Distributed Compressed Sensing for Sensor Networks with Packet Erasures

We study two approaches to distributed compressed sensing for in-network data compression and signal reconstruction at a sink in a wireless sensor network where sensors are placed on a straight line. Communication to the sink is considered to be bandwidth-constrained due to the large number of devices. By using distributed compressed sensing for compression of the data in the network, the communication cost (bandwith usage) to the sink can be decreased at the expense of delay induced by the local communication necessary for compression. We investigate the relation between cost and delay given a certain reconstruction performance requirement when using basis pursuit denoising for reconstruction. Moreover, we analyze and compare the performance degradation due to erased packets sent to the sink of the two approaches.Comment: Paper accepted to GLOBECOM 201

Multisensor Poisson Multi-Bernoulli Filter for Joint Target-Sensor State Tracking

In a typical multitarget tracking (MTT) scenario, the sensor state is either assumed known, or tracking is performed in the sensor's (relative) coordinate frame. This assumption does not hold when the sensor, e.g., an automotive radar, is mounted on a vehicle, and the target state should be represented in a global (absolute) coordinate frame. Then it is important to consider the uncertain location of the vehicle on which the sensor is mounted for MTT. In this paper, we present a multisensor low complexity Poisson multi-Bernoulli MTT filter, which jointly tracks the uncertain vehicle state and target states. Measurements collected by different sensors mounted on multiple vehicles with varying location uncertainty are incorporated sequentially based on the arrival of new sensor measurements. In doing so, targets observed from a sensor mounted on a well-localized vehicle reduce the state uncertainty of other poorly localized vehicles, provided that a common non-empty subset of targets is observed. A low complexity filter is obtained by approximations of the joint sensor-feature state density minimizing the Kullback-Leibler divergence (KLD). Results from synthetic as well as experimental measurement data, collected in a vehicle driving scenario, demonstrate the performance benefits of joint vehicle-target state tracking.Comment: 13 pages, 7 figure

Compressed Sensing in Wireless Sensor Networks without Explicit Position Information

Reconstruction in compressed sensing relies on knowledge of a sparsifying transform. In a setting where a sink reconstructs a field based on measurements from a wireless sensor network, this transform is tied to the locations of the individual sensors, which may not be available to the sink during reconstruction. In contrast to previous works, we do not assume that the sink knows the position of each sensor to build up the sparsifying basis. Instead, we propose the use of spatial interpolation based on a predetermined sparsifying transform, followed by random linear projections and ratio consensus using local communication between sensors. For this proposed architecture, we upper bound the reconstruction error induced by spatial interpolation, as well as the reconstruction error induced by distributed compression. These upper bounds are then utilized to analyze the communication cost tradeoff between communication to the sink and sensor-to-sensor communication

Toward a Standard-Compliant Implementation for Consensus Algorithms in Vehicular Networks

Cooperative Intelligent Transport System (C-ITS) applications require a continuous exchange of information between road users and roadside infrastructures. In this regard, distributed consensus algorithms can play an essential role in the definition of the information exchange rules between an ITS station and its neighbors. Although the consensus approach for networked systems is well-established, the efficiency of consensus methods under real-world vehicular communication constraints is largely unknown. This paper provides an ITS standard-compliant framework for analysis of consensus algorithms in vehicular networks with an emphasis on the role of robustness to changes in network topology in highly dynamic and dense environments. Our simulations reveal that in regular traffic conditions, the implemented consensus algorithm is able to achieve good performances in terms of both convergence time and needed consensus iterations. However, numerical results demonstrate that under dense and high-mobility traffic conditions the frequent exchange of large amounts of range information increases the Channel Busy Ratio (CBR) of the vehicular network and reduces the effectiveness of the algorithm as well

Cooperative Localization of Vehicles without Inter-vehicle Measurements

While cooperation among vehicles can improve localization, standard communication technologies (e.g., 802.11p) cannot provide reliable range or angle measurements. To allow cooperation without explicit inter-vehicle measurements, we propose a cooperative localization method whereby vehicles track mobile features in the environment and use associations of features among vehicles to improve the vehicles\u27 localization accuracy. The proposed algorithm, which scales linearly in the number of vehicles and quadratically in the number of tracked features, shows superior localization performance compared to a non-cooperative approach

Two key polymorphisms in a newly discovered allele of the Vitis vinifera TPS24 gene are responsible for the production of the rotundone precursor α-guaiene

Rotundone was initially identified as a grape-derived compound responsible for the peppery aroma of Shiraz wine varieties. It has subsequently been found in black and white pepper and several other spices. Because of its potent aroma, the molecular basis for rotundone formation is of particular relevance to grape and wine scientists and industry. We have identified and functionally characterized in planta a sesquiterpene synthase, VvGuaS, from developing grape berries, and have demonstrated that it produces the precursor of rotundone, α-guaiene, as its main product. The VvGuaS enzyme is a novel allele of the sesquiterpene synthase gene, VvTPS24, which has previously been reported to encode VvPNSeInt, an enzyme that produces a variety of selinene-type sesquiterpenes. This newly discovered VvTPS24 allele encodes an enzyme 99.5% identical to VvPNSeInt, with the differences comprising just 6 out of the 561 amino acid residues. Molecular modelling of the enzymes revealed that two of these residues, T414 and V530, are located in the active site of VvGuaS within 4 Å of the binding-site of the substrate, farnesyl pyrophosphate. Mutation of these two residues of VvGuaS into the corresponding polymorphisms in VvPNSeInt results in a complete functional conversion of one enzyme into the other, while mutation of each residue individually produces an intermediate change in the product profile. We have therefore demonstrated that VvGuaS, an enzyme responsible for production of the rotundone precursor, α-guaiene, is encoded by a novel allele of the previously characterized grapevine gene VvTPS24 and that two specific polymorphisms are responsible for functional differences between VvTPS24 alleles

Writ(h)ing Images: Imagination, the Human Form, and the Divine in William Blake, Salman Rushdie, and Simon Louvish

In this paper, we address issues in segmentation Of remotely sensed LIDAR (LIght Detection And Ranging) data. The LIDAR data, which were captured by airborne laser scanner, contain 2.5 dimensional (2.5D) terrain surface height information, e.g. houses, vegetation, flat field, river, basin, etc. Our aim in this paper is to segment ground (flat field)from non-ground (houses and high vegetation) in hilly urban areas. By projecting the 2.5D data onto a surface, we obtain a texture map as a grey-level image. Based on the image, Gabor wavelet filters are applied to generate Gabor wavelet features. These features are then grouped into various windows. Among these windows, a combination of their first and second order of statistics is used as a measure to determine the surface properties. The test results have shown that ground areas can successfully be segmented from LIDAR data. Most buildings and high vegetation can be detected. In addition, Gabor wavelet transform can partially remove hill or slope effects in the original data by tuning Gabor parameters

Use of Microzonation to Site Facility on Low Angle Thrust and Associated Fault Bend Folding

The campus of the College of the Redwoods is located completely within the Little Salmon Fault Zone, designated by the State of California as an active fault. The College has been extensively investigated for fault rupture and other seismic hazards in 1989, 1993, 1997, 1998, and 1999. The Little Salmon Fault Zone bounds the College and consists of two main northwest-striking, northeastdipping, low-angle thrusts. The west splay daylights along the southwest edge of the campus and projects beneath it. A recurrence interval of 268 years and slip rate of 5+/-3 mm/yr is estimated by CDMG. Individual dip-slip displacements along the west trace are reported to be 12 to 15 feet (3.6 to 4.5 m). Movement on the Little Salmon fault (LSF) is accompanied by growth of broad asymmetric folds in the upper thrust sheet resulting in surface rupture, localized uplift and discreet fault-bend fold axial surfaces. College of the Redwoods is located approximately 8 miles (13 km) south of Eureka and 25 miles (40 km) north-northeast of Cape Mendocino and the Mendocino Triple Junction (MTJ) in northern California. The \u27MTJ is the point of transition fi-om strike-slip faulting of the San Andreas transform system to low-angle thrust faulting and folding associated with the convergent margin of the Cascadia Subduction Zone. Campus infrastructure is located along the base of the Humboldt Hill Anticline (HHA), a major faultbend fold of the Cascadia fold and thrust belt. A new learning resource center (LRC) is proposed for a location 400 feet (120 m) northeast of where the west trace of the LSF daylights and 200 feet (60 m) above the low-angle fault plane. Building setback and design recommendations to mitigate for both fault rupture hazards and fault-generated folding hazards are presented