A shrinkage-based particle filter for tracking with correlated measurements
作者： Aroland Kiring , Naveed Salman , Chao Liu , Inaki Esnaola , Lyudmila Mihaylova
关键词:
摘要: This paper studies the problem of tracking with wireless sensor networks (WSNs) using received signal strength (RSS) measurements. The log-normal shadowing associated RSS measurements from a mobile terminal is correlated both in space and time. We propose particle filter that exploits temporal spatial correlation estimates covariance matrix measurement noise shrinkage technique. Simulation results show estimated improves considerably performance. It also demonstrated via simulations shrinkage-based exhibits superior performance to without when limited are available. Results high accuracy proposed method presented.
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