In this paper we examine an asynchronous networked estimation system for state estimation of continuous time stochastic processes. Such a system is comprised of several estimation nodes connected using a possibly inco...
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ISBN:
(纸本)9781479928569
In this paper we examine an asynchronous networked estimation system for state estimation of continuous time stochastic processes. Such a system is comprised of several estimation nodes connected using a possibly incomplete communication graph. Each of the nodes uses a Kalman filter algorithm and data from a local sensor to compute local state estimates of the process under observation. It also performs data fusion of local estimates and data received from other directly connected nodes. Asynchronism means that each node preforms measurement, estimation, and data fusion in moments of time that are independent of the work cycles of the other nodes.
This paper presents an occupancy grid tracking system based on particles, and the use of this system for dynamic obstacle detection in driving environments. The particles will have a dual nature - they will denote hyp...
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This paper presents an occupancy grid tracking system based on particles, and the use of this system for dynamic obstacle detection in driving environments. The particles will have a dual nature - they will denote hypotheses, as in the particle filtering algorithms, but they will also be the building blocks of our modeled world. The particles have position and speed, and they can migrate in the grid from cell to cell depending on their motion model and motion parameters, but they will also be created and destroyed using a weighting-resampling mechanism specific to particle filter algorithms. An obstacle grid derived from processing a stereovision-generated elevation map is used as measurement information, and the measurement model takes into account the uncertainties of the stereo reconstruction. The dynamic occupancy grid is used for improving the quality of the stereovision-based reconstruction as oriented cuboids. The resulted system is a flexible, real-time tracking solution for dynamic unstructured driving environments, and a useful tool for extracting intermediate dynamic information that can considerably improve object detection and tracking.
The GPS carrier phase observations are widely used for the high precision static and kinematic positioning applications. However, GPS signals are seriously distorted when passing through walls and other obstructions. ...
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The GPS carrier phase observations are widely used for the high precision static and kinematic positioning applications. However, GPS signals are seriously distorted when passing through walls and other obstructions. This paper focuses on this issue and outlines the research carried out to investigate the effects of some commonly used construction materials on the GPS signals. For the purpose of generating the multipath in a controlled manner, an experimental set-up is designed to test the effect of typical building surface materials (toughened glass, wood board, PVC board and ceramic tile) on positioning accuracy. The effects of signal attenuation on the accuracy of the positioning solution are explored by an improved particle filtering algorithm and some statistical methods, and reasons for these effects are further analyzed. The findings of the experimental results may be used to enhance the performance of GPS technology. (C) 2012 Elsevier Ltd. All rights reserved.
We propose a pitch track correction technique using a sigmoidal objective function in a particlefiltering framework. The conventional method for pitch track correction simply considers the peak locations of the autoc...
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ISBN:
(纸本)9781467317139
We propose a pitch track correction technique using a sigmoidal objective function in a particlefiltering framework. The conventional method for pitch track correction simply considers the peak locations of the autocorrelation functions as the pitch values and depends only on the longest reliable pitch streak. This constraint may induce pitch correction errors. The proposed approach uses particlefiltering to further correctly track the pitch values. To apply the particle filtering algorithm to pitch track correction, a method for the importance weight computation using a sigmoidal function on foreground streams is proposed. The similarity between the estimated pitch values and the subband signals are computed, and a sigmoid transfer function is used to convert it as a probability value. To verify the efficiency of our proposed approach, we carried out speech segregation experiments for mixtures of speech and various noise sources in various mixing signal-to-noise ratios (SNRs). With respect to several performance measures including SNR, energy loss ratio, and noise residue ratio of the segregated speech, the proposed method achieved superior performance compared to the conventional approach.
The paper proposes a carrier synchronization procedure for high-order QAM modulated signals that uses a decision-directed extended Kalman filtering (EKF) technique. The proposed method combines the Kalman filter with ...
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ISBN:
(纸本)9781467321242
The paper proposes a carrier synchronization procedure for high-order QAM modulated signals that uses a decision-directed extended Kalman filtering (EKF) technique. The proposed method combines the Kalman filter with a lock detector to establish the status of the synchronization process, modifying adaptively the Kalman filter parameters. As compared with the complete EKF filter, the proposed synchronization algorithm simplifies the Kalman measurement model to a single scalar equation reducing significantly the computational complexity of the algorithm. Simulations show that the simplified Kalman algorithm has equivalent synchronization performances with the complete EKF filter.
A multimodal radar varies its bandwidth (and hence resolution) based on the arrangement of target scattering features, possibly leaving unused bandwidth for other applications. In this paper, we explore bandwidth shar...
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ISBN:
(纸本)9781467310710
A multimodal radar varies its bandwidth (and hence resolution) based on the arrangement of target scattering features, possibly leaving unused bandwidth for other applications. In this paper, we explore bandwidth sharing scenarios between radar and communications. We divide the surveillance space into sectors and use fuzzy logic to arrive at priorities for each sector. Multi-objective optimization is used to arrive at solutions making the best use of available bandwidth between radar and communications. We also consider the problem of scheduling between tracking and surveillance for the multimodal radar. Smart scheduling is necessary to make the best use of available radar resources. We look at algorithms for special target scenarios. Tracking is performed using the particle filter algorithm.
We consider the problem of mobile sensor node localization and propose an unscented particle filter algorithm in wireless sensor networks (WSNs) consisting of mobile nodes and static anchor nodes. Because the received...
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ISBN:
(纸本)9781467358088
We consider the problem of mobile sensor node localization and propose an unscented particle filter algorithm in wireless sensor networks (WSNs) consisting of mobile nodes and static anchor nodes. Because the received signal strength (RSS) varies obviously, we employ particle filter to decrease the bad effect. We first form the system state model, mobile model, and RSS model, and then apply unscented particle filter and utilize the systematic resample to decrease the degeneration of the particle. We eliminate the uncertain of the RSS in wireless channel and get accurate location of mobile nodes. The predicted position of the mobile node is constrained by its velocity and the measurement value of RSS. We do a lot of simulation to validate the algorithm by assigning different parameters. Simulation results show that the algorithm enhances the localization accuracy of mobile node compared with the standard particle filter algorithm.
作者:
Ngoduy, D.Univ Leeds
Inst Transport Studies Leeds LS2 9JT W Yorkshire England
Real time traffic flow simulation models are used to provide traffic information for dynamic traffic management systems. Those simulation models are supplied by traffic data in order to estimate and predict traffic co...
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Real time traffic flow simulation models are used to provide traffic information for dynamic traffic management systems. Those simulation models are supplied by traffic data in order to estimate and predict traffic conditions in unobserved sections of a traffic network. In general, most of recent real time traffic simulators are based on the macroscopic model because the macroscopic model replicates the average traffic behavior in terms of observable variables such as (time-space) flow and speed at a relatively fast computational time. Like other simulation models, an important aspect of the real time macroscopic simulator is to calibrate the model parameters online. The most conventional way of the online calibration is to add a random walk to the parameters to constitute an augmentation of the traffic variables and the model parameters to be estimated. Actually, this method allows the parameters to vary at every time step and, therefore, describes the adaptation of the model to the prevailing traffic conditions. However, it has been reported that the use of the random walk results in a loss of information and an increase of the covariance of parameters, which consequently leads to posteriors that are far more diffuse than the theoretical posteriors for the true parameters. To this end, this article puts forward a Kernel density estimation technique in the calibration process to handle the covariance issue and to avoid the information loss. The Kernel density estimation technique is embedded in the particle filter algorithm, which is extended to the calibration problems. The proposed framework is investigated using real-life data collected in a freeway in England.
We propose a novel inference framework for finding maximal cliques in a weighted graph that satisfy hard constraints. The constraints specify the graph nodes that must belong to the solution as well as mutual exclusio...
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ISBN:
(纸本)9781618395993
We propose a novel inference framework for finding maximal cliques in a weighted graph that satisfy hard constraints. The constraints specify the graph nodes that must belong to the solution as well as mutual exclusions of graph nodes, i.e., sets of nodes that cannot belong to the same solution. The proposed inference is based on a novel particle filter algorithm with state permeations. We apply the inference framework to a challenging problem of learning part-based, deformable object models. Two core problems in the learning framework, matching of image patches and finding salient parts, are formulated as two instances of the problem of finding maximal cliques with hard constraints. Our learning framework yields discriminative part based object models that achieve very good detection rate, and outperform other methods on object classes with large deformation.
This paper presents a new approach to solve multi robot simultaneous localization and mapping (SLAM) problem by allowing fast and efficient features exchange among teammates. Each mate is able to build its own SLAM so...
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ISBN:
(纸本)9781457721366
This paper presents a new approach to solve multi robot simultaneous localization and mapping (SLAM) problem by allowing fast and efficient features exchange among teammates. Each mate is able to build its own SLAM solution by using feature based Rao-Blackwellised particle Filter algorithm. This scheme proposes that every feature extracted by individual mate should be shared with all team mates no matter that some features are viewed by more than one member. As the information exchange comprises only on small features set so the time taken to accommodate the information is small which makes it a good solution for distributed multi-robot system working with limited communication range and bandwidth. This paper presents experimental results for two different environments by using different platforms.
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