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.
Optimization and analysis of PDAF with Bayesian detection
IEEE Transactions on Aerospace and Electronic Systems ; 52 , 4 ; 1986-1995
2016-08-01
748249 byte
Article (Journal)
Electronic Resource
English
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