria weighted as a function of separation distance. Additionally, the optimised avoidance trajectory considers the constraints imposed by the ABIA in terms of RPAS platform dynamics and GNSS constellation satellite elevation angles, preventing degradation or losses of navigation data during the whole DAA loop. This integration scheme allows real-time trajectory corrections to re-establish the Required Navigation Performance (RNP) when actual GNSS accuracy degradations and/or data losses take place (e.g., due to aircraft-satellite relative geometry, GNSS receiver tracking, interference, jamming or other external factors). Cooperative and non-cooperative simulation case studies were accomplished to evaluate the performance of this Integrity-Augmented DAA (IAS) architecture. The selected host platform was the AEROSONDE RPAS and the simulation cases were performed in a representative cross-section of the RPAS operational flight envelope. The simulation results show that the proposed IAS architecture is capable of performing high-integrity conflict detection and resolution when GNSS is the primary source of navigation data

4-dimensional trajectory generation algorithms for RPAS mission management systems

This paper presents the algorithms enabling real-time 4-Dimensional Flight Trajectory (4DT) functionalities in Next Generation Mission Management Systems (NG-MMS), which are the core element of future Remotely Piloted Aircraft Systems (RPAS) avionics. In particular, the algorithms are employed for multi-objective optimisation of 4DT intents in various operational scenarios spanning from online strategic to tactical and emergency tasks. The adopted formulation of the multi-objective 4DT optimisation problem includes a number of environmental objectives and operational constraints. In particular, this paper describes the algorithm for planning of 4DT based on a multi-objective optimisation approach and the generalised expression of the cost function adopted for penalties associated with specific airspace volumes, accounting for weather, condensation trails and noise models

CNS+A capabilities for the integration of unmanned aircraft in controlled airspace

In this paper, the system requirements for the integration of Remotely Piloted Aircraft Systems (RPAS) in controlled airspace regions are discussed. The specificities in terms of Air Traffic Management (ATM) level of service, jurisdiction for deconfliction duties and prevalent traffic characteristics are analysed to support the identification of operational and equipage requirements for RPAS developers. Communication, Navigation, Surveillance, ATM and Avionics (CNS+A) equipment play an essential role in airspace regions characteried by high levels of Air Traffic Services (ATS) and a higher probability of traffic conflicts. A denser route structure and a more frequent occurrence of traffic conflicts mandate high CNS performance, as the deconfliction by ATM crucially relies on accurate and reliable CNS information. Notwithstanding, the reduced jurisdiction of aircraft in deconfliction duties also offers an opportunity to RPAS developers, as it relieves the requirements for on-board expert processing

Novel flight management system for improved safety and sustainability in the CNS+A context

Avionic system developers are faced with the challenge of researching and introducing innovative technologies that satisfy the requirements arising from the rapid expansion of global air transport while addressing the growing concerns for environmental sustainability of the aviation sector. As a consequence, novel systems are being developed in the Communication, Navigation and Surveillance/Air Traffic Management (CNS/ATM) and Avionics (CNS+A) context. The introduction of dedicated software modules in Next Generation Flight Management Systems (NG-FMS), which are the primary providers of automated navigation and guidance services in manned aircraft and Remotely-Piloted Aircraft Systems (RPAS), has the potential to enable the significant advances brought in by time based operations. In this paper, key elements of the NG-FMS architecture are presented that allow the incorporation of 4-Dimensional Trajectory (4DT) planning and optimisation with inclusion of CNS integrity monitoring and augmentation functions in the overall design. The NG-FMS is designed to be fully interoperable with a future ground based 4DT Planning, Negotiation and Validation (4-PNV) system, enabling automated Trajectory/Intent-Based Operations (TBO/IBO). The mathematical models for 4DT planning are presented and the CNS integrity performance criteria are identified for various mission- and safety-critical tasks. Evaluation of the proposed concepts and methodologies is performed through dedicated simulation test case. The results demonstrate the functional capability of the NG-FMS to generate cost-effective trajectory profiles satisfying operational as well as environmental constraints

Communication, navigation and surveillance performance criteria for safety-critical avionics and ATM systems

The demand for improved safety, integrity and efficiency due to the rapid growth of aviation sector and the growing concern for environmental sustainability issues poses significant challenges on the development of future Communication, Navigation and Surveillance/Air Traffic Management (CNS/ATM) and Avionics (CNS+A) systems. High-integrity, high-reliability and all-weather services are required in the context of four dimensional Trajectory Based Operations / Intent Based Operations (TBO/IBO). The Next Generation Flight Management Systems (NG-FMS) and the Next Generation Air Traffic Management (NG-ATM) systems are developed allowing automated negotiation and validation of the aircraft intents provided by the NG-FMS. After describing the key system architectures, the mathematical models for trajectory generation and CNS performance criteria evaluation are presented. In this paper, the method for evaluating navigation performance is presented, including a detailed Monte Carlo simulation case study. The proposed approach will form a basis for evaluating communication and surveillance performances as well in future research. The Monte Carlo simulation results demonstrate the capability of the proposed CNS+A system architectures to comply with the required navigation performance criteria in the generation of optimized aircraft trajectory profiles

Avionics-based GNSS integrity augmentation performance in a jamming environment

Intentional and unintentional radiofrequency interference (i.e., jamming) can result in degraded navigation accuracy or complete loss of the GNSS signal tracking. Jammers can be classified into three broad categories: Narrowband Jammers (NBJ), Spread Spectrum Jammers(SSJ) and Wideband Gaussian Jammers (WGJ). In recent years, a number of effective jamming detection and anti-jamming (filtering and suppression) techniques have been developed for military GNSS applications and some of them are envisaged to be used for civil purposes (e.g., terrorist attacks). The synergies between these jamming detection techniques and our newly developed Avionics-Based Integrity Augmentation (ABIA) system are investigated in this paper. In particular, GNSS vulnerability to NBJ, SSJ and WGJ types of jamming is analytically described in terms of Jamming to Signal (J/S) tracking thresholds and the models for calculating the minimum acceptable aircraft-to-jammer ranges are presented. Simulation results demonstrate that the proposed ABIA architecture is capable of performing jamming detection and avoidance when GNSS is considered as the primary source of navigation data

A unified approach to cooperative and non-cooperative sense-and-avoid

Cooperative and non-cooperative Sense-and-Avoid (SAA) capabilities are key enablers for Unmanned Aircraft Vehicle (UAV) to safely and routinely access all classes of airspace. In this paper state-of-the-art cooperative and non-cooperative SAA sensor/system technologies for small-to-medium size UAV are identified and the associated multi-sensor data fusion techniques are introduced. A reference SAA system architecture is presented based on Boolean Decision Logics (BDL) for selecting and sorting non-cooperative and cooperative sensors/systems including both passive and active Forward Looking Sensors (FLS), Traffic Collision Avoidance System (TCAS) and Automatic Dependent Surveillance - Broadcast (ADS-B). After elaborating the SAA system processes, the key mathematical models associated with both non-cooperative and cooperative SAA functions are presented. The analytical models adopted to compute the overall uncertainty volume in the airspace surrounding an intruder are described. Based on these mathematical models, the SAA Unified Method (SUM) for cooperative and non-cooperative SAA is presented. In this unified approach, navigation and tracking errors affecting the measurements are considered and translated to unified range and bearing uncertainty descriptors, which apply both to cooperative and non-cooperative scenarios. Simulation case studies are carried out to evaluate the performance of the proposed SAA approach on a representative host platform (AEROSONDE UAV) and various intruder platforms. Results corroborate the validity of the proposed approach and demonstrate the impact of SUM towards providing a cohesive logical framework for the development of an airworthy SAA capability, which provides a pathway for manned/unmanned aircraft coexistence in all classes of airspace