In a decentralized detection scheme, several sensors perform a binary (hard) decision and send the resulting data to a fusion center for the final decision. If each local decision has a constant false alarm rate (CFAR), the final decision is ensured to be CFAR. We consider the case that each local decision is a threshold decision, and the threshold is proportional, through a suitable multiplier, to a linear combination of order statistics (OS) from a reference set (a generalization of the concept of OS thresholding). We address the following problem: given the fusion rule and the relevant system parameters, select each threshold multiplier and the coefficients of each linear combination so as to maximize the overall probability of detection for constrained probability of false alarm. By a Lagrangian maximization approach, we obtain a general solution to this problem and closed-form solutions for the AND and OR fusion logics. A performance assessment is carried on, showing a global superiority of the OR fusion rule in terms of detection probability (for operating conditions matching the design assumptions) and of robustness (when these do not match). We also investigate the effect of the hard quantization performed at the local sensors, by comparing the said performance to those achievable by the same fusion rule in the limiting case of no quantization.
OS-CFAR thresholding in decentralized radar systems
IEEE Transactions on Aerospace and Electronic Systems ; 32 , 4 ; 1257-1267
1996-10-01
1715852 byte
Article (Journal)
Electronic Resource
English
OS-CFAR Thresholding in Decentralized Radar Systems
Online Contents | 1996
|Decentralized CFAR signal detection
IEEE | 1989
|Sample-Deficient Adaptive Detection: Adaptive Scalar Thresholding versus CFAR Detector Performance
Online Contents | 2010
|Local SNR Considerations in Decentralized CFAR Detection
Online Contents | 1998
|