2012/11/07 by Srinivas Sridharan, Sridharan, Srinivas
Computer Science · Engineering · Mathematics · #49L20 #93E10 #Distributed Sensor Networks and Detection Algorithms #FOS: Mathematics #Fault Detection and Control Systems #Optimization and Control (math.OC) #Target Tracking and Data Fusion in Sensor Networks #math.OC #msc:49L20 #msc:93E10
paper · pdf · doi:10.48550/arxiv.1211.1449
6 pages, 4 figures
openalex publication_date 2012/11/07 · arxiv created 2012/11/08 · arxiv updated 2012/11/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A robust (deterministic) filtering approach to the problem of optimal sensor selection is considered herein. For a given system with several sensors, at each time step the output of one of the sensors must be chosen in order to obtain the best state estimate. We reformulate this problem in an optimal control framework which can then be solved using dynamic programming. In order to tackle the numerical computation of the solution in an efficient manner, we exploit the preservation of the min-plus structure of the optimal cost function when acted upon by the dynamic programming operator. This technique yields a grid free numerical approach to the problem. Simulations on an example problem serve to highlight the efficacy of this generalizable approach to robust multi-sensor state estimation.