Algorithms for spacecraft formation flying navigation based on wireless positioning system measurements

Spacecraft formation flying navigation continues to receive a great deal of interest. The research presented in this dissertation focuses on developing methods for estimating spacecraft absolute and relative positions, assuming measurements of only relative positions using wireless sensors. The implementation of the extended Kalman filter to the spacecraft formation navigation problem results in high estimation errors and instabilities in state estimation at times. This is due tp the high nonlinearities in the system dynamic model. Several approaches are attempted in this dissertation aiming at increasing the estimation stability and improving the estimation accuracy. A differential geometric filter is implemented for spacecraft positions estimation. The differential geometric filter avoids the linearization step (which is always carried out in the extended Kalman filter) through a mathematical transformation that converts the nonlinear system into a linear system. A linear estimator is designed in the linear domain, and then transformed back to the physical domain. This approach demonstrated better estimation stability for spacecraft formation positions estimation, as detailed in this dissertation. The constrained Kalman filter is also implemented for spacecraft formation flying absolute positions estimation. The orbital motion of a spacecraft is characterized by two range extrema (perigee and apogee). At the extremum, the rate of change of a spacecraft’s range vanishes. This motion constraint can be used to improve the position estimation accuracy. The application of the constrained Kalman filter at only two points in the orbit causes filter instability. Two variables are introduced into the constrained Kalman filter to maintain the stability and improve the estimation accuracy. An extended Kalman filter is implemented as a benchmark for comparison with the constrained Kalman filter. Simulation results show that the constrained Kalman filter provides better estimation accuracy as compared with the extended Kalman filter. A Weighted Measurement Fusion Kalman Filter (WMFKF) is proposed in this dissertation. In wireless localizing sensors, a measurement error is proportional to the distance of the signal travels and sensor noise. In this proposed Weighted Measurement Fusion Kalman Filter, the signal traveling time delay is not modeled; however, each measurement is weighted based on the measured signal travel distance. The obtained estimation performance is compared to the standard Kalman filter in two scenarios. The first scenario assumes using a wireless local positioning system in a GPS denied environment. The second scenario assumes the availability of both the wireless local positioning system and GPS measurements. The simulation results show that the WMFKF has similar accuracy performance as the standard Kalman Filter (KF) in the GPS denied environment. However, the WMFKF maintains the position estimation error within its expected error boundary when the WLPS detection range limit is above 30km. In addition, the WMFKF has a better accuracy and stability performance when GPS is available. Also, the computational cost analysis shows that the WMFKF has less computational cost than the standard KF, and the WMFKF has higher ellipsoid error probable percentage than the standard Measurement Fusion method. A method to determine the relative attitudes between three spacecraft is developed. The method requires four direction measurements between the three spacecraft. The simulation results and covariance analysis show that the method’s error falls within a three sigma boundary without exhibiting any singularity issues. A study of the accuracy of the proposed method with respect to the shape of the spacecraft formation is also presented.

Quantum dot / optical protein bio-nano hybrid system biosensing

The integration of novel nanomaterials with highly-functional biological molecules has advanced multiple fields including electronics, sensing, imaging, and energy harvesting. This work focuses on the creation of a new type of bio-nano hybrid substrate for military biosensing applications. Specifically it is shown that the nano-scale interactions of the optical protein bacteriorhodopsin and colloidal semiconductor quantum dots can be utilized as a generic sensing substrate. This work spans from the basic creation of the protein to its application in a novel biosensing system. The functionality of this sensor design originates from the unique interactions between the quantum dot and bacteriorhodopsin molecule when in nanoscale proximity. A direct energy transfer relationship has been established between coreshell quantum dots and the optical protein bacteriorhodopsin that substantially enhances the protein’s native photovoltaic capabilities. This energy transfer phenomena is largely distance dependent, in the sub-10nm realm, and is characterized experimentally at multiple separation distances. Experimental results on the energy transfer efficiency in this hybrid system correlate closely to theoretical predictions. Deposition of the hybrid system with nano-scale control has allowed for the utilization of this energy transfer phenomena as a modulation point for a functional biosensor prototype. This work reveals that quantum dots have the ability to activate the bacteriorhodopsin photocycle through both photonic and non-photonic energy transfer mechanisms. By altering the energy transferred to the bacteriorhodopsin molecule from the quantum dot, the electrical output of the protein can be modulated. A biosensing prototype was created in which the energy transfer relationship is altered upon target binding, demonstrating the applicability of a quantum dot/bacteriorhodopsin hybrid system for sensor applications. The electrical nature of this sensing substrate will allow for its efficient integration into a nanoelectronics array form, potentially leading to a small-low power sensing platform for remote toxin detection applications.

Stability analysis of a mono inverter dual sensorless motors system

When a single brush-less dc motor is fed by an inverter with a sensor-less algorithm embedded in the switching controller, the system exhibits a linear and stable output in terms of the speed and torque. However, with two motors modulated by the same inverter, the system is unstable and rendered useless for a steady application, unless provided with some resistive damping on the supply lines. The project discusses and analysis the stability of such a system through simulations and hardware demonstrations and also will discuss a method to derive the values of these damping.

DESIGN AND FABRICATION OF RESONANT GAS SENSOR FOR HIGH SENSITIVITY IN THE PRESENCE OF AIR DAMPING

Gas sensors have been used widely in different important area including industrial control, environmental monitoring, counter-terrorism and chemical production. Micro-fabrication offers a promising way to achieve sensitive and inexpensive gas sensors. Over the years, various MEMS gas sensors have been investigated and fabricated. One significant type of MEMS gas sensors is based on mass change detection and the integration with specific polymer. This dissertation aims to make contributions to the design and fabrication of MEMS resonant mass sensors with capacitance actuation and sensing that lead to improved sensitivity. To accomplish this goal, the research has several objectives: (1) Define an effective measure for evaluating the sensitivity of resonant mass devices; (2) Model the effects of air damping on microcantilevers and validate models using laser measurement system (3) Develop design guidelines for improving sensitivity in the presence of air damping; (4) Characterize the degree of uncertainty in performance arising from fabrication variation for one or more process sequences, and establish design guidelines for improved robustness. Work has been completed toward these objectives. An evaluation measure has been developed and compared to an RMS based measure. Analytic models of air damping for parallel plate that include holes are compared with a COMSOL model. The models have been used to identify cantilever design parameters that maximize sensitivity. Additional designs have been modeled with COMSOL and the development of an analytical model for Fixed-free cantilever geometries with holes has been developed. Two process flows have been implemented and compared. A number of cantilever designs have been fabricated and the uncertainty in process has been investigated. Variability from processing have been evaluated and characterized.

Automatic Food Intake Assessment Using Camera Phones

Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.

USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS

Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.

Fabrication methods for creating flexible polymer substrate sensor tags

The authors describe the design, fabrication, and testing of a passive wireless sensor platform utilizing low-cost commercial surface acoustic wave filters and sensors. Polyimide and polyethylene terephthalate sheets are used as substrates to create a flexible sensor tag that can be applied to curved surfaces. A microfabricated antenna is integrated on the substrate in order to create a compact form factor. The sensor tags are fabricated using 315 MHz surface acoustic wave filters and photodiodes and tested with the aid of a fiber-coupled tungsten lamp. Microwave energy transmitted from a network analyzer is used to interrogate the sensor tag. Due to an electrical impedance mismatch at the SAW filter and sensor, energy is reflected at the sensor load and reradiated from the integrated antenna. By selecting sensors that change electrical impedance based on environmental conditions, the sensor state can be inferred through measurement of the reflected energy profile. Testing has shown that a calibrated system utilizing this type of sensor tag can detect distinct light levels wireless and passively. The authors also demonstrate simultaneous operation of two tags with different center passbands that detects light. Ranging tests show that the sensor tags can operate at a distance of at least 3.6 m.

Pharmacovigilance of drug allergy and hypersensitivity using the ENDA-DAHD database and the GALEN platform. The Galenda project

Nonallergic hypersensitivity and allergic reactions are part of the many different types of adverse drug reactions (ADRs). Databases exist for the collection of ADRs. Spontaneous reporting makes up the core data-generating system of pharmacovigilance, but there is a large under-estimation of allergy/hypersensitivity drug reactions. A specific database is therefore required for drug allergy and hypersensitivity using standard operating procedures (SOPs), as the diagnosis of drug allergy/hypersensitivity is difficult and current pharmacovigilance algorithms are insufficient. Although difficult, the diagnosis of drug allergy/hypersensitivity has been standardized by the European Network for Drug Allergy (ENDA) under the aegis of the European Academy of Allergology and Clinical Immunology and SOPs have been published. Based on ENDA and Global Allergy and Asthma European Network (GA(2)LEN, EU Framework Programme 6) SOPs, a Drug Allergy and Hypersensitivity Database (DAHD((R))) has been established under FileMaker((R)) Pro 9. It is already available online in many different languages and can be accessed using a personal login. GA(2)LEN is a European network of 27 partners (16 countries) and 59 collaborating centres (26 countries), which can coordinate and implement the DAHD across Europe. The GA(2)LEN-ENDA-DAHD platform interacting with a pharmacovigilance network appears to be of great interest for the reporting of allergy/hypersensitivity ADRs in conjunction with other pharmacovigilance instruments.

Landmark-based augmented reality system for paranasal and transnasal endoscopic surgeries

BACKGROUND: In this paper we present a landmark-based augmented reality (AR) endoscope system for endoscopic paranasal and transnasal surgeries along with fast and automatic calibration and registration procedures for the endoscope. METHODS: Preoperatively the surgeon selects natural landmarks or can define new landmarks in CT volume. These landmarks are overlaid, after proper registration of preoperative CT to the patient, on the endoscopic video stream. The specified name of the landmark, along with selected colour and its distance from the endoscope tip, is also augmented. The endoscope optics are calibrated and registered by fast and automatic methods. Accuracy of the system is evaluated in a metallic grid and cadaver set-up. RESULTS: Root mean square (RMS) error of the system is 0.8 mm in a controlled laboratory set-up (metallic grid) and was 2.25 mm during cadaver studies. CONCLUSIONS: A novel landmark-based AR endoscope system is implemented and its accuracy is evaluated. Augmented landmarks will help the surgeon to orientate and navigate the surgical field. Studies prove the capability of the system for the proposed application. Further clinical studies are planned in near future.

Increasing Realism and Supporting Content Planning for Dynamic Scenes in a Mixed Reality System incorporating a Time-of-Flight Camera

For broadcasting purposes MIXED REALITY, the combination of real and virtual scene content, has become ubiquitous nowadays. Mixed Reality recording still requires expensive studio setups and is often limited to simple color keying. We present a system for Mixed Reality applications which uses depth keying and provides threedimensional mixing of real and artificial content. It features enhanced realism through automatic shadow computation which we consider a core issue to obtain realism and a convincing visual perception, besides the correct alignment of the two modalities and correct occlusion handling. Furthermore we present a possibility to support placement of virtual content in the scene. Core feature of our system is the incorporation of a TIME-OF-FLIGHT (TOF)-camera device. This device delivers real-time depth images of the environment at a reasonable resolution and quality. This camera is used to build a static environment model and it also allows correct handling of mutual occlusions between real and virtual content, shadow computation and enhanced content planning. The presented system is inexpensive, compact, mobile, flexible and provides convenient calibration procedures. Chroma-keying is replaced by depth-keying which is efficiently performed on the GRAPHICS PROCESSING UNIT (GPU) by the usage of an environment model and the current ToF-camera image. Automatic extraction and tracking of dynamic scene content is herewith performed and this information is used for planning and alignment of virtual content. An additional sustainable feature is that depth maps of the mixed content are available in real-time, which makes the approach suitable for future 3DTV productions. The presented paper gives an overview of the whole system approach including camera calibration, environment model generation, real-time keying and mixing of virtual and real content, shadowing for virtual content and dynamic object tracking for content planning.

Occurrence of vasospasm and infarction in relation to a focal monitoring sensor in patients after SAH: placing a bet when placing a probe?

INTRODUCTION Vasospastic brain infarction is a devastating complication of aneurysmal subarachnoid hemorrhage (SAH). Using a probe for invasive monitoring of brain tissue oxygenation or blood flow is highly focal and may miss the site of cerebral vasospasm (CVS). Probe placement is based on the assumption that the spasm will occur either at the dependent vessel territory of the parent artery of the ruptured aneurysm or at the artery exposed to the focal thick blood clot. We investigated the likelihood of a focal monitoring sensor being placed in vasospasm or infarction territory on a hypothetical basis. METHODS From our database we retrospectively selected consecutive SAH patients with angiographically proven (day 7-14) severe CVS (narrowing of vessel lumen >50%). Depending on the aneurysm location we applied a standard protocol of probe placement to detect the most probable site of severe CVS or infarction. We analyzed whether the placement was congruent with existing CVS/infarction. RESULTS We analyzed 100 patients after SAH caused by aneurysms located in the following locations: MCA (n = 14), ICA (n = 30), A1CA (n = 4), AcoA or A2CA (n = 33), and VBA (n = 19). Sensor location corresponded with CVS territory in 93% of MCA, 87% of ICA, 76% of AcoA or A2CA, but only 50% of A1CA and 42% of VBA aneurysms. The focal probe was located inside the infarction territory in 95% of ICA, 89% of MCA, 78% of ACoA or A2CA, 50% of A1CA and 23% of VBA aneurysms. CONCLUSION The probability that a single focal probe will be situated in the territory of severe CVS and infarction varies. It seems to be reasonably accurate for MCA and ICA aneurysms, but not for ACA or VBA aneurysms.

NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques

In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.

The Virtual Skeleton Database: An Open Access Repository for Biomedical Research and Collaboration

Background: Statistical shape models are widely used in biomedical research. They are routinely implemented for automatic image segmentation or object identification in medical images. In these fields, however, the acquisition of the large training datasets, required to develop these models, is usually a time-consuming process. Even after this effort, the collections of datasets are often lost or mishandled resulting in replication of work. Objective: To solve these problems, the Virtual Skeleton Database (VSD) is proposed as a centralized storage system where the data necessary to build statistical shape models can be stored and shared. Methods: The VSD provides an online repository system tailored to the needs of the medical research community. The processing of the most common image file types, a statistical shape model framework, and an ontology-based search provide the generic tools to store, exchange, and retrieve digital medical datasets. The hosted data are accessible to the community, and collaborative research catalyzes their productivity. Results: To illustrate the need for an online repository for medical research, three exemplary projects of the VSD are presented: (1) an international collaboration to achieve improvement in cochlear surgery and implant optimization, (2) a population-based analysis of femoral fracture risk between genders, and (3) an online application developed for the evaluation and comparison of the segmentation of brain tumors. Conclusions: The VSD is a novel system for scientific collaboration for the medical image community with a data-centric concept and semantically driven search option for anatomical structures. The repository has been proven to be a useful tool for collaborative model building, as a resource for biomechanical population studies, or to enhance segmentation algorithms.

User and Machine Authentication and Authorization Infrastructure for Distributed Wireless Sensor Network Testbeds

The intention of an authentication and authorization infrastructure (AAI) is to simplify and unify access to different web resources. With a single login, a user can access web applications at multiple organizations. The Shibboleth authentication and authorization infrastructure is a standards-based, open source software package for web single sign-on (SSO) across or within organizational boundaries. It allows service providers to make fine-grained authorization decisions for individual access of protected online resources. The Shibboleth system is a widely used AAI, but only supports protection of browser-based web resources. We have implemented a Shibboleth AAI extension to protect web services using Simple Object Access Protocol (SOAP). Besides user authentication for browser-based web resources, this extension also provides user and machine authentication for web service-based resources. Although implemented for a Shibboleth AAI, the architecture can be easily adapted to other AAIs.

The Houston Academy of Medicine--Texas Medical Center Library management information system.

A management information system (MIS) provides a means for collecting, reporting, and analyzing data from all segments of an organization. Such systems are common in business but rare in libraries. The Houston Academy of Medicine-Texas Medical Center Library developed an MIS that operates on a system of networked IBM PCs and Paradox, a commercial database software package. The data collected in the system include monthly reports, client profile information, and data collected at the time of service requests. The MIS assists with enforcement of library policies, ensures that correct information is recorded, and provides reports for library managers. It also can be used to help answer a variety of ad hoc questions. Future plans call for the development of an MIS that could be adapted to other libraries' needs, and a decision-support interface that would facilitate access to the data contained in the MIS databases.