%0 Journal Article
%T Target-Multiplicity Analysis of CML Processor for Partially-Correlated ¦Ö2 Targets
%J International Journal of Aerospace Sciences
%@ 2169-8899
%D 2012
%I 
%R 10.5923/j.aerospace.20120105.02
%X Our scope in this paper is to treat the problem of detecting what is called moderately fluctuating targets when the operating environment is contaminated with a number of outlying targets along with the target under test (multiple-target situations). The illumination of this important class of radar targets by a coherent pulse train, return a train of correlated pulses with a correlation coefficient in the range 0<¦Ñ<1 (intermediate between SWII & SWI). To achieve this goal, we choose the OS based type of adaptive detectors owing to its immunity to interfering targets. However, the homogeneous performance of OS technique is always lower than that of the CA scheme. Therefore, it is preferable to choose the more efficient version, which combines the benefits of these two schemes, of the adaptive detectors. This modified version is known as censored mean-level (CML) in the literature. It implements trimmed averaging of a weighted ordered range samples. Here, the detection performance of the CML processor is analyzed on the assumption that the radar receiver collects data from M successive pulses and the radar system operates in target multiplicity environments. The primary as well as the secondary interfering targets fluctuates in accordance with ¦Ö2 fluctuation model. SWI and SWII cases represent the situations where the signal is completely correlated and completely decorrelated, respectively, from pulse to pulse. Exact expressions are derived for the detection and false alarm rate performances in nonideal situations. For weak SNR, it is shown that the processor performance improves as the correlation coefficient ¦Ñ increases and this occurs either in the absence or in the presence of outlying targets. This behavior is rapidly changed as the SNR becomes stronger where the processor performance degrades as ¦Ñ increases, and the SWII and SWI models embrace all the correlated target cases.
%K Adaptive Radar Detectors
%K Postdetection Integration
%K Partially-Correlated ¦¶2 Fluctuating Targets
%K Swerling I and II Models
%K Target Multiplicity Environments
%U http://article.sapub.org/10.5923.j.aerospace.20120105.02.html