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An extended target tracking problem for high resolution sensors is considered. An ellipsoidal model is proposed to exploit sensor measurement of target extent, which can provide extra information to enhance tracking accuracy, data association performance, and target identification. Due to the presence of high nonlinearity of the model, a Rao-Blackwellised unscented Kalman filter (RBUKF) is adopted...
The neural extended Kalman filter (NEKF) has proven to be a quality maneuver target tracking system when the sensors provide a fully observable measurement, such as a radarpsilas range-bearing measurement or a position report. As with any state estimation technique, the NEKF requires observability in order to estimate the target track states. Observability is needed as well to train the weights of...
Sensor measurement systems rely upon knowledge of the functional dynamics between system states and the measured outputs. Errors in sensor measurements come from a variety of sources, but standard systems can easily compensate for only some types of errors. There are well known techniques to compensate for errors that result from such issues as noise and sensor accuracy limitations, but other types...
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