Computer graphics: principles and practice (2nd ed.)
Computer graphics: principles and practice (2nd ed.)
Information Theoretic Sensor Data Selection for Active Object Recognition and State Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
Feature Space Trajectory Methods for Active Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Sensor management using an active sensing approach
Signal Processing
A particle filter for joint detection and tracking of color objects
Image and Vision Computing
Information driven localisation of a radiological point source
Information Fusion
Foundations and Applications of Sensor Management
Foundations and Applications of Sensor Management
Discrimination gain to optimize detection and classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Least squares estimation techniques for position tracking of radioactive sources
Automatica (Journal of IFAC)
Brief Optimizing the receiver maneuvers for bearings-only tracking
Automatica (Journal of IFAC)
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The problem is to estimate the number of radioactive point sources in a specified area and to estimate their parameters (locations and magnitudes), using measurements collected by a low-cost Geiger-Muller counter. The measurements are Poisson distributed with the mean proportional to the radiation field intensity. The radiation field represents a superposition of background radiation and the source contributions subjected to the inverse distance squared attenuation. The solution is based on an information gain driven search which comprises a sequential Bayesian estimator coupled with a sensor/observer control unit. The control unit directs the observer(s) to move to new locations and acquire measurements that maximise the information gain in the Renyi divergence sense. The performance of the proposed information driven search, including a comparison with a unform search along a predefined path, is studied by simulations. A successful application of the proposed technique to experimental datasets, recently collected in the field trials, verifies the measurement model and the theoretical considerations.