In view of the decline filtering accuracy caused by measured outliers in target tracking application, a novel reweighted robust particle filter is proposed to acquire accurate state estimates an automotive radar system. To infer importance each entry multidimensional contaminated measurement vector, we employ weight which follows Gamma distribution, model noise and carry out estimates. Addition...

In distributed sensor networks, the tradeoff between application performance and resource consumption is a fundamental issue. In this paper, we analyze the tradeoff in the context of localization problems. In particular, the localization performance is characterized using the Cramer-Rao lower bound which reflects the performance limit in the family of unbiased estimators. For a variety of dista...

The simultaneous multi-beam working mode of the collocated multiple-input and multiple-output (MIMO) radar enables to track multiple targets simultaneously. A joint power bandwidth allocation algorithm in a MIMO based on quality service (QoS) framework is proposed for multi-target tracking problem with different threat levels. Firstly, posterior Cramer–Rao lower bound (PCRLB) concerning derived...

Optimal performance of delay tracking loops in a binary linearly-modulated system is investigated, which is compared with the Cramer-Rao lower bound and the performance of a tracking loop suggested by the maximumlikelihood timing estimation.

The Cramer-Rao error bound provides a fundamental limit on the expected performance of a statistical estimator. The error bound depends on the general properties of the system, but not on the specific properties of the estimator or the solution. The Cramer-Rao error bound has been applied to scalarand vector-valued estimators and recently to parametric shape estimators. However, nonparametric, ...