Analysis of adaptive detection of moderately fluctuating radar targets in target multiplicity environments

Abstract

In this article, we provide a complete detection analysis, in its exact form, of what is known as moderately fluctuating radar targets when the background environment contains a number of interfering targets along with the target under test. The illumination of this class of radar targets by a coherent pulse train, return a train of correlated pulses with a correlation coefficient in the range 0< ρ<1 (intermediate between SWII and SWI models). Since the adaptive detection is one of the desirable features for modern radar receivers, it becomes of importance to adaptively detect this class of targets. The attractive class of adaptive detectors is that based on order-statistics (OS) technique. The more advanced version of the OS algorithm, known as the generalized trimmed-mean (GTM) scheme, is chosen here to carry out this task. It implements trimmed averaging of a weighted ordered range samples. This processor is analyzed for the case where the radar receiver incorporates a postdetection integrator amongst its contents and where the operating environment is multitarget. The primary and the secondary interfering targets are assumed to be fluctuating in accordance with partially correlated χ 2 fluctuation model. SWI and SWII well-known models represent the cases where the signal is completely correlated and completely decorrelated, respectively, from pulse to pulse. It is shown that the processor performance improves, for weak SNR of the primary target, as the correlation coefficient ρ s increases and this occurs either in the absence or in the presence of spurious targets. For strong SNR, on the other hand, the processor performance degrades as ρ s increases and the SWI and SWII models enclose the correlated target case and this behavior is common for all GTM based schemes.