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Risk-sensitive filter is a robust and numerically efficient algorithm compared to risk neutral filter with model uncertainties. For nonlinear plant, the square root unscented Kalman risk-sensitive filter (SUKRSF) is proposed in this paper by using unscented transformation approximation. Square root unscented Kalman filter (SRUKF), a derivative-free nonlinear estimation tool is used to solve risk-sensitive...
Indoor WLAN positioning should be modeled as a nonlinear and non-Gaussian dynamic system due to the complex indoor environment, radio propagation and motion behaviour. The aim of this paper is to analyze different filtering strategies for real life indoor WLAN positioning systems. The performance criteria for the comparison are the mean of localization errors and computational complexity. Three nonlinear...
The leader node particle filter is a partially distributed approach to tracking in a sensor network, in which the node performing the particle filter computations (the leader node) changes over time. The primary advantage is that the position of the leader node can follow the target, improving the efficiency of data collection. When the leader node changes, the particle filter must be communicated...
We consider the placement of sensors with circular sensing regions for q-coverage of planar regions.We first consider the placement of sensors of multiple types and costs over a specified set of locations to minimize the total sensorspsila cost. We present two approximate solutions to this problem with multiplicative factors of 3 and 1+1/l of the optimal cost, where l is a tunable parameter. We then...
For estimation and fusion tasks it is inevitable to approximate a Gaussian mixture by one with fewer components to keep the complexity bounded. Appropriate approximations can be typically generated by exploiting the redundancy in the shape description of the original mixture. In contrast to the common approach of successively merging pairs of components to maintain a desired complexity, the novel...
Tracking multiple targets in a cluttered environment is a challenging task. Probabilistic multiple hypothesis tracking (PMHT) is an efficient approach for dealing with it. Essentially, PMHT is based on expectation-maximization for handling association conflicts. Linearity in the number of targets and measurements is the main motivation for a further development and extension of this methodology. However,...
The problem of tracking targets, where measurements may occasionally be masked by the Doppler blind zone of the sensor, arises in Ground Moving Target Indicator tracking and aerial surveillance. For such problems, no target return is registered when the range rate (Doppler) of the target falls below a sensor-specific threshold in magnitude. For this reason, possible missed detections provide kinematic...
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