Non-Linear Fusion of Observations Provided by Two Sensors

Entropy

Monir Azmani²  Serge Reboul¹ 

[1] Laboratoire d’Informatique, Signal et Image de la Côte d’Opale (LISIC), Univ Lille Nord de France, Université du Littoral Côte d’Opale (ULCO), 50 rue Ferdinand Buisson, BP719, 62228 Calais Cedex, France;

关键词: estimation;    fusion;    weighted sum;   

DOI  :  10.3390/e15072698

来源: mdpi

【 摘 要 】

When we try to make the best estimate of some quantity, the problem of combining results from different experiments is encountered. In multi-sensor data fusion, the problem is seen as combining observations provided by different sensors. Sensors provide observations and information on an unknown quantity, which can differ in precision. We propose a combined estimate that uses prior information. We consider the simpler aspects of the problem, so that two sensors provide an observation of the same quantity. The standard error of the observations is supposed to be known. The prior information is an interval that bounds the parameter of the estimate. We derive the proposed combined estimate methodology, and we show its efficiency in the minimum mean square sense. The proposed combined estimate is assessed using synthetic data, and an application is presented.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.