OS-CFAR THRESHOLDING IN DECENTRALIZED RADAR SYSTEMS

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 rat e (CFAR), the final decision is ensured to be CFAR We consider the cas e that each local decision is a threshold decision, and the threshold is proportional, through a suitable multiplier, to a linear combinatio n of order statistics (OS) from a reference set (a generalization of t he concept of OS thresholding). We address the following problem given the fusion rule and the relevant system parameters, select each thres hold multiplier and the coefficients of each linear combination so as to maximize the overall probability of detection for constrained proba bility of false alarm. By a Lagrangian maximization approach, we obtai n a general solution to this problem and closed-form solutions for the AND and OR fusion logics. A performance assessment is carried on, sho wing a global superiority of the OR fusion mle in term of detection pr obability (for operating conditions matching the design assumptions) a nd of robustness (when these do not match). We also investigate the ef fect of the hard quantization performed at the local sensors, by compa ring the said performance to those achievable by the same fusion rule in the limiting case of no quantization.