Abstract
In this paper, a nonsimulation performance prediction-based PDAF with Bayesian detection (BD) is proposed where the parameter in detection is dynamically optimized in a tracker-aware manner. The theoretical analysis and simulation results show that the dynamic PDAF-BD always outperforms the PDAF-BD with fixed thresholds and can be better than the dynamic PDAF when the spatial density of detection sampling is large.
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