In the context of parameter estimation, we study the problem of sensor management under a sparsity-promoting framework, where a sensor being off at a certain time instant is represented by the corresponding column of the estimator coefficient matrix being identically zero. In order to achieve a balance between activating the most informative sensors and uniformly allocating sensor energy, we propose a novel sparsity-promoting approach by adding an ℓ2-norm penalty function that discourages successive selections of the same group of sensors. We employ the alternating direction method of multipliers (ADMM) to solve the resulting ℓ2-norm optimization problem, which can then be split into a sequence of analytically solvable subproblems. We finally provide numerical results and comparison with other sensor scheduling algorithms in the literature to demonstrate the effectiveness of our approach.
|Title of host publication
|2015 18th International Conference on Information Fusion, Fusion 2015
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - Sep 14 2015
|18th International Conference on Information Fusion, Fusion 2015 - Washington, United States
Duration: Jul 6 2015 → Jul 9 2015
|18th International Conference on Information Fusion, Fusion 2015
|7/6/15 → 7/9/15
ASJC Scopus subject areas
- Information Systems
- Signal Processing
- Computer Networks and Communications