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A Weight Redistributed GM-PHD filter Accounting for Stochastic Missed Detection | Synapse
March 3, 2026
A Weight Redistributed GM-PHD filter Accounting for Stochastic Missed Detection
LZ
Liu Zeya
ZG
Zhai Guang
WS
Wei Shijun
Key Points
The weight redistributed GM-PHD filter enhances detection capabilities in real-time scenarios, improving tracking accuracy.
Key evidence shows improved performance metrics when incorporating stochastic processes into traditional methods.
Analysis of simulated tracking scenarios demonstrates the efficiency of the weight redistribution approach in overcoming missed detections.
Improved algorithm highlights the potential for better target tracking systems, but real-world trials are needed for validation.
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Zeya et al. (Thu,) studied this question.
synapsesocial.com/papers/69a766e9badf0bb9e87dee5a
https://doi.org/https://doi.org/10.1016/j.ast.2026.111849
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