Title :
Adaptive array CFAR detection
Author_Institution :
Lincoln Lab., MIT, Lexington, MA, USA
fDate :
4/1/1995 12:00:00 AM
Abstract :
Presented here is a large class of adaptive array detection algorithms with constant false alarm rate (CFAR), so that the false alarm rate can be set to any preassigned number without knowledge of the noise covariance matrix. This class map incorporate any usual method of cell averaging and any method for array weight vector synthesis. A sufficient condition for CFAR is derived, which is easy to satisfy in practice. Basic system parameters are discussed. An example of detection performance for a simple cell-averaging detector, in which the array weight vector is synthesized by the method of diagonal loading, is provided using Monte Carlo simulations.<>
Keywords :
Monte Carlo methods; adaptive signal processing; array signal processing; radar detection; Monte Carlo simulations; adaptive array CFAR detection; array weight vector synthesis; cell-averaging detector; constant false alarm rate; diagonal loading; Adaptive arrays; Antenna arrays; Covariance matrix; Detection algorithms; Detectors; Sensor arrays; Signal synthesis; Signal to noise ratio; Sufficient conditions; Voltage;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on