2021/02/28 by Vedang M. Deshpande, Deshpande, Vedang M., Raktim Bhattacharya +1
Computer Science · Engineering · #Distributed Control Multi-Agent Systems #Distributed Sensor Networks and Detection Algorithms #Target Tracking and Data Fusion in Sensor Networks #cs.SY #eess.SY
paper · pdf · doi:10.48550/arxiv.2103.00739
arxiv created 2021/03/01 · arxiv updated 2021/03/02
In this paper the tracking problem of multi-agent systems, in a particular scenario where a segment of agents entering a sensing-denied environment or behaving as non-cooperative targets, is considered. The focus is on determining the optimal sensor precisions while simultaneously promoting sparseness in the sensor measurements to guarantee a specified estimation performance. The problem is formulated in the discrete-time centralized Kalman filtering framework. A semi-definite program subject to linear matrix inequalities is solved to minimize the trace of precision matrix which is defined to be the inverse of sensor noise covariance matrix. Simulation results expose a trade-off between sensor precisions and sensing frequency.