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Many sensors, such as range, sonar, radar, GPS and visual devices, produce measurements which are contaminated by outliers. This problem can be addressed by using fat-tailed sensor models, which account for the possibility of outliers. Unfortunately, all estimation algorithms belonging to the family of Gaussian filters (such as the widely-used extended Kalman filter and unscented Kalman filter) are...
In this paper, we propose a novel state estimation algorithm that is resilient to sparse data injection attacks and robust to additive and multiplicative modeling errors. By leveraging principles of robust optimization, we construct uncertainty sets that lead to tractable optimization solutions. As a corollary, we obtain a novel robust filtering algorithm when there are no attacks, which can be viewed...
A vision-based and straightforward parking space surveillance system is presented. In particular, the novelty of the approach lies in the use of self-driven and direct dissimilarity computing mechanisms based on image raw brightness. Notably, the parking occupancy is estimated in real-time by applying fast computed estimators that optimize a global dissimilarity measure over slot-centered parking...
Orthogonal frequency division multiplexing (OFD-M)based cognitive radio networks (CRNs) is a promising paradigm to increase spectrum efficiency and achieve flexible resource allocation. However, previous works either lack the consideration of channel uncertainties or ignore the effect of imperfect spectrum sensing. In this paper, we focus on the power control for a downlink OFDM-based CRN with the...
This paper introduces the observability radius of network systems, which measures the robustness of a network to perturbations of the edges. We consider linear networks, where the dynamics are described by a weighted adjacency matrix, and dedicated sensors are positioned at a subset of nodes. We allow for perturbations of certain edge weights, with the objective of preventing observability of some...
This article presents an accurate study about the validity of the tuning rule for symmetric-send-on-delta (SSOD) based PID controllers which was presented by the authors in a previous work. First we obtain the conditions under which the rule is valid and then we study its fulfillment for an extensive batch of 134 models. The results demonstrated that most of the models used in practical applications...
This manuscript describes a UAV implemented with vision and laser based localization algorithm to track and land on a moving platform. Specifically, a pre-designed marker is installed on the moving platform and a downward facing monocular camera is mounted on the UAV for pose estimation. For a robust and precise UAV height estimation, a LiDAR scanning range finder is utilized to determine accurate...
An estimation framework is presented that improves the robustness of GPS-denied state estimation to changing environmental conditions by fusing updates from multiple view-based odometry algorithms. This allows the vehicle to utilize a suite of complementary exteroceptive sensors or sensing modalities. By estimating the vehicle states relative to a local coordinate frame collocated with an odometry...
Information system (IS) agility has been consistently ranked high by executives in various surveys conducted in the past decade. However, the concept of agility lacks clarity and specification, which can hinder our efforts accumulating knowledge and comparing studies. Based on a comprehensive conceptualisation, we compare agility with commonly confused concepts such as flexibility, evaluate four key...
We present results of an improved smartphone based inertial navigation based indoor localization system. Spatial constraints drawn from domain specific knowledge for direction correction and actual velocity model for velocity correction are applied to increase the accuracy by counteracting the accumulation of large drift caused by sensor reading errors. We investigated the accuracy of the algorithm...
In this paper, we consider the problem of optimal opportunistic spectrum access using full-duplex (FD) radios in presence of uncertain primary user (PU) channel statistics and propose a Sensing-and-Selectively-Transmit protocol (SaST). To optimize its throughput, the SU sensing period has to be carefully tuned. However, in absence of the exact knowledge of PU activity statistics, under SaST, the PU's...
Compressed sensing, further to its ability of reducing resources spent in signal acquisition, may be seen as an implicit private-key encryption scheme. The level of achievable secrecy has been analyzed in the most classical settings, when the sensing matrix is made of independent and identically distributed entries. Yet, it is known that substantially improved acquisition can be achieved by tuning...
We report a rapid, robust full-wave methodology to model electromagnetic (EM) wave radiation by distributed current sources embedded in planar-layered media. Primitive causality-related numerical instabilities within the computation chain, induced by exponentially rising "distributed" current source spectrum functions, are addressed for both linear and aperture sources, leading to solution...
Spectrum Sensing is elementary function in Cognitive Radio Networks (CRN) to identify the white spaces in spectrum for opportunistic communication. In this paper, we proposed a novel two stage spectrum sensing under the environment as noise uncertainty. The robustness of uncertainty of noise power is one of the main challenges in spectrum sensing method. Since detection of primary users (PU) in the...
As the Global Navigation Satellite Systems (GNSS) are intensively used as main source of Position, Navigation and Timing (PNT) information for maritime and inland water navigation, it becomes increasingly important to ensure the reliability of GNSS-based navigation solutions for challenging environments. Although an intensive work has been done in developing GNSS Receiver Autonomous Integrity Monitoring...
We apply a pseudo-analytical algorithm to computing time-harmonic responses of steeply deviated triaxial electromagnetic induction sensors, used in the well-logging of hydrocarbon reserves, which are embedded in planar-layered media of general anisotropy and loss. Many geophysical parameter inversion techniques heavily rely upon repeated use of computational forward engines, whose robust accuracy...
Cooperative spectrum sensing, despite its effectiveness in enabling dynamic spectrum access, suffers from location privacy threats, merely because secondary users (SUs)' sensing reports that need to be shared with a fusion center to make spectrum availability decisions are highly correlated to the users' locations. It is therefore important that cooperative spectrum sensing schemes be empowered with...
This demo presents the Zephyr system for robust respiratory rate estimation that has been accepted in Infocom'16. Human respiratory rate is widely recognized as a vital measure of a patient's health and an indicator of several medical problems. However, it is usually ignored by medical practitioners due to limitations with available measurements techniques that are either visual counting by trained...
The registration of multi-source remote sensing images is a challenging and crucial problem in remote sensing field. An automatic registration based on genetic algorithm is presented in this paper. Firstly, Scale-Invariant Feature Transform Modification (SIFT-M) and global matching are used to initialize the candidate points. Next, Genetic Algorithm (GA) is utilized to exclude the mismatch pairs and...
With the advent of Internet of Things (IoT) Wireless Sensor Networks (WSN) seem to play key a role in the connectivity of smart objects. The limited resources of WSN devices and the increased demand for new and more sophisticated services call for new and more efficient architectures. The new architectures should ensure energy-efficiency, flexibility, reliability and robustness. We believe that using...
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