Journal
AUTOMATICA
Volume 115, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2020.108882
Keywords
Particle filter; Fading measurements; Two-stage scheme; Parallelized implementation; Object tracking
Funding
- National Natural Science Foundation of China [61873148, 61933007, 61627810, 61320106010, 61633003, 61803282]
- Program for Changjiang Scholars and Innovative Research Team in University [IRT16R03]
- Royal Society of the UK
- Alexander von Humboldt Foundation of Germany
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In this paper, the filtering problem for systems with fading measurements is considered. Taking advantage of the cascaded structure of the system, the original filtering problem is decomposed into two subproblems: 1) recovery of the original measurements from the faded ones, and 2) state estimation based on the recovered signals. A two-stage particle filtering (PF) algorithm is proposed to achieve simultaneous measurement recovery and state estimation. In our scheme, the second-stage resampling procedure can be implemented concurrently, resulting in a significant reduction of execution time. Two examples are provided to demonstrate the effectiveness of our algorithm. A benchmark problem for nonlinear filtering is tackled in the first example and, in the second example, the proposed algorithm is applied to the object tracking problem where the measured signal is distorted by the communication channel. Simulation results show that, compared with the brute force PF, the two-stage PF can strike better balance between tracking accuracy and execution time. (C) 2020 Elsevier Ltd. All rights reserved.
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