A robust Constant False Alarm Rate (CFAR) distributed detection system that operates in heavy clutter with unknown distribution is presented. The system is designed to provide CFARness under clutter power fluctuations and robustness under unknown clutter and noise distributions. The system is also designed to operate successfully under different-power sensors and exhibit fault-tolerance in the presence of sensor power fluctuations. The test statistic at each sensor is a robust CFAR t-statistic. In addition to the primary binary decisions, confidence levels are generated with each decision and used in the fusion logic to robustify the fusion performance and eliminate weaknesses of the Boolean fusion logic. The test statistic and the fusion logic are analyzed theoretically for Weibull and log-normal clutter. The theoretical performance is compared against Monte-Carlo simulations that verify that the system exhibits the desired characteristics of CFARness, robustness, insensitivity to power fluctuations and fault-tolerance. The system is tested with experimental target-in-clear and target-in-clutter data and its experimental performance agrees with the theoretically predicted behavior.<<ETX>>
[1]
Stelios C. A. Thomopoulos,et al.
Decision and Evidence Fusion in Sensor Integration
,
1991
.
[2]
Stelios C. A. Thomopoulos,et al.
Design of a Robust Multi-Radar Distributed Data Fusion System
,
1993,
Proceedings. The First IEEE Regional Conference on Aerospace Control Systems,.
[3]
G. B. Goldstein,et al.
False-Alarm Regulation in Log-Normal and Weibull Clutter
,
1973,
IEEE Transactions on Aerospace and Electronic Systems.
[4]
Ramanarayanan Viswanathan,et al.
Optimal Decision Fusion in Multiple Sensor Systems
,
1987,
IEEE Transactions on Aerospace and Electronic Systems.
[5]
Stelios C.A. Thomopoulos,et al.
Distributed Detection with Consulting Sensors and Communication Cost: The Gaussian Case
,
1988,
1988 American Control Conference.
[6]
Ramanarayanan Viswanathan,et al.
Optimal distributed decision fusion
,
1989
.