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arXiv · 2602.09679

Real time filtering algorithms

Chang Qin·Yikun Li·Ru Qian·Jiayi Kang·Yao Mao
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Abstract

This paper presents a systematic review of recent advances in nonlinear filtering algorithms, structured into three principal categories: Kalman-type methods, Monte Carlo methods, and the Yau-Yau algorithm. For each category, we provide a comprehensive synthesis of theoretical developments, algorithmic variants, and practical applications that have emerged in recent years. Importantly, this review addresses both continuous-time and discrete-time system formulations, offering a unified review of filtering methodologies across different frameworks. Furthermore, our analysis reveals the transformative influence of artificial intelligence breakthroughs on the entire nonlinear filtering field, particularly in areas such as learning-based filters, neural network-augmented algorithms, and data-driven approaches.

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Chang Qin, Yikun Li, Ru Qian, Jiayi Kang, Yao Mao. 2026-02-10. Real time filtering algorithms. https://doi.org/10.4310/cis.260128105210

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