Title :
A multifeature decision space approach to radar target identification
Abstract :
This work focuses on the use of actual radar sensor data to construct a multifeature decision space formulation to the target identification (TID) problem. The decision space concepts are classical and the basic target features used can be extracted from the data provided by standard radar sensor operating modes. The target features used in the decision process along with the construction of a useful statistical description of each feature for a given target are presented. A multidimensional formulation of the decision space and the decision logic is also presented leading to a versatile multifeature based algorithm. The algorithm performance has been evaluated on live data and the results are reported.
Keywords :
Bayes methods; airborne radar; decision theory; feature extraction; radar computing; radar signal processing; radar target recognition; radar tracking; search radar; sensor fusion; Bayesian decision rule; airborne radar; algorithm performance; decision logic; feature vector elements; multidimensional formulation; multifeature based algorithm; multifeature decision space approach; radar sensor data; radar target identification; statistical description; surveillance radar; target discriminants; tracking radar; Aerospace testing; Data mining; Electronic equipment testing; Logic; Maximum likelihood estimation; Multidimensional systems; Sensor phenomena and characterization; Sensor systems; Sociotechnical systems; Spaceborne radar; Statistical analysis; Statistics; Surveillance; System testing;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
