Articles
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Abstract Many commercial and defense applications involve multisensor, multitarget tracking, requiring the fusion of information from a set of sensors. An interesting use case occurs when data available at a central node (due to geometric diversity or retrodiction) allows for the tailoring of state estimation for a target. For instance, if a target is initially
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Abstract Target characterization is an important step in many defense missions, often relying on fitting a known target model to observed data. Optimization of model parameters can be computationally expensive depending on the model complexity, thus having models that both describe the data well and that can be efficiently optimized is critical. This work introduces
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Abstract In the field of sensing, a typically unavoidable nuisance is the inherent bias of a sensor due to imperfections in timing, calibration, and other sources. The errors incurred by the bias ripple through higher-level processes such as tracking and sensor fusion, causing varying effects to each operation. In many different applications, such as track-to-track
Zac Chance 