Mark R. Morelande

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Object/target tracking refers to the problem of using sensor measurements to determine the location, path and characteristics of objects of interest. A sensor can be any measuring device, such as radar, sonar, ladar, camera, infrared sensor, microphone, ultrasound or any other sensor that can be used to collect information about objects in the environment.(More)
This paper considers the problem of simultaneously detecting and tracking multiple targets. The problem can be formulated in a Bayesian framework and solved, in principle, by computation of the joint multitarget probability density (JMPD). In practice, exact computation of the JMPD is impossible, and the predominant challenge is to arrive at a(More)
Particle filter (PF) based multi-target tracking (MTT) methods suffer from the curse of dimensionality. Existing strategies to combat this assume posterior independence between target states, in order to then sample targets independently, or to perform joint sampling of closely spaced targets only. When many targets are in proximity, these strategies either(More)
Given an area where an unknown number of unaccounted radioactive sources potentially exist, and using gamma- radiation count measurements collected at known locations within this area, the problem is to estimate the number of sources as well as their locations and intensities. Two approaches are investigated. The first is based on the maximum likelihood(More)
An algorithm for scheduling and control of passive sensors is proposed. This algorithm is based on a partially observed Markov decision process and an expected short- or long-term reward given by the sum of Renyi information divergences between Gaussian densities. This allows effective and efficient implementations and is demonstrated on simulations of(More)
The paper is devoted to statistical analysis of vessel motion patterns in the ports and waterways using AIS ship self-reporting data. From the real historic AIS data we extract motion patterns which are then used to construct the corresponding motion anomaly detectors. This is carried out in the framework of adaptive kernel density estimation. The anomaly(More)
| This paper addresses the problem of sensor management for a large network of agile sensors. Sensor management, as defined here, is the process of dynamically retasking agile sensors in response to an evolving environment. Sensors may be agile in a variety of ways, e.g., the ability to reposition, point an antenna, choose sensing mode, or waveform. The(More)
We consider analytical modeling of the anterior corneal surface with a set of orthogonal basis functions that are a product of radial polynomials and angular functions. Several candidate basis functions were chosen from the repertoire of functions that are orthogonal in the unit circle and invariant in form with respect to rotation about the origin. In(More)
Node localisation in wireless sensor networks is a difficult problem due to the large number of parameters to be estimated and the nonlinear relationship between the measurements and the parameters. Assuming the presence of a number of anchor nodes with known positions and a centralised architecture, a Bayesian algorithm for node localisation in wireless(More)