Advanced Navigation System for Aircraft Applications

Various forms of navigation are present in today’s world, leading from satellite based navigation to several archaic forms of navigation like star gazing. Now, lots of technologies are available to achieve this but with certain limitations. For example, FOG based navigation provides accuracy with in 0.10-100 range which is not sufficient for various military applications. Therefore, there is a need to design a system which will have better accuracy and thus requires development of ring laser gyro-based inertial systems. This paper concentrates on the aided navigation system based on ring laser gyro of 0.01 deg/hr class and GPS - GLONASS to further enhance the capability of system in terms of accuracy. The usage of such systems not only provides accurate results momentarily but it also persists for longer duration with the aid of GPS - GLONASS for applications like aircraft, ship and long range missiles. The system provides accuracy of the level of 1 Nm/hr in pure navigation and 30 m with the aid of GPS - GLONASS. Apart from this, the availability of gyro-compass and baro-inertial algorithms further enhances the system capabilities and made them self dependent to the major extent.Defence Science Journal, 2013, 63(2), pp.131-137, DOI:http://dx.doi.org/10.14429/dsj.63.425

Design and Analysis of a Navigation System Using the Federated Filter

The purpose of this paper was to design and analyse a federated filter design, to be used for retrofit of an Embedded GPS/INS (EGI) navigation unit into an existing Kalman filter-based air navigation system. A design was selected and simulations were conducted in the Distributed Kalman Filter Simulation software (DKFSIM). As well, a centralized Kalman filter design was simulated under identical conditions for comparison purposes. The federated filter was shown to be a feasible design, with accuracy in position and velocity very close to centralized Kalman filter values. The federated filter design also showed some attractive fault detection and isolation features, superior to the centralized Kalman filter, due to the independent operation of the component Kalman filters. The federated filter was shown to be well worthy of continued study for implementation in air navigation systems, especially where distributed filters are required

All Source Sensor Integration Using an Extended Kalman Filter

The global positioning system (GPS) has become an ubiquitous source for navigation in the modern age, especially since the removal of selective availability at the beginning of this century. The utility of the GPS is unmatched, however GPS is not available in all environments. Heavy reliance on GPS for navigation makes the warfighter increasingly vulnerability as modern warfare continues to evolve. This research provides a method for incorporating measurements from a massive variety of sensors to mitigate GPS dependence. The result is the integration of sensor sets that encompass those examined in recent literature as well as some custom navigation devices. A full-state extended Kalman filter is developed and implemented, accommodating the requirements of the varied sensor sets and scenarios. Some 19 types of sensors are used in multiple quantities including inertial measurement units, single cameras and stereo pairs, 2D and 3D laser scanners, altimeters, 3-axis magnetometers, heading sensors, inclinometers, a stop sign sensor, an odometer, a step sensor, a ranging device, a signal of opportunity sensor, global navigation satellite system sensors, an air data computer, and radio frequency identification devices. Simulation data for all sensors was generated to test filter performance. Additionally, real data was collected and processed from an aircraft, ground vehicles, and a pedestrian. Measurement equations are developed to relate sensor measurements to the navigation states. Each sensor measurement is incorporated into the filter using the Kalman filter measurement update equations. Measurement types are segregated based on whether they observe instantaneous or accumulated state information. Accumulated state measurements are incorporated using delayed-state update equations. All other measurements are incorporated using the numerically robust UD update equations

Non-GPS Navigation Using Vision-Aiding and Active Radio Range Measurements

The military depends on the Global Positioning System (GPS) for a wide array of advanced weaponry guidance and precision navigation systems. Lack of GPS access makes precision navigation very difficult. Inclusion of inertial sensors in existing navigation systems provides short-term precision navigation, but drifts significantly over long-term navigation. This thesis is motivated by the need for inertial sensor drift-constraint in degraded and denied GPS environments. The navigation system developed consists of inertial sensors, a simulated barometer, three Raytheon DH500 radios, and a stereo-camera image-aiding system. The Raytheon DH500 is a combat communication radio which also provides range measurements between radios. The measurements from each sensor are fused together with an extended Kalman filter to estimate the navigation trajectory. Residual monitoring and the Sage-Husa adaptive algorithm are individually tested in the Kalman filter range update algorithm to help improve the radio range positioning performance. The navigation system is shown to provide long-term inertial sensor drift-constraint with position errors as low as 3 meters

Integration of INS, GPS, Magnetometer and Barometer for Improving Accuracy Navigation of the Vehicle

This paper describes integrated navigation system that is based on a low cost inertial sensor, global positioning system (GPS) receiver, magnetometer and a barometer, in order to improve accuracy of complete attitude and navigation solution. The main advantage of integration consists in availability of reliable navigation parameters during the intervals of absence of GPS data. The magnetometer and the barometer are applied for the attitude calibration and vertical channel stabilization, respectively. The acceptable accuracy of inertial navigation system (INS) is achieved by the proper damping of INS errors. The integration is made by the implementation of an extended Kalman filter (EKF) with control signal that is designed appropriate for low accuracy sensors noise characteristics. The analysis of integrated navigation system performances is made experimentally and the results show that integrated navigation system provides continuous and reliable navigation solutions.Defence Science Journal, 2013, 63(5), pp.451-455, DOI:http://dx.doi.org/10.14429/dsj.63.453

Automatic Landing without GPS

Sagem Défense et Sécurité (now Safran Electronics & Defense), a French space and defense company of the SAFRAN group, is working on the next generation of Unmanned Aerial System (UAS). This UAS features a fully automatic Unmanned Aerial Vehicle (UAV) equipped with a state-of-the-art navigation system. This navigation system relies mainly on a high-accuracy Inertial Measurement Unit (IMU) coupled with a GPS receiver. But the GPS is known to be easy to jam, either naturally (solar flare for example) or intentionally. In the event of a loss of GPS signal, the navigation system is not able anymore to provide accurate position and speed information to the Flight Controller (FC). Deprived of reliable position and speed information the FC is not able to guide the UAV safely to the ground. So the goal of the project detailed in this report is to add to the existing UAS the ability to land safely in case of a GPS loss. At the core of the solution described in this report is a sensor fusion algorithm taking as input inertial, vision based, barometric, laser and azimuthal measurements. The filter is using all these measurements to establish reliable position and speed estimates. Even if very reliable systems enabling automatic landing without GPS exist today; they all require heavy and expensive ground equipment. This is why SAGEM decided to develop its own solution using more embedded sensors and less ground equipment. This is a first step toward a fully embedded automatic landing system nondependent on GPS availability, a very active field of research today. All the tests done during the thesis and presented in this report shows the efficiency and robustness of this solution

Flight Test Evaluation of Mission Computer Algorithms for a Modern Trainer Aircraft

A low cost integrated avionics system has been realized on a modern trainer aircraft. Without using an expensive inertial navigation system onboard, acceptable level of accuracy for navigation, guidance, and weapon aiming is achieved by extensive data fusion within mission computer. The flight test evaluation of mission computer is carried out by assessing the overall performance under various navigation and guidance modes. In flight simulation is carried out for weapon aiming modes. The mission computer interfaces with various subsystems and implements the functional requirements for flight management and mission management. The aim of this paper is to discuss the algorithms of a data fusion intensive mission computer and flight test evaluation of these algorithms, for a typical modern trainer aircraft. The challenges and innovations involved in the work are also discussed.Defence Science Journal, 2013, 63(2), pp.164-173, DOI:http://dx.doi.org/10.14429/dsj.63.425

Pilot Assisted Inertial Navigation System Aiding Using Bearings-Only Measurements Taken Over Time

The objective of this work is to develop an alternative INS aiding source other than the GPS, while preserving the autonomy of the integrated navigation system. It is proposed to develop a modernized method of aerial navigation using driftmeter measurements from an E/O system for ground feature tracking, and an independent altitude sensor in conjunction with the INS. The pilot will track a ground feature with the E/O system, while the aircraft is on autopilot holding constant airspeed, altitude, and heading during an INS aiding session. The ground feature measurements from the E/O system and the INS output form measurements provided to a linear KF running on the navigation computer to accomplish the INS aiding action. Aiding the INS will be periodically repeated as operationally permissible under pilot discretion. Little to no modeling error will be present when implementing the linear Kalman filter, indicating the strength of the INS aiding action will be exclusively determined by the prevailing degree of observability

Modeling of Barometric Altimeter Measurements to support Geodetic Altitude Navigation

Vertical Navigation is of great importance for safe aircraft navigation and guidance, which have been for decades based on standard pressure altitude to support the determination of aircrafts flight levels. This altitude is obtained from airborne pressure measurements performed by barometers and is referenced to the International Standard Aatmosphere Mean Sea Level isobar surface. Standard pressure altitude deviates from true geodetic altitude, that is the one used by GNSS and referenced to an Earth's reference ellipsoid, up to several hundreds of meters for aircrafts flying at typical civil aviation cruise altitudes. Accurate and reliable geodetic altitude navigation is necessary and critical for airport vicinities operations and for new applications like Urban Air Mobility or Alternative Positioning Navigation applications. Although Inertial Navigation Systems and Global Navigation Satellite Systems are able to provide geodetic altitude estimation, both kinds of navigation systems show normally poorer performances in vertical navigation than in the horizontal one. First, this thesis investigates the accuracy in the computation of geodetic altitude from a corrected pressure altitude computed with barometric pressure and external weather data. This computation method is herein shown to remarkably reduce the deviation of the standard pressure altitude from the true geodetic altitude. Secondly, this work derives two robust error models to support the use of barometric pressure measurements for safe geodetic altitude navigation. The first overbounding model is suitable for the use in snapshot (i.e., single-epoch) algorithms. The second dynamic overbounding model is suitable to be included in sequential estimators and in those applications where the time correlation of the pressure measurements must be properly taken into account. The evaluation of the accuracy obtained in computing geodetic altitude from the corrected pressure altitude as well as the analysis of the residual error models is obtained by the use of data gathered during more than 20 flight hours performed with the Dassault Falcon 20-E5 aircraft within a DLR flight tests campaign

Vertiport Navigation Requirements and Multisensor Architecture Considerations for Urban Air Mobility

Communication, Navigation and Surveillance (CNS) technologies are key enablers for future safe operation of drones in urban environments. However, the design of navigation technologies for these new applications is more challenging compared to e.g., civil aviation. On the one hand, the use cases and operations in urban environments are expected to have stringent requirements in terms of accuracy, integrity, continuity and availability. On the other hand, airborne sensors may not be based on high-quality equipment as in civil aviation and solutions need to rely on tighter multisensor solutions, whose safety is difficult to assess. In this work, we first provide some initial navigation requirements related to precision approach operations based on recently proposed vertiport designs. Then, we provide an overview of a possible multisensor navigation architecture solution able to support these types of operations and we comment on the challenges of each of the subsystems. Finally, initial proof of concept for some navigation sensor subsystems is presented based on flight trials performed during the German Aerospace Center (DLR) project HorizonUAM