Showing papers presented at "IEEE Aerospace Conference in 2009"

A diagnostic approach for electro-mechanical actuators in aerospace systems

Abstract: Electro-mechanical actuators (EMA) are finding increasing use in aerospace applications, especially with the trend towards all all-electric aircraft and spacecraft designs. However, electro-mechanical actuators still lack the knowledge base accumulated for other fielded actuator types, particularly with regard to fault detection and characterization. This paper presents a thorough analysis of some of the critical failure modes documented for EMAs and describes experiments conducted on detecting and isolating a subset of them. The list of failures has been prepared through an extensive Failure Modes and Criticality Analysis (FMECA) reference, literature review, and accessible industry experience. Methods for data acquisition and validation of algorithms on EMA test stands are described. A variety of condition indicators were developed that enabled detection, identification, and isolation among the various fault modes. A diagnostic algorithm based on an artificial neural network is shown to operate successfully using these condition indicators and furthermore, robustness of these diagnostic routines to sensor faults is demonstrated by showing their ability to distinguish between them and component failures. The paper concludes with a roadmap leading from this effort towards developing successful prognostic algorithms for electromechanical actuators.

Evaluating algorithm performance metrics tailored for prognostics

Abstract: Prognostics has taken center stage in Condition Based Maintenance (CBM) where it is desired to estimate Remaining Useful Life (RUL) of a system so that remedial measures may be taken in advance to avoid catastrophic events or unwanted downtimes. Validation of such predictions is an important but difficult proposition and a lack of appropriate evaluation methods renders prognostics meaningless. Evaluation methods currently used in the research community are not standardized and in many cases do not sufficiently assess key performance aspects expected out of a prognostics algorithm. In this paper we introduce several new evaluation metrics tailored for prognostics and show that they can effectively evaluate various algorithms as compared to other conventional metrics. Four prognostic algorithms, Relevance Vector Machine (RVM), Gaussian Process Regression (GPR), Artificial Neural Network (ANN), and Polynomial Regression (PR), are compared. These algorithms vary in complexity and their ability to manage uncertainty around predicted estimates. Results show that the new metrics rank these algorithms in a different manner; depending on the requirements and constraints suitable metrics may be chosen. Beyond these results, this paper offers ideas about how metrics suitable to prognostics may be designed so that the evaluation procedure can be standardized.

Towards prognostics for electronics components

Abstract: Electronics components have an increasingly critical role in avionics systems and in the development of future aircraft systems. Prognostics of such components is becoming a very important research field as a result of the need to provide aircraft systems with system level health management information. This paper focuses on a prognostics application for electronics components within avionics systems, and in particular its application to an Isolated Gate Bipolar Transistor (IGBT). This application utilizes the remaining useful life prediction, accomplished by employing the particle filter framework, leveraging data from accelerated aging tests on IGBTs. These tests induced thermal-electrical overstresses by applying thermal cycling to the IGBT devices. In-situ state monitoring, including measurements of steady-state voltages and currents, electrical transients, and thermal transients are recorded and used as potential precursors of failure.

A bundle of problems

Abstract: Delay-Tolerant Networking” (DTN) is a neologism used for a new store-and-forward architecture and protocol suite intended for disrupted networks where there is intermittent or ad-hoc connectivity. This has been proposed as one approach to supporting delay-tolerant networks. Work in the late 1990s on the “Interplanetary Internet” forms the basis for current DTN protocols and architecture. That early work considered transport protocols robust to the hours-long propagation delays of deep-space communications. DTN is also known, primarily in military circles, as Disruption-Tolerant Networking, due to the dynamic links and outages in the military tactical environment, rather than long-delay links. In both cases, DTN technologies are well-suited to applications that are mostly asynchronous and insensitive to large variations in delivery conditions. DTN networks differ sufficiently from traditional terrestrial networks in their characteristics and connectivity that link, network and transport protocols must be carefully considered and chosen to cope with these different characteristics, or new protocols can be designed that are suited for the problems that these DTN network conditions impose. The “Bundle Protocol” exists within the DTN architecture, which sends bundles over subnet-specific transport protocols, called “convergence layers.” “Bundling” has undergone a large amount of shared development and design over a period of years as a research effort. We examine the Bundle Protocol and its related architecture closely, and discuss areas where we have found that the current Bundle approach is not well-suited to many of the operational concepts that it was intended to support. Problems with the Bundle Protocol and its convergence layers exist in mechanisms for error detection and overall reliability. This weakens the Bundle Protocol's suitability to disrupted and error-prone networks. We show that these reliability issues can lead to performance problems in DTN networks, requiring mitigation. Open research and development areas also exist with design choices in handling timing information, in determining necessary and sufficient security mechanisms, in its Quality of Service capabilities, and in other aspects of application or content identification. We show that the existing DTN bundling architecture has a number of open real-world deployment issues that can be addressed. We suggest possible remediation strategies for these weak areas of the bundle protocol that we have been working on. We also look at alternate approaches to DTN networking. Rather than only providing criticism, this paper identifies open issues, where work on modifying the Bundle Protocol is encouraged and approaches to address its various problems are suggested.

Methodologies for uncertainty management in prognostics

Abstract: Effective uncertainty management processes are essential elements in the design of prognostic modules if they to be viable for Integrated Vehicle Health Management (IVHM) systems. Modeling uncertainty, measurement and estimation uncertainties, future load uncertainty, among other factors, all potentially contribute to prognostic uncertainty. This paper analyzes the source of uncertainties in typical IVHM systems and presents a rigorous set of algorithms for uncertainty management that are generic and capable of addressing a variety of uncertainty sources. Specifically, model parameter uncertainty is addressed by a Bayesian-based updating scheme with two variants. One approach utilizes an inner-outer loop Monte Carlo simulation scheme with hyper-parameter adaptation and is intended for off-line applications, while the other particle filtering-based approach can be implemented on-line in real-time. Modeling uncertainty (or model structure uncertainty) is addressed by a Bayesian model selection/fusion method. Effective approaches for handling diagnostic uncertainty and the aggregation of component level uncertainty to system level are also addressed. Select results for the application of particular algorithms are presented.

Modeling and detection techniques for Counter-Terror Social Network Analysis and Intent Recognition

Abstract: In this paper, we describe our approach and initial results on modeling, detection, and tracking of terrorist groups and their intents based on multimedia data. While research on automated information extraction from multimedia data has yielded significant progress in areas such as the extraction of entities, links, and events, less progress has been made in the development of automated tools for analyzing the results of information extraction to “connect the dots.” Hence, our Counter-Terror Social Network Analysis and Intent Recognition (CT-SNAIR) work focuses on development of automated techniques and tools for detection and tracking of dynamically-changing terrorist networks as well as recognition of capability and potential intent. In addition to obtaining and working with real data for algorithm development and test, we have a major focus on modeling and simulation of terrorist attacks based on real information about past attacks. We describe the development and application of a new Terror Attack Description Language (TADL), which is used as a basis for modeling and simulation of terrorist attacks. Examples are shown which illustrate the use of TADL and a companion simulator based on a Hidden Markov Model (HMM) structure to generate transactions for attack scenarios drawn from real events. We also describe our techniques for generating realistic background clutter traffic to enable experiments to estimate performance in the presence of a mix of data. An important part of our effort is to produce scenarios and corpora for use in our own research, which can be shared with a community of researchers in this area. We describe our scenario and corpus development, including specific examples from the September 2004 bombing of the Australian embassy in Jakarta and a fictitious scenario which was developed in a prior project for research in social network analysis. The scenarios can be created by subject matter experts using a graphical editing tool. Given a set of time ordered transactions between actors, we employ social network analysis (SNA) algorithms as a filtering step to divide the actors into distinct communities before determining intent. This helps reduce clutter and enhances the ability to determine activities within a specific group. For modeling and simulation purposes, we generate random networks with structures and properties similar to real-world social networks. Modeling of background traffic is an important step in generating classifiers that can separate harmless activities from suspicious activity. An algorithm for recognition of simulated potential attack scenarios in clutter based on Support Vector Machine (SVM) techniques is presented. We show performance examples, including probability of detection versus probability of false alarm tradeoffs, for a range of system parameters.

ATHLETE: A cargo and habitat transporter for the moon

Abstract: As part of the NASA Exploration Technology Development Program, the Jet Propulsion Laboratory is developing a vehicle called ATHLETE: the All-Terrain Hex-Limbed Extra-Terrestrial Explorer. The vehicle concept is based on six wheels at the ends of six multi-degree-of-freedom limbs. Because each limb has enough degrees of freedom for use as a general-purpose leg, the wheels can be locked and used as feet to walk out of excessively soft or other extreme terrain. Since the vehicle has this alternative mode of traversing through (or at least out of) extreme terrain, the wheels and wheel actuators can be sized only for nominal terrain. There are substantial mass savings in the wheels and wheel actuators associated with designing for nominal instead of extreme terrain. These mass savings are comparable-to or larger-than the extra mass associated with the articulated limbs. As a result, the entire mobility system, including wheels and limbs, can be about 25% lighter than a conventional mobility chassis for planetary exploration. A side benefit of this approach is that each limb has sufficient degrees-of-freedom for use as a general-purpose manipulator (hence the name “limb” instead of “leg”). Our prototype ATHLETE vehicles have quick-disconnect tool adapters on the limbs that allow tools to be drawn out of a “tool belt” and maneuvered by the limb. A rotating power-take-off from the wheel actuates the tools, so that they can take advantage of the 1+ horsepower motor in each wheel to enable drilling, gripping or other power-tool functions.

A Radar Terminal Descent Sensor for the Mars Science Laboratory mission

Abstract: The soft-touchdown, “sky-crane” concept employed by the 2009 NASA Mars Science Laboratory mission requires an order-of-magnitude improvement from previous missions in the sensing of vehicle velocity and altitude. This paper describes the development of a new radar “Terminal Descent Sensor” that provides decimeterper-second velocity accuracy while also providing better than 2% range accuracy on six unique beams. This sensor design uses a millimeter-wave center frequency (Ka-band) and pencil beam antennas to achieve the required velocity precision and to overcome the problems that angle-of-arrival errors can cause in velocity reconstruction. Included are discussions of the design concept, driving requirements, hardware architecture, and results from a high fidelity performance simulation.

Situation aware UAV mission route planning

Abstract: This paper outlines an agent based approach for UAV (Unmanned Air Vehicles) mission route planning problem. In this context, mission route planning can be defined as finding the “best” set of waypoints for the UAV that will enhance its probability of success in its mission. Mission route planning may be carried out either in premission or in mission time. It may be done either by an onboard control system or by a ground mission planning system. Regardless of these considerations, a problem solving agent for UAV mission route planning problem is proposed in this research. Mission Route Planning Agent in UAV mission route planning context needs to perceive the elements in its environment and comprehend the meaning of this situation to compute a route. In other words, it will use target, threat, terrain and air space restrictions to compute the “best” route for that UAV mission. In a dynamic replanning environment, it will compute its new route again and again each time the situation has changed. To compute the “best” route, an A* based graph search algorithm is used. For a node, while real cost is computed using fuel and threat costs with determined weightings, heuristic cost is selected as the geometric distance. Network is constructed in the search time. Consecutive nodes are determined by spanning range and azimuth with determined increments. The values of weightings for fuel and threat costs and the increments used to construct the network have a great effect on the resulting route and the computation time. While common practice is to use default or user defined values for those, this paper presents a situation aware UAV Mission Route Planning Agent that uses the tactical situation to determine these values.

Small Class-D spacecraft thermal design, test and analysis - PharmaSat biological experiment

Abstract: Small spacecraft have been increasing in popularity because of their low cost, short turnaround and relative efficiency. In the past, small spacecraft have been primarily used for technology demonstrations, but advances in technology have made the miniaturization of space science possible [1,2].

Particle filter based anomaly detection for aircraft actuator systems

Abstract: This paper describes the background, simulation and experimental evaluation of an anomaly detector for Brushless DC motor winding insulation faults in the context of an aircraft Electro-Mechanical Actuator (EMA) application. Results acquired from an internal Failure Modes and Effects Analysis (FMEA) study identified turn-to-turn winding faults as the primary mechanism, or mode, of failure. Physics-of-failure mechanisms used to develop a model for the identified fault are provided. The model was implemented in Simulink to simulate the dynamics of the motor with a turn-to-turn insulation winding fault. Then, an experimental test procedure was devised and executed to validate the model. Additionally, a diagnostic feature, identified by the fault model and derived using Hilbert transforms, was validated using the Simulink model and experimental data for several fault dimensions. Next, a feature extraction routine preprocesses monitoring parameters and passes the resulting features to a particle filter. The particle filter, based on Bayesian estimation theory, allows for representation and management of uncertainty in a computationally efficient manner. The resulting anomaly detection routine declares a fault only when a specified confidence level is reached at a given false alarm rate. Finally, the real-time performance of the anomaly detector is evaluated using LabVIEW.

Optimization by Design of Experiment techniques

Abstract: Design of Experiments (DOE) is a statistical technique for quickly optimizing performance of systems with known input variables. It starts with a screening experimental design test plan involving all of the known factors that are suspected to affect the system's performance (or output). When the number of input variables or test factors is large, the primary experimental objective is to pare this number down into a manageable few. This is usually followed by another designed experiment design or test plan with the objective of optimizing the system's performance. The most common initial and final optimization designs of experiment are called the Screening Design and the Response Surface Method (RSM). This paper will present some examples in the use of these designs.

Experimental and analytical development of health management for Electro-Mechanical Actuators

Abstract: Expanded deployment of Electro-Mechanical Actuators (EMAs) in critical applications has created much interest in EMA Prognostic Health Management (PHM), a key enabling technology of Condition Based Maintenance (CBM). As such, Impact Technologies, LLC is collaborating with the NASA Ames Research Center to perform a number of research efforts in support of NASA's Integrated Vehicle Health Management (IVHM) initiatives. These efforts have combined experimental test stand development, laboratory seeded fault testing, and physical model-based health monitoring in a comprehensive PHM system development strategy. This paper discusses two closely related EMA research programs being conducted by Impact and NASA Ames. The first of these efforts resulted in the creation of an electro-mechanical actuator test stand for the Prognostics Center of Excellence at the NASA Ames Research Center. The second effort is ongoing and is utilizing physics-based modeling techniques to develop an algorithm and software package toolset for PHM of aircraft EMA systems using a hybrid (virtual sensor) approach.

Standardized failure signature for a turbofan engine

Abstract: The capacity to master engines behavior is fundamental for a manufacturer to prove its efficiency in conception and maintenance capability. This understanding goes through the capacity to acquire and treat data flows produced by sensors for monitoring purposes.

Advanced diagnostics and prognostics for engine health monitoring

Abstract: Modern military and commercial aircraft require advanced diagnostic and prognostic schemes to determine engine performance in order to reduce operational and maintenance costs and improve aircraft down time. Condition Based Maintenance (CBM) can be performed on an aircraft when a fault/failure is detected. However, to streamline maintenance procedures and avoid unnecessary delays the engineers and maintainers need current and best estimates of engine performance and health before upcoming flights.

Behavioral competencies of highly regarded systems engineers at NASA

Abstract: Have you ever wondered why some systems engineers are successful and others aren't? In order to answer that question, NASA recently conducted a study of the behavioral competencies of highly regarded systems engineers working on different types of programs and projects in diverse environments across the agency. As projects become increasingly complex, NASA understands that it is vital to grow and develop a cadre of highly trained and skilled systems engineers who will be available to ensure the continued success of future missions. It is not enough to focus only on the science of engineering space systems, since that is only half the story. The other half of the story is the art of systems engineering. But what does that entail?

Introducing photonics in spacecraft engineering: ESA's strategic approach

Abstract: Photonic Technologies in the form of fiber optics, integrated optics and micro-photonics offer some compelling advantages when considered for use in spacecraft. Since 2002 the European Space Agency has engaged in a comprehensive Research and Development program in Photonics that covers applications in communications, sensing, signal processing as well as in some specialized applications. The Research and Development program has been accompanied with the first in-flight demonstrations as well as with the first operational use of fiber optics as critical element of a satellite payload. Fiber optic digital communications for all types of data rates is the first application of Photonics that will reach space qualification. Analog signal communication will follow together with fiber optic sensing. Signal processing applications including Rf down-conversion, switching and analog to digital conversion with electro-photonic means are also under development and their potentials remain to be assessed in comparison with the evolving electronic approaches.

The Phoenix Mars Lander Robotic Arm

Abstract: The Phoenix Mars Lander Robotic Arm (RA) has operated for 149 sols since the Lander touched down on the north polar region of Mars on May 25, 2008. During its mission it has dug numerous trenches in the Martian regolith, acquired samples of Martian dry and icy soil, and delivered them to the Thermal Evolved Gas Analyzer (TEGA) and the Microscopy, Electrochemistry, and Conductivity Analyzer (MECA). The RA inserted the Thermal and Electrical Conductivity Probe (TECP) into the Martian regolith and positioned it at various heights above the surface for relative humidity measurements. The RA was used to point the Robotic Arm Camera to take images of the surface, trenches, samples within the scoop, and other objects of scientific interest within its workspace. Data from the RA sensors during trenching, scraping, and trench cave-in experiments have been used to infer mechanical properties of the Martian soil. This paper describes the design and operations of the RA as a critical component of the Phoenix Mars Lander necessary to achieve the scientific goals of the mission.

GRAIL: Gravity mapping the moon

Abstract: The Gravity Recovery and Interior Laboratory (GRAIL) mission is the most recently selected NASA Discovery mission. The GRAIL mission will utilize two spacecraft flying in tandem to provide a crust-to-core lunar gravity map. This lunar gravity map will provide important insight into the evolution of the Moon and other planetary bodies. The mission is currently in development with a September 2011 planned launch. The GRAIL mission concept is based on heritage from the GRACE instrument being used to map the gravity of the Earth. The spacecraft bus is based on a heritage system used successfully by Lockheed-Martin, the spacecraft contractor. This paper will discuss the science return expected from the GRAIL mission and provide an overview of the spacecraft system and mission design being developed to implement this exciting Discovery mission.

Exploring the use of a test automation framework

Abstract: It is known that software testers, more often than not, lack the time needed to fully test the delivered software product within the time period allotted to them. When problems in the implementation phase of a development project occur, it normally causes the software delivery date to slide. As a result, testers either need to work longer hours, or supplementary resources need to be added to the test team in order to meet aggressive test deadlines. One solution to this problem is to provide testers with a test automation framework to facilitate the development of automated test solutions.

A look inside the Juno Mission to Jupiter

Abstract: Juno, the second mission within the New Frontiers Program, is a Jupiter polar orbiter mission designed to return high-priority science data that spans across multiple divisions within NASA's Science Mission Directorate. Juno's science objectives, coupled with the natural constraints of a cost-capped, PI-led mission and the harsh environment of Jupiter, have led to a very unique mission and spacecraft design. The mission and spacecraft design accommodates the required payload suite of instruments in a way that maximizes science data collection and return, maintains a simplified orbital operations approach, and meets the many challenges associated with operating a spin-stabilized, solar-powered spacecraft in Jupiter's high radiation and magnetic environment. The project's efforts during the preliminary design phase have resulted in an integrated design and operations approach that meets all science objectives, retains significant technical, schedule and cost margins, and has retired key risks and challenges. As a result, Juno has been authorized to proceed with the detailed design phase and work toward an August 2011 launch.

Improved target tracking with road network information

Abstract: In this paper we consider the problem of tracking targets, which can move both on-road and off-road, with particle filters utilizing the road-network information. It is argued that the constraints like speed-limits and/or one-way roads generally incorporated into on-road motion models make it necessary to consider additional high-bandwidth off-road motion models. This is true even if the targets under consideration are only allowed to move on-road due to the possibility of imperfect road-map information and drivers violating the traffic rules. The particle filters currently used struggles during sharp mode transitions, with poor estimation quality as a result. This is due to the fact the number of particles allocated to each motion mode is varying according to the mode probabilities. A recently proposed interacting multiple model (IMM) particle filtering algorithm, which keeps the number of particles in each mode constant irrespective of the mode probabilities, is applied to this problem and its performance is compared to a previously existing algorithm. The results of the simulations on a challenging bearing-only tracking scenario show that the proposed algorithm, unlike the previously existing algorithm, can achieve good performance even under the sharpest mode transitions.

On-board multi-objective mission planning for Unmanned Aerial Vehicles

Abstract: A system for automated mission planning is presented with a view to operate Unmanned Aerial Vehicles (UAVs) in the National Airspace System (NAS). This paper describes methods for modelling decision variables, for enroute flight planning under Visual Flight Rules (VFR). For demonstration purposes, the task of delivering a medical package to a remote location was chosen. Decision variables include fuel consumption, flight time, wind and weather conditions, terrain elevation, airspace classification and the flight trajectories of other aircraft. The decision variables are transformed, using a Multi-Criteria Decision Making (MCDM) cost function, into a single cost value for a grid-based search algorithm (e.g. A*). It is shown that the proposed system provides a means for fast, autonomous generation of near-optimal flight plans, which in turn are a key enabler in the operation of UAVs in the NAS.

Hazard Detection Methods for Lunar Landing

Abstract: The methods and experiences from the Apollo Program are fundamental building blocks for the development of lunar landing strategies for the Constellation Program. Each of the six lunar landing Apollo missions landed under near ideal lighting conditions. The astronauts visually performed terrain relative navigation while looking out of windows, and were greatly aided by external communication and well lit scenes. As the LM approached the landing site, the astronauts performed visual hazard detection and avoidance, also under near-ideal lighting conditions. The astronauts were looking out of the windows trying to the best of their ability to avoid rocks, slopes, and craters and find a safe landing location. NASA has expressed a desire for global lunar access for both crewed and robotic sortie lunar exploration missions [2] [3]. Early NASA architecture studies have identified the lunar poles as desirable locations for early lunar missions. These polar missions provide less than ideal lighting conditions that will significantly affect the way a crewed vehicle is to land at such locales. Consequently, a variety of hazard identification methods should be considered for use by the crew to ensure a high degree of safety. This paper discusses such identification methods applicable to the poorly lit polar lunar environment, better ensuring global access for the soon to be designed Lunar Lander Vehicle (LLV).

Cobra: A two-degree of freedom fiber optic positioning mechanism

Abstract: The Wide-Field Multi Object Spectrometer (WFMOS) along with corrective optics will mount in place of the Secondary Mirror of the Subaru telescope on Mauna Kea, Hawaii to allow simultaneous observations of cosmologic targets. It will conduct large scale Galactic Archeology and Dark Energy surveys to help unlock the secrets of the universe. The key enabler of the observations is an array of 2400 Cobra optic fiber positioners made from very small rotary motors which were developed for this purpose. Cobra is a two degree of freedom mechanism that can position an optical fiber in the prime focus of the telescope to a precision of 5 μm. It is a theta-phi style positioner containing two rotary piezo tube motors with one offset from the other, which enables the optic fiber to be placed anywhere in a small circular patrol region. The patrol diameter of the actuator is large enough to obtain 100% sky coverage of the close packed hex array pattern of positioners. The name Cobra was chosen because the positioner resembles a snake ready to strike.

Design and development of the first Quasi-Zenith Satellite attitude and orbit control system

Abstract: The Quasi-zenith Satellite (QZS-1) is the first Japanese first navigation satellite to demonstrate the technology for providing GPS interoperable and augmentation services around Japan and Oceania. The attitude and orbit control system (AOCS) of the QZS-1 has several features that improve the mission availability. The use of a star tracker in a GEO altitude orbit and yaw steering function for high inclination are important features. In addition, robust software can maintain nominal operation, even in cases where one failure would occur in attitude sensors, actuators, or the main computer. Furthermore, the intervals of reaction wheel momentum unloading and orbital maneuvers are maximized by optimizing the system design and considering disturbances, such as solar radiation pressure, orbital perturbations, and thrust variations. As described herein, we present an overview and the design results of the QZS-1 attitude and orbit control system.

Improved Hamiltonian Adaptive Control of spacecraft

Abstract: Spacecraft control is complicated by on-orbit inertia uncertainties. Considerable initial, on-orbit check-out time is required for identification of accurate system models enabling fine pointing. Smart, plug-n-play control algorithms should formulate smart control signals regardless of inertia. Adaptive control techniques provide such promise. Spacecraft control has been proposed to be adapted in the inertial frame based on estimated inertia to minimize tracking error. Due to unwieldy computations, later researchers suggested adapting the control in the body frame. This paper derives this later suggested approach using the recommended 9-parameter regression model for 3-axis spacecraft rotational maneuvers. Additionally, a new 6-parameter regression model is shown to be equivalent. A new, further-reduced 3-parameter regression model is demonstrated to yield similar performance. A new improved, simplified adaptive feedforward technique is developed and shown to provide superior performance. Following promising simulations, experimental verification is performed on a free-floating three-axis spacecraft simulator actuated by non-redundant, single-gimbaled control moment gyroscopes.

Multitarget detection and tracking using multi-sensor passive acoustic data

Abstract: This paper describes a Bayesian approach to detecting and tracking multiple moving targets using acoustic data from multiple passive arrays. Traditional undersea acoustic systems develop tracks at the single array level, requiring track association between nodes with nonlinear projections from measurement space to target space. In contrast, our nonlinear filtering approach fuses data at the measurement level and operates directly in the target state space. As such, this approach directly addresses both the nonlinear sensor to target state coupling as well as the ambiguities caused by bearings-only nature of the passive regime. In particular, our method better addresses these challenges by combining high-fidelity physics-based sensor statistical modeling, an innovative nonlinear Bayesian filter, and a unique method of handing the computational implementation.

On information measures based on particle mixture for optimal bearings-only tracking

Abstract: In this work we consider a target tracking scenario where a moving observer with a bearings-only sensor is tracking a target. The tracking performance is highly dependent on the trajectory of the sensor platform, and the problem is to determine how it should maneuver for optimal tracking performance. The problem is considered as a stochastic optimal control problem and two sub-optimal control strategies are presented based on the Information filter and the determinant of the information matrix as the optimization objective. Using the determinant of the information matrix as an objective function in the planning problem is equivalent to using differential entropy of the posterior target density when it is Gaussian. For the non-Gaussian case, an approximation of the differential entropy of a density represented by a particle mixture is proposed. Furthermore, a gradient approximation of the differential entropy is derived and used in a stochastic gradient search algorithm applied to the planning problem.

Broadband optical beam forming for airborne phased array antenna

Abstract: For enhanced communication on board aircraft, novel antenna systems with broadband satellite-based capabilities are required. The technology will enhance airline operations by providing in-flight connectivity for flight crew information and will bring live TV and high-speed Internet connectivity to passengers. The installation of such systems on board aircraft requires for aerodynamic reasons the development a very low-profile aircraft antenna, which can point to satellites anywhere in the upper hemisphere. Major keystones for the success of steerable low-profile antennas are multi-layer printed circuit boards (PCBs) with an array of broadband antenna elements, and compact micro-wave systems with appropriate beam steering capabilities. The present paper describes the development of a prototype 8x1 optical beam forming network using cascades of optical ring resonators as part of a breadboard Ku-band phased array antenna.