Title
Optimal linear and quadratic estimators for tracking from distance measurements
Abstract
We consider the tracking problem of a point moving in a three-dimensional space using only measurements of distance from a set of reference points. The approach followed in this paper is to derive a linear map with multiplicative noise through a quadratic transformation of the distance measurements. A suitable rewriting by means of an output injection term makes the multiplicative noise of the linear map amenable to be processed by recursive estimators. These estimators are guaranteed to be internally stable and the variance of the estimation error is estimated. We compare the performance of the resulting algorithm for the linear and quadratic case with standard alternatives.
Year
DOI
Venue
2020
10.1016/j.sysconle.2020.104674
Systems & Control Letters
Keywords
DocType
Volume
Target tracking,State estimation,Kalman filtering
Journal
139
ISSN
Citations 
PageRank 
0167-6911
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
F. Cacace1443106.96
Francesco Conte2236.39
A. Germani340152.47
Giovanni Palombo411.37