239,756 research outputs found
Adaptive target birth intensity for PHD and CPHD filters
No full textThe standard formulation of the probability hypothesis density (PHD) and cardinalised PHD (CPHD) filters assumes that the target birth intensity is known a priori. In situations where the targets can appear anywhere in the surveillance volume this is clearly inefficient, since the target birth intensity needs to cover the entire state space. This paper presents a new extension of the PHD and CPHD filters, which distinguishes between the persistent and the newborn targets. This extension enables us to adaptively design the target birth intensity at each scan using the received measurements. Sequential Monte-Carlo (SMC) implementations of the resulting PHD and CPHD filters are presented and their performance studied numerically. The proposed measurement-driven birth intensity improves the estimation accuracy of both the number of targets and their spatial distribution
Convergence analysis of the Gaussian mixture PHD filter
No full textThe Gaussian mixture probability hypothesis density (PHD) filter was proposed recently for jointly estimating the time-varying number of targets and their states from a sequence of sets of observations without the need for measurement-to-track data association. It was shown that, under linear-Gaussian assumptions, the posterior intensity at any point in time is a Gaussian mixture. This paper proves uniform convergence of the errors in the algorithm and provides error bounds for the pruning and merging stages. In addition, uniform convergence results for the extended Kalman PHD Filter are given, and the unscented Kalman PHD Filter implementation is discussed. © 2007 IEEE.</p
A Metric for Performance Evaluation of Multi-Target Tracking Algorithms
No full textPerformance evaluation of multi-target tracking algorithms is of great practical importance in the design, parameter optimization and comparison of tracking systems. The goal of performance evaluation is to measure the distance between two sets of tracks: the ground truth tracks and the set of estimated tracks. This paper proposes a mathematically rigorous metric for this purpose. The basis of the proposed distance measure is the recently formulated consistent metric for performance evaluation of multi-target filters, referred to as the OSPA metric. Multi-target filters sequentially estimate the number of targets and their position in the state space. The OSPA metric is therefore defined on the space of finite sets of vectors. The distinction between filtering and tracking is that tracking algorithms output tracks and a track represents a labeled temporal sequence of state estimates, associated with the same target. The metric proposed in this paper is therefore defined on the space of finite sets of tracks and incorporates the labeling error. Numerical examples demonstrate that the proposed metric behaves in a manner consistent with our expectations.</p
Bernoulli Forward-Backward Smoothing for Joint Target Detection and Tracking
No full textIn this correspondence, we derive a forward-backward smoother for joint target detection and estimation and propose a sequential Monte Carlo implementation. We model the target by a Bernoulli random finite set since the target can be in one of two "present" or "absent" modes. Finite set statistics is used to derive the smoothing recursion. Our results indicate that smoothing has two distinct advantages over just using filtering: First, we are able to more accurately identify the appearance and disappearance of a target in the scene, and second, we can provide improved state estimates when the target exists.</p
A note on the reward function for PHD filters with sensor control
No full textThe context is sensor control for multi-object Bayes filtering in the framework of partially observed Markov decision processes (POMDPs). The current information state is represented by the multi-object probability density function (pdf), while the reward function associated with each sensor control (action) is the information gain measured by the alpha or Rényi divergence. Assuming that both the predicted and updated state can be represented by independent identically distributed (IID) cluster random finite sets (RFSs) or, as a special case, the Poisson RFSs, this work derives the analytic expressions of the corresponding Rényi divergence based information gains. The implementation of Rényi divergence via the sequential Monte Carlo method is presented. The performance of the proposed reward function is demonstrated by a numerical example, where a moving range-only sensor is controlled to estimate the number and the states of several moving objects using the PHD filter. © 2006 IEEE.</p
The VO-Neural project:. recent developments and some applications
No full textVO-Neural is the natural evolution of the Astroneural project which was started in 1994 with the aim to implement a suite of neural tools for data mining in astronomical massive data sets. At a difference with its ancestor, which was implemented under Matlab, VO-Neural is written in C++, object oriented, and it is specifically tailored to work in distributed computing architectures. We discuss the current status of implementation of VO-Neural, present an application to the classification of Active Galactic Nuclei, and outline the ongoing work to improve the functionalities of the package
Data association and track management for the gaussian mixture probability hypothesis density filter
No full textThe Gaussian mixture probability hypothesis density (GM-PHD) recursion is a closed-form solution to the probability hypothesis density (PHD) recursion, which was proposed for jointly estimating the time-varying number of targets and their states from a sequence of noisy measurement sets in the presence of data association uncertainty, clutter, and miss-detection. However the GM-PHD filter does not provide identities of individual target state estimates, that are needed to construct tracks of individual targets. In this paper, we propose a new multi-target tracker based on the GM-PHD filter, which gives the association amongst state estimates of targets over time and provides track labels. Various issues regarding initiating, propagating and terminating tracks are discussed. Furthermore, we also propose a technique for resolving identities of targets in close proximity, which the PHD filter is unable to do on its own. © 2006 IEEE.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Preparation of nanotextured VO 2[B] from vanadium oxide aerogels
No full textVanadium oxide aerogels were used as a precursor for preparing nanotextured VO 2[B] by low-temperature heat treatment under vacuum. The VO 2[B] material retains the fibrous morphology and high surface area of the aerogel. Evolution of the VO 2[B] phase, as studied by FTIR and X-ray diffraction, indicates that the local structure of the vanadium oxide aerogel is close to that of VO 2[B], in agreement with the bilayer-type structure previously proposed for vanadium oxide aerogels/xerogels. The electrochemical behavior of VO 2[B] also bears similarity to that of vanadium oxide aerogels. Specific capacities for lithium as high as 500 mA·h/g are obtained for nanocrystalline VO 2[B], and stable electrochemical response is obtained when cycled between 4 and 2.4 V vs Li +/Li 0. © 2006 American Chemical Society
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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