A filtering problem with uncertainty in observation

2019/07/02 by Shaolin Ji, Ji, Shaolin, Chuiliu Kong +3
Computer Science · Decision Sciences · Economics, Econometrics and Finance · #FOS: Mathematics #Probabilistic and Robust Engineering Design #Probability (math.PR) #Stochastic processes and financial applications #Target Tracking and Data Fusion in Sensor Networks

paper · pdf · doi:10.48550/arxiv.1907.01550

openalex publication_date 2019/07/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper is concerned with a generalized Kalman-Bucy filtering model and corresponding robust problem under model uncertainty. We find that this robust problem is equivalent to considering an estimate problem under some sublinear operator. Therefore, we turn to obtaining the minimum mean square estimator under a sublinear operator. By Girsanov theorem and minimax theorem, we obtain the optimal estimator x_t of the signal process x_t for given time t∈\lbrack0,T].

Citations

• Statistics of Random Processes

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