A framework for cots software evaluation and selection for COTS mismatches handling and non-functional requirements

The decision to purchase Commercial Off-The-Shelf (COTS) software needs systematic guidelines so that the appropriate COTS software can be selected in order to provide a viable and effective solution to the organizations. However, the existing COTS software evaluation and selection frameworks focus more on functional aspects and do not give adequate attention to accommodate the mismatch between user requirements and COTS software specification, and also integration with non functional requirements of COTS software. Studies have identified that these two criteria are important in COTS software evaluation and selection. Therefore, this study aims to develop a new framework of COTS software evaluation and selection that focuses on handling COTS software mismatches and integrating the nonfunctional requirements. The study is conducted using mixed-mode methodology which involves survey and interview. The study is conducted in four main phases: a survey and interview of 63 organizations to identify COTS software evaluation criteria, development of COTS software evaluation and selection framework using Evaluation Theory, development of a new decision making technique by integrating Analytical Hierarchy Process and Gap Analysis to handle COTS software mismatches, and validation of the practicality and reliability of the proposed COTS software Evaluation and Selection Framework (COTS-ESF) using experts’ review, case studies and yardstick validation. This study has developed the COTS-ESF which consists of five categories of evaluation criteria: Quality, Domain, Architecture, Operational Environment and Vendor Reputation. It also provides a decision making technique and a complete process for performing the evaluation and selection of COTS software. The result of this study shows that the evaluated aspects of the framework are feasible and demonstrate their potential and practicality to be applied in the real environment. The contribution of this study straddles both the research and practical perspectives of software evaluation by improving decision making and providing a systematic guidelines for handling issue in purchasing viable COTS software

Real-Time Implementation of Vision-Aided Monocular Navigation for Small Fixed-Wing Unmanned Aerial Systems

The goal of this project was to develop and implement algorithms to demonstrate real-time positioning of a UAV using a monocular camera combined with previously collected orthorectified imagery. Unlike previous tests, this project did not utilize a full inertial navigation system (INS) for attitude, but instead had to rely on the attitude obtained by inexpensive commercial off-the-shelf (COTS) autopilots. The system consisted of primarily COTS components and open-source software, and was own over Camp Atterbury, IN for a sequence of flight tests in Fall 2015. The system obtained valid solutions over much of the flight path, identifying features in the flight image, matching those features with a database of features, and then solving both the 6DOF solution, and an attitude-aided 3DOF solution. The tests demonstrated that such attitude aiding is beneficial, since the horizontal DRMS of the 6DOF solution was 59m, whereas the 3DOF solution DRMS was 15m. Post processing was done to improve the algorithm to correct for system errors, obtaining a 3DOF solution DRMS of 8.22 meters. Overall, this project increased our understanding of the capabilities and limitations of real-time vision-aided navigation, and demonstrated that such navigation is possible on a relatively small platform with limited computational power

The design and implementation of a wideband digital radio receiver

Historically radio has been implemented using largely analogue circuitry. Improvements in mixed signal and digital signal processing technology are rapidly leading towards a largely digital approach, with down-conversion and filtering moving to the digital signal processing domain. Advantages of this technology include increased performance and functionality, as well as reduced cost. Wideband receivers place the heaviest demands on both mixed signal and digital signal processing technology, requiring high spurious free dynamic range (SFDR) and signal processing bandwidths. This dissertation investigates the extent to which current digital technology is able to meet these demands and compete with the proven architectures of analogue receivers. A scalable generalised digital radio receiver capable of operating in the HF and VHF bands was designed, implemented and tested, yielding instantaneous bandwidths in excess of 10 MHz with a spurious-free dynamic range exceeding 80 decibels below carrier (dBc). The results achieved reflect favourably on the digital receiver architecture. While the necessity for minimal analogue circuitry will possibly always exist, digital radio architectures are currently able to compete with analogue counterparts. The digital receiver is simple to manufacture, based on the use of largely commercial off-the-shelf (COTS) components, and exhibits extreme flexibility and high performance when compared with comparably priced analogue receivers

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

DECENTRALIZED ROBUST NONLINEAR MODEL PREDICTIVE CONTROLLER FOR UNMANNED AERIAL SYSTEMS

The nonlinear and unsteady nature of aircraft aerodynamics together with limited practical range of controls and state variables make the use of the linear control theory inadequate especially in the presence of external disturbances, such as wind. In the classical approach, aircraft are controlled by multiple inner and outer loops, designed separately and sequentially. For unmanned aerial systems in particular, control technology must evolve to a point where autonomy is extended to the entire mission flight envelope. This requires advanced controllers that have sufficient robustness, track complex trajectories, and use all the vehicles control capabilities at higher levels of accuracy. In this work, a robust nonlinear model predictive controller is designed to command and control an unmanned aerial system to track complex tight trajectories in the presence of internal and external perturbance. The Flight System developed in this work achieves the above performance by using: 1 A nonlinear guidance algorithm that enables the vehicle to follow an arbitrary trajectory shaped by moving points; 2 A formulation that embeds the guidance logic and trajectory information in the aircraft model, avoiding cross coupling and control degradation; 3 An artificial neural network, designed to adaptively estimate and provide aerodynamic and propulsive forces in real-time; and 4 A mixed sensitivity approach that enhances the robustness for a nonlinear model predictive controller overcoming the effect of un-modeled dynamics, external disturbances such as wind, and measurement additive perturbations, such as noise and biases. These elements have been integrated and tested in simulation and with previously stored flight test data and shown to be feasible

A Highly Integrated Navigation Unit for On-Orbit Servicing Missions

VINAG (VISION/INS integrated Navigation Assisted by GNSS) is a highly integrated multisensor navigation unit, particularly conceived for On-Orbit Servicing missions. The system is designed to provide all-in-one, on-board real time autonomous absolute navigation as well as pose determination of an uncooperative known object orbiting in LEO (Low Earth Orbit), GEO (GEosynchronous Orbits) and possibly in HEO (Highly Earth Orbit). The system VINAG is under development by a team of Italian companies and universities, co-financed by the Italian Space Agency. Thanks to a tight optimized integration of its subsystems, VINAG is characterized by a low power and mass total budgets and therefore it is suitable for small and very small satellites. In order to provide both 1) absolute orbit and attitude determination and 2) vision-based pose determination, the unit integrates three metrology systems: a Cameras Subsystem (a monocular camera and a Star sensor), an Inertial Measurement Unit (IMU) and a GNSS (Global Navigation Satellite System) receiver. In this paper, we introduce the complete system architecture, the adopted algorithms and then the adopted hardware design solutions. In addition, we describe preliminary numerical simulation results obtained for different orbits from LEO to GEO carried out for the validation phase of VINAG

Identifying and Correcting First Order Effects in Explanatory Variables for Longitudinal Real Time Parameter Identification Methods in Atmospheric Turbulence

The use of real time parameter estimation methods for dynamic flight modeling in atmospheric turbulence was studied. Real time parameter estimation results of flight data in atmospheric turbulence and in a calm atmosphere were used to explain the problem and identify potential error sources. The use of indirect atmospheric turbulence measurements for real-time parameter estimation in a linear longitudinal dynamics model was studied to account for atmospheric turbulence. It is shown that measuring the air data angles correctly makes it possible to account for atmospheric turbulence as a measured explanatory variable in the parameter estimation problem. Commercial off-the-shelf sensors were researched and evaluated, then compared to air data booms. Frequency response of airflow angle vanes, structural response of the air data boom, and the frequency-dependent upwash and time delay were identified and studied as sources of colored noise in the explanatory variables resulting from typical atmospheric turbulence measurement techniques. The theory explaining the frequency dependent upwash and time delay of airflow angle vanes was studied. The resulting upwash and time delay corrections were analyzed and compared to previous time shift dynamic modeling research. Simulation data, as well as flight test data in atmospheric turbulence, were used to verify the upwash and time delay behavior. A methodology was developed to apply real time upwash and time delay corrections to the airflow angle vanes, dramatically improving parameter estimation results over the existing state of the art. Recommendations are given for follow-on theoretical development, flight research, and instrumentation

Alternative Methods for Non-Linearity Estimation in High-Resolution Analog-to-Digital Converters

The evaluation of the linearity performance of a high resolution Analog-to- Digital Converter (ADC) by the Standard Histogram method is an outstanding challenge due to the requirement of high purity of the input signal and the high number of output data that must be acquired to obtain an acceptable accuracy on the estimation. These requirements become major application drawbacks when the measures have to be performed multiple times within long test flows and for many parts, and under an industrial environment that seeks to reduce costs and lead times as is the case in the New Space sector. This thesis introduces two alternative methods that succeed in relaxing the two previous requirements for the estimation of the Integral Nonlinearity (INL) parameter in ADCs. The methods have been evaluated by estimating the Integral Non-Linearity pattern by simulation using realistic high-resolution ADC models and experimentally by applying them to real high performance ADCs. First, the challenge of applying the Standard Histogram method for the evaluation of static parameters in high resolution ADCs and how the drawbacks are accentuated in the New Space industry is analysed, being a highly expensive method for an industrial environment where cost and lead time reduction is demanded. Several alternative methods to the Standard Histogram for estimating Integral Nonlinearity in high resolution ADCs are reviewed and studied. As the number of existing works in the literature is very large and addressing all of them is a challenge in itself, only those most relevant to the development of this thesis have been included. Methods based on spectral processing to reduce the number of data acquired for the linearity test and methods based on a double histogram to be able to use generators that do not meet the the purity requirement against the ADC to be tested are further analysed. Two novel contributions are presented in this work for the estimation of the Integral Nonlinearity in ADCs, as possible alternatives to the Standard Histogram method. The first method, referred to as SSA (Simple Spectral Approach), seeks to reduce the number of output data that need to be acquired and focuses on INL estimation using an algorithm based on processing the spectrum of the output signal when a sinusoidal input stimulus is used. This type of approach requires a much smaller number of samples than the Standard Histogram method, although the estimation accuracy will depend on how smooth or abrupt the ADC nonlinearity pattern is. In general, this algorithm cannot be used to perform a calibration of the ADC nonlinearity error, but it can be applied to find out between which limits it lies and what its approximate shape is. The second method, named SDH (Simplified Double Histogram)aims to estimate the Non-Linearity of the ADC using a poor linearity generator. The approach uses two histograms constructed from the two set of output data in response to two identical input signals except for a dc offset between them. Using a simple adder model, an extended approach named ESDH (Extended Simplified Double Histogram) addresses and corrects for possible time drifts during the two data acquisitions, so that it can be successfully applied in a non-stationary test environment. According to the experimental results obtained, the proposed algorithm achieves high estimation accuracy. Both contributions have been successfully tested in high-resolution ADCs with both simulated and real laboratory experiments, the latter using a commercial ADC with 14-bit resolution and 65Msps sampling rate (AD6644 from Analog Devices).La medida de la característica de linealidad de un convertidor analógicodigital (ADC) de alta resolución mediante el método estándar del Histograma constituye un gran desafío debido los requisitos de alta pureza de la señal de entrada y del elevado número de datos de salida que deben adquirirse para obtener una precisión aceptable en la estimación. Estos requisitos encuentran importantes inconvenientes para su aplicación cuando las medidas deben realizarse dentro de largos flujos de pruebas, múltiples veces y en un gran número de piezas, y todo bajo un entorno industrial que busca reducir costes y plazos de entrega como es el caso del sector del Nuevo Espacio. Esta tesis introduce dos métodos alternativos que consiguen relajar los dos requisitos anteriores para la estimación de los parámetros de no linealidad en los ADCs. Los métodos se han evaluado estimando el patrón de No Linealidad Integral (INL) mediante simulación utilizando modelos realistas de ADC de alta resolución y experimentalmente aplicándolos en ADCs reales. Inicialmente se analiza el reto que supone la aplicación del método estándar del Histograma para la evaluación de los parámetros estáticos en ADCs de alta resolución y cómo sus inconvenientes se acentúan en la industria del Nuevo Espacio, siendo un método altamente costoso para un entorno industrial donde se exige la reducción de costes y plazos de entrega. Se estudian métodos alternativos al Histograma estándar para la estimación de la No Linealidad Integral en ADCs de alta resolución. Como el número de trabajos es muy amplio y abordarlos todos es ya en sí un desafío, se han incluido aquellos más relevantes para el desarrollo de esta tesis. Se analizan especialmente los métodos basados en el procesamiento espectral para reducir el número de datos que necesitan ser adquiridos y los métodos basados en un doble histograma para poder utilizar generadores que no cumplen el requisito de precisión frente al ADC a medir. En este trabajo se presentan dos novedosas aportaciones para la estimación de la No Linealidad Integral en ADCs, como posibles alternativas al método estándar del Histograma. El primer método, denominado SSA (Simple Spectral Approach), busca reducir el número de datos de salida que es necesario adquirir y se centra en la estimación de la INL mediante un algoritmo basado en el procesamiento del espectro de la señal de salida cuando se utiliza un estímulo de entrada sinusoidal. Este tipo de enfoque requiere un número mucho menor de muestras que el método estándar del Histograma, aunque la precisión de la estimación dependerá de lo suave o abrupto que sea el patrón de no-linealidad del ADC a medir. En general, este algoritmo no puede utilizarse para realizar una calibración del error de no linealidad del ADC, pero puede aplicarse para averiguar entre qué límites se encuentra y cuál es su forma aproximada. El segundo método, denominado SDH (Simplified Double Histogram) tiene como objetivo estimar la no linealidad del ADC utilizando un generador de baja pureza. El algoritmo utiliza dos histogramas, construidos a partir de dos conjuntos de datos de salida en respuesta a dos señales de entrada idénticas, excepto por un desplazamiento constante entre ellas. Utilizando un modelo simple de sumador, un enfoque ampliado denominado ESDH (Extended Simplified Double Histogram) aborda y corrige las posibles derivas temporales durante las dos adquisiciones de datos, de modo que puede aplicarse con éxito en un entorno de prueba no estacionario. De acuerdo con los resultados experimentales obtenidos, el algoritmo propuesto alcanza una alta precisión de estimación. Ambas contribuciones han sido probadas en ADCs de alta resolución con experimentos tanto simulados como reales en laboratorio, estos últimos utilizando un ADC comercial con una resolución de 14 bits y una tasa de muestreo de 65Msps (AD6644 de Analog Devices)

Air-to-Air Missile Vector Scoring

An air-to-air missile vector scoring system is proposed for test and evaluation applications. Three different linear missile dynamics models are considered: a six-state constant velocity model and nine-state constant acceleration and three-dimensional coordinated turn models. Frequency modulated continuous wave radar sensors, carefully located to provide spherical coverage around the target, provide updates of missile kinematic information relative to a drone aircraft. Data from the radar sensors is fused with predictions from one of the three missile models using either an extended Kalman filter, an unscented Kalman filter or a particle filter algorithm. The performance of all nine model/filter combinations are evaluated through high-fidelity, six-degree of freedom simulations yielding sub-meter end-game accuracy in a variety of scenarios. Simulations demonstrate the superior performance of the unscented Kalman filter incorporating the continuous velocity dynamics model. The scoring system is experimentally demonstrated through flight testing using commercial off the shelf radar sensors with a Beechcraft C-12 as a surrogate missile

Precise Orbit Determination of CubeSats

CubeSats are faced with some limitations, mainly due to the limited onboard power and the quality of the onboard sensors. These limitations significantly reduce CubeSats' applicability in space missions requiring high orbital accuracy. This thesis first investigates the limitations in the precise orbit determination of CubeSats and next develops algorithms and remedies to reach high orbital and clock accuracies. The outputs would help in increasing CubeSats' applicability in future space missions