Practical Automotive Applications of Cramer-Rao Bound Analysis
Paper in proceedings, 2005

The Cramér-Rao lower bound places a bound, in a mean squared sense, on the performance of all unbiased estimators. In this paper, as a base for discussion, we provide a straight forward derivation of such bounds for estimators of mobile node positions, operating on observations of distances between entities in an asynchronous network. While Cramér-Rao bound analysis is very common in the positioning community, it is mostly used for analytical evaluation of various estimators, for comparison purposes and for sensor information fusion. In this work, we present some more commercial and practical applications of these tools for performance evaluation. We first discuss the deployment of beacons throughout a transportation infrastructure as a first step towards providing global automotive, possibly GPS augmented, positioning services with applications such as collision warning and collision avoidance. We then move on to describe how the cost associated with the deployment of such beacons can be drastically reduced through relying on inter-node range measurements and a dynamic beaconing scheme we call the lighthouse scheme. We also present a method for complexity reduction in the estimation of relative node coordinates and evaluation of Cramér-Rao performance measures. ©2005 IEEE.

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Author

Mats Rydström

Chalmers, Signals and Systems, Communication and Antenna Systems, Communication Systems

Mats Rydström

Chalmers

Erik Ström

Chalmers, Signals and Systems, Communication and Antenna Systems, Communication Systems

Arne Svensson

Chalmers, Signals and Systems, Communication and Antenna Systems, Communication Systems

Proceedings IEEE Intelligent Vehicles Symposium, Las Vegas, Nevada, USA

61-66

Subject Categories

Computer and Information Science

DOI

10.1109/IVS.2005.1505078

ISBN

0780389611

More information

Latest update

9/10/2018