A novel distributed CMLWLC CFAR detector

In the past applications, the centralized CFAR, which used in the multi-sensor information fusion system, brings an overload communication burden, therefore the distributed CFAR detector becomes a developing and important field. In current distributed CFAR detectors, most of them assume that every sensor in the detector have same signal to noise ratio (SNR). In this paper, we study the case that every sensor in the detector have different SNR. Corresponding to this case, a novel distributed adaptive CFAR detector termed as CMLWLC is presented. In the scheme, a local test statistic, which is the ratio of its test sample level and a designated censored mean level (CML) of its reference samples, is calculated by distributed sensors, and then each sensor transmits its local test statistic to the fusion center. At the fusion center, the global decision is made based on weighted linear combining (WLC). Since the weights are adjusted according to different SNR, adaptively, the proposed detector can available in the case that the target echo and noise/clutter have different level for every sensor. Meanwhile, for a Swerling II fluctuating target in Gaussian noise of unknown level, its closed-form expressions of false alarm probability and detection probability are derived. Comparison numerical results show that the CMLWLC detector has good detection performance in both homogeneous and multi-target backgrounds.