We present a novel approach to use mountain drainage patterns for GPS-Denied navigation of small unmanned aerial systems (UAS) such as the ScanEagle, utilizing a down-looking fixed focus monocular imager. Our proposal allows extension of missions to GPS-denied mountain areas, with no assumption of human-made geographic objects. We leverage the analogy between mountain drainage patterns, human arteriograms, and human fingerprints, to match local drainage patterns to Graphics Processing Unit (GPU) rendered parallax occlusion maps of geo-registered radar returns (GRRR). Details of our actual GPU algorithm is beyond the subject of this paper, and is planned as a future paper. The matching occurs in real-time, while GRRR data is loaded on-board the aircraft pre-mission, so as not to require a scanning aperture radar during the mission. For recognition purposes, we represent a given mountain area with a set of spatially distributed mountain minutiae, i.e., details found in the drainage patterns, so that conventional minutiae-based fingerprint matching approaches can be used to match real-time camera image against template images in the training set. We use medical arteriography processing techniques to extract the patterns. The minutiae-based representation of mountains is achieved by first exposing mountain ridges and valleys with a series of filters and then extracting mountain minutiae from these ridges/valleys. Our results are experimentally validated on actual terrain data and show the effectiveness of minutiae-based mountain representation method. Furthermore, we study how to select landmarks for UAS navigation based on the proposed mountain representation and give a set of examples to show its feasibility. This research was in part funded by Rockwell Collins Inc.
KEYWORDS: Principal component analysis, Global Positioning System, Cameras, Geographic information systems, Navigation systems, Sensors, Signal to noise ratio, Algorithm development, Image segmentation, Roads
GPS is a critical sensor for Unmanned Aircraft Systems (UASs) due to its accuracy, global coverage and small hardware footprint, but is subject to denial due to signal blockage or RF interference. When GPS is unavailable, position, velocity and attitude (PVA) performance from other inertial and air data sensors is not sufficient, especially for small UASs. Recently, image-based navigation algorithms have been developed to address GPS outages for UASs, since most of these platforms already include a camera as standard equipage. Performing absolute navigation with real-time aerial images requires georeferenced data, either images or landmarks, as a reference. Georeferenced imagery is readily available today, but requires a large amount of storage, whereas collections of discrete landmarks are compact but must be generated by pre-processing. An alternative, compact source of georeferenced data having large coverage area is open source vector maps from which meta-objects can be extracted for matching against real-time acquired imagery. We have developed a novel, automated approach called MINA (Meta Image Navigation Augmenters), which is a synergy of machine-vision and machine-learning algorithms for map aided navigation. As opposed to existing image map matching algorithms, MINA utilizes publicly available open-source geo-referenced vector map data, such as OpenStreetMap, in conjunction with real-time optical imagery from an on-board, monocular camera to augment the UAS navigation computer when GPS is not available. The MINA approach has been experimentally validated with both actual flight data and flight simulation data and results are presented in the paper.
Today networks are too cumbersome due to the incoherent integration of various technologies developed over
time. Convergence of data, voice, and video has caused the retro-fitting of a network to support non-native traffic
types and this has led to sub-par performance for every traffic type. Fundamental changes are warranted to support
high bandwidth traffic. The network must guarantee end-to-end delivery and provide inherent protection within
the physical structure. We propose that the main traffic types of today's applications should be carried using
the following features: connection-oriented service, traffic grooming to fill those connection oriented pipes, and
forward error recovery with protection provided in the physical layer. We present some of our research results.
Although All-Optical Network (AON) are a viable technology for future telecommunication and data networks, it creates many security vulnerabilities that do not exist in traditional networks. Transparency and non regeneration features make attack detection and localization difficult, because the effects of an attack connection can propagate quickly to different parts of a transparent All-Optical Network. Among all attack types in AON, crosstalk attack's propagation capability is second to none. Quick detection and localization of such attack source can avoid losing large amounts of data in an All-Optical Network. However, to detect attack sources, it is not necessary to put monitors on all nodes. Since those connections affected by the attack connection would provide valuable information for diagnosis, we show that placing a relatively small number of monitors on a selected set of nodes in a network is sufficient to achieve the required level of performance. This paper introduces crosstalk attack model and monitor-segment concept. After showing a necessary and sufficient condition for one-OAF diagnosable AON, a new sparse monitor placement method is proposed.
Most research to date in survivable optical network design and
operation, focused on the failure of a single component such as a
link or a node. A double-link failure model in which any two links
in the network may fail in an arbitrary order was proposed
recently in literature. Three loop-back methods of
recovering from double-link failures were also presented. The
basic idea behind these methods is to pre-compute two backup
paths for each link on the primary paths and reserve resources on
these paths. Compared to protection methods for single-link
failure model, the protection methods for double-link failure
model require much more spare capacity. Reserving dedicated
resources on every backup path at the time of establishing primary
path itself would consume excessive resources.
In Ref. 2 and 3, we captured the various operational phases in
survivable WDM networks as a single integer programming based (ILP)
optimization problem. In this work, we extend our optimization framework to
include double-link failures. We use the double-link failure recovery methods
available in literature, employ backup multiplexing schemes to optimize
capacity utilization, and provide 100\% protection guarantee for double-link
failure recovery. We develop rules to identify scenarios when capacity sharing
among interacting demand sets is possible. Our results indicate that for the
double-link failure recovery methods, the shared-link protection scheme
provides 10-15\% savings in capacity utilization over the dedicated link
protection scheme which reserves dedicated capacity on two backup paths for
each link. We provide a way of adapting the heuristic based double-link
failure recovery methods into a mathematical framework, and use techniques to
improve wavelength utilization for optimal capacity usage.
The effects of an attack connection can propagate quickly to different parts of a transparent All-Optical Network. Such attacks affect the normal traffic and can either cause service degradation or outright service denial. Quick detection and localization of an attack source can avoid losing large amounts of data in an All-Optical Network. Attack monitors can collect the information from connections and nodes for diagnostic purpose. However, to
detect attack sources, it is not necessary to put monitors on all nodes. Since those connections affected by the attack connection would provide valuable information for diagnosis, we show that placing a relatively small number of monitors on a selected set of
nodes in a network is sufficient to achieve the required level of performance. However, the monitor placement, routing, and attack diagnosis are challenging problems which need research attention.
We, in this paper, first develop our models of crosstalk attack and monitor node. With these models, we prove the necessary and sufficient condition for one-crosstalk-attack diagnosable network. After that, we develop a scalable diagnosis method which can
localize the attack connection efficiently with sparse monitor
nodes.
Multicasting in the optical layer has gained significant importance in the recent years due to several factors. Most of the research work in this area concentrate either on minimizing the number of wavelengths required to meet a given static demand or on multicast route selection algorithms to achieve efficient utilization of fiber bandwidth. Very few significant research has been found, to the best of authors' knowledge, in developing an analytical model for evaluating the blocking performance of tree establishment in optical networks, which motivates this research. In this paper, an analytical model for evaluating the blocking performance of multicast tree establishment in time-space switched optical networks is developed. The performance of different switch architectures are then studied using the analytical model. it is observed that if the multicast tree has very low degree of branching, the blocking probability of establishing the tree is the same as that of establishing a path with same number of links.
This paper addresses the problem of dynamically establishing dependable low-rate traffic stream connections in WDM mesh networks with traffic grooming capabilities. To establish a dependable connection, we set up link-disjoint primary and backup traffic stream paths between the source and destination and use backup multiplexing to reduce the overhead of backup traffic streams. We present a dynamic algorithm to obtain the optimal spare capacity on a wavelength on a link when a number of backup traffic streams are multiplexed onto it. We propose two schemes for grooming traffic streams onto wavelengths: Mixed Primary-Backup Grooming Policy (MGP) and Segregated Primary-Backup Grooming Policy (SGP). We illustrate how these schemes can be applied in a WDM mesh network scenario along with a routing and wavelength assignment algorithm. We conduct simulation experiments to evaluate the effectiveness of the proposed schemes on different network topologies, using different routing and wavelength assignment methods. The effect of change in granularity and change in the number of alternate paths on the grooming policies are also presented. From the simulation results, it is inferred that SGP is useful in network topologies, such as mesh-torus, characterized by good connectivity and a good amount of traffic switching and mixing at the nodes. On the other hand, MGP is useful in network topologies, such as a ring, characterized by low connectivity and high load correlation.
In this paper, we analyze the performance of WDM networks with traffic grooming capabilities supporting low-rate circuit-switched traffic streams. Traffic grooming in WDM networks collectively refers to the multiplexing, demultiplexing and switching of lower-rate traffic streams onto high capacity lightpaths. Networks which perform grooming only at the OADMs present in the nodes are referred to as Constrained Grooming Networks. Networks whose nodes switch traffic streams between wavelengths and perform grooming at the OADMs are referred to as Sparse Grooming Networks. Given the network topology, the traffic matrix and the node locations of grooming and traffic stream switching, we present an analytical model, using link-independence and wavelength-independence assumptions, to calculate the blocking performance. We illustrate the benefits of sparse grooming over constrained grooming in the mesh-torus and ring network topologies, using both simulation and analytical results.
All-optical networks with wavelength-division multiplexing (WDM) are considered to be a promising technology for next generation transport networks, as they can satisfy the growing bandwidth demand caused primarily due to an explosive growth of web-related services over the Internet. As the traffic demand increases, survivability becomes an indispensable requirement in WDM transport networks. This motivates the need for addressing failure restoration as an integral part of optical network design and operation. To date, the design problems have considered a static traffic demand aimed at optimizing the network capacity and cost, assuming various cost and survivability models. In this paper, we formulate three operational phases viz., initial call setup, medium-term reconfiguration when connections are blocked, and long-term reconfiguration to optimize resource utilization for the existing traffic, as a single Integer Linear Programming (ILP) optimization problem. This integrated framework is an attractive formulation that captures both capacity optimization and service disruption aspect in the problem formulation.
Service availability is an indispensable requirement for many current and future applications over the Internet and hence has to be addressed as part of the optical QoS service model. Network service providers can offer varying classes of services based on the choice of protection employed which can vary from full protection to no protection. Based on the service classes, traffic in the network falls into one of the three classes viz., full protection, no protection and best-effort. The network typically relies on the best-effort traffic for maximizing revenue. We consider two variations on the best-effort class, (1) all connections are accepted and network tries to protect as many as possible and (2) a mix of protected and unprotected connections and the goal is to maximize revenue. In this paper, we present a mathematical formulation, that captures service differentiation based on lightpath protection, for revenue maximization in a wavelength routed backbone networks. Our approach also captures the service disruption aspect into the problem formulation, as there may be a penalty for disrupting currently working connections.
This paper addresses the issue of capacity fairness in WDM networks with traffic grooming capabilities, supporting lower- rate circuit-switched traffic streams. Traffic grooming in WDM networks, is defined as the act of multiplexing, demultiplexing and switching lower rate traffic streams onto higher capacity lightpaths. In such a network, in addition to add/drop and full wavelength switching features, some or all of the network nodes can be provided with the capability to switch lower-rate traffic streams from one wavelength on an input port to another wavelength on an output port. Call requests arrive randomly and can request a lower-rate traffic connection to be established between the node pair. The call requests that ask for capacity nearer to the full wavelength capacity are bound to experience higher blocking than those that ask for a smaller fraction. This difference in loss performance is more pronounced as the traffic switching capability of the network is increased. In this paper, we study the capacity fairness of existing dynamic wavelength assignment algorithms.
Wavelength-routed all-optical networks have been receiving significant attention for high-capacity transport applications. A good routing and wavelength assignment algorithm is critically important to improve the performance of wavelength-routed WDM networks. We study the blocking performance of fixed-paths least-congestion (FPLC) routing in multifiber WDM networks in this paper. A new analytical model based on the link-load correlation is developed to evaluate the blocking performance of the FPLC routing. The analytical model is a generalized model that can be used in both regular (e.g. mesh-torus) and irregular (e.g. NSFnet) networks. It is shown that the analytical results closely match the simulation results, which indicates that the model is adequate in analytically predicting the performance of the FPLC routing in different networks.
In this paper, we consider the problem of optimally placing a given number of wavelength converters on a path to minimize the call blocking probability. Using a simple performance model, we first prove that uniform spacing of converters is optimal for the end-to-end performance when link loads are uniform and independent. We then show that significant gains are achievable with optimal placement compared to random placement. For non-uniform link loads, we provide a dynamic programming algorithm for the optimal placement and compare the performance with random and uniform placement.
The wavelet transform is a popular signal processing technique, particularly due to its impressive results in data compression. Its usefulness includes two-dimensional data for use in image processing and three-dimensional data for use in video processing. In image processing, the current trends are for image sizes which require a substantial amount of computing power; an application processing a 1024 by 1024 standard quality image requires many millions of processing steps per image frame. When processing sequences of these images for video, the throughput required is considerable in order to attain even low display rates. Three-based architectures have been proposed to provide this throughput rate by processing pixels in a data parallel fashion. Each level of the wavelet transform is processed using an array or a plane of processing elements operating in parallel on shared or distributed data. The largest of these architectures, the plane-based H-tree design, provides a real-time, pipelineable implementation of the 2DWT, but is costly in terms of VLSI area due to its requirement of O(n2) processors for a n by n data-set. In this paper, we look at methods for improving the practicality of these architectures by reducing the required area for a given problem size. This is achieved by adding extra processors at the root of the tree, which allows processing of larger images with an insignificant addition of hardware in exchange for a detrimental effect on the processing speed. We conclude the paper by presenting area/time trade-offs which can be used to evaluate cost/performance specifications.
Robert Haralick, Arun Somani, Craig Wittenbrink, Robert Johnson, Kenneth Cooper, Linda Shapiro, Ihsin Phillips, Jenq Hwang, William Cheung, Yung Yao, Chung-Ho Chen, Larry Yang, Brian Daugherty, Bob Lorbeski, Kent Loving, Tom Miller, Larye Parkins, Steven Soos
KEYWORDS: Image processing, Machine vision, Process control, Telecommunications, Computer vision technology, Signal processing, Control systems, Data processing, Computer architecture, Binary data
The Proteus architecture is a highly parallel MIMD, multiple instruction, multiple-data machine, optimized for large granularity tasks such as machine vision and image processing The system can achieve 20 Giga-flops (80 Giga-flops peak). It accepts data via multiple serial links at a rate of up to 640 megabytes/second. The system employs a hierarchical reconfigurable interconnection network with the highest level being a circuit switched Enhanced Hypercube serial interconnection network for internal data transfers. The system is designed to use 256 to 1,024 RISC processors. The processors use one megabyte external Read/Write Allocating Caches for reduced multiprocessor contention. The system detects, locates, and replaces faulty subsystems using redundant hardware to facilitate fault tolerance. The parallelism is directly controllable through an advanced software system for partitioning, scheduling, and development. System software includes a translator for the INSIGHT language, a parallel debugger, low and high level simulators, and a message passing system for all control needs. Image processing application software includes a variety of point operators neighborhood, operators, convolution, and the mathematical morphology operations of binary and gray scale dilation, erosion, opening, and closing.
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