Title :
A new method for emitter source signal fusion identification
Author :
Jin-feng, Pang ; Yun, Lin
Author_Institution :
Inf. & Commun. Eng. Coll., Harbin Eng. Univ., Harbin, China
Abstract :
Information fusion is widely used in many fields, such as space remote sensing, environment monitor, emitter recognition, and so on. In this paper, aiming at the drawbacks of DS evidence algorithm, which is difficult to deal with high conflict and mutuality evidence, based on convex optimization theory, a new information fusion algorithm is presented. Firstly, according to the sensor reports, it constructs the cost function of information fusion. By decomposing the cost function, the problem of information fusion is transformed to convexity optimization problem. Finally, it is solved by using interior-point logarithm, which has simple structure, small computation and easy to come true. The theory analysis and simulation result prove that the convex optimization algorithm has better recognition ability and flexibility than traditional DS evidence algorithm, so it can be used in emitter recognition.
Keywords :
convex programming; sensor fusion; DS evidence algorithm; convex optimization theory; convexity optimization problem; cost function; emitter recognition; emitter source signal fusion identification; environment monitor; information fusion; interior-point logarithm; mutuality evidence; recognition ability; sensor reports; space remote sensing; Algorithm design and analysis; Complexity theory; Convex functions; Cost function; Educational institutions; Polynomials; Convex Optimization Theory; DS Algorithm; Emitter Recognition; Information Fusion; Interior-point Logarithm;
Conference_Titel :
Millimeter Waves (GSMM), 2012 5th Global Symposium on
Conference_Location :
Harbin
Print_ISBN :
978-1-4673-1302-5
DOI :
10.1109/GSMM.2012.6314389