Multi-sensor allocation based on Cramér-Rao Low Bound

Abstract

Multi-sensor allocation is one of the key problems of multi-sensor management. In order to establish a reasonable allocation model, a method based on Vague set for the target priority was proposed firstly. It is effectively to avoid the subjectivity of the weight selection by calculating the weights that making the Vague distance maximum. Then, this paper principally studied the method based on Cramér-Rao Low Bound for Multi-sensor allocation. The CRLB was introduced into the multi-sensor allocation model according to the characteristics of tracking, and it need not choose target tracking algorithm. Furthermore, the model made it more close to the actual situation by detailing the constraints. Finally, an application example was given and the results validated the applicability and effectiveness of this method.