Several Constant False Alarm Rate （CFAR） architectures, where radar systems often employ them to automatically adapt the detection threshold to the local background noise or clutter power in an attempt to maintain a...Several Constant False Alarm Rate （CFAR） architectures, where radar systems often employ them to automatically adapt the detection threshold to the local background noise or clutter power in an attempt to maintain an approximately constant rate of false alarm, have been recently proposed to estimate the unknown noise power level. Since the Ordered-Statistics （OS） based algorithm has some advantages over the Cell-Averaging （CA） technique, we are concerned here with this type of CFAR detectors. The Linearly Combined Ordered-Statistic （LCOS） processor, which sets threshold by processing a weighted ordered range samples within finite moving window, may actually perform somewhat better than the conventional OS detector. Our objective in this paper is to analyze the LCOS processor along with the conventional OS scheme for the case where the radar receiver incorporates a postdetection integrator amongst its contents and where the operating environments contain a number of secondary interfering targets along with the primary target of concern and the two target types fluctuate in accordance with the Swerling Ⅱ fluctuation model and to compare their performances under various operating conditions.展开更多
This paper deals with the exact detection analysis of the Ordered-Statistic(OS) processor along with OS Greatest Of(OSGO) and OS Smallest Of(OSSO) modified versions, for M postdetection integrated pulses when the oper...This paper deals with the exact detection analysis of the Ordered-Statistic(OS) processor along with OS Greatest Of(OSGO) and OS Smallest Of(OSSO) modified versions, for M postdetection integrated pulses when the operating environment is nonhomogeneous. Analytical results are presented in multiple-target case as well as in regions of clutter power transitions. The primary and the secondary interfering targets are assumed to be fluctuating in accordance with the SWII target fluctuation model. As the number of noncoherently integrated pulses increases,lower threshold values and consequently better detection performances are obtained in both homogeneous and multiple target background models. However, the false alarm rate performance of OSSO-CFAR(Constant False Alarm Rate) scheme at clutter edges is worsen with increasing the postdetection integrated pulses. As predicted, the OSGO-CFAR detector accommodates the presence of spurious targets in the reference window, given that their number is within its allowable range in each local window, and controls the rate of false alarm when the contents of the reference cells have clutter boundaries.展开更多
文摘Several Constant False Alarm Rate （CFAR） architectures, where radar systems often employ them to automatically adapt the detection threshold to the local background noise or clutter power in an attempt to maintain an approximately constant rate of false alarm, have been recently proposed to estimate the unknown noise power level. Since the Ordered-Statistics （OS） based algorithm has some advantages over the Cell-Averaging （CA） technique, we are concerned here with this type of CFAR detectors. The Linearly Combined Ordered-Statistic （LCOS） processor, which sets threshold by processing a weighted ordered range samples within finite moving window, may actually perform somewhat better than the conventional OS detector. Our objective in this paper is to analyze the LCOS processor along with the conventional OS scheme for the case where the radar receiver incorporates a postdetection integrator amongst its contents and where the operating environments contain a number of secondary interfering targets along with the primary target of concern and the two target types fluctuate in accordance with the Swerling Ⅱ fluctuation model and to compare their performances under various operating conditions.
文摘This paper deals with the exact detection analysis of the Ordered-Statistic(OS) processor along with OS Greatest Of(OSGO) and OS Smallest Of(OSSO) modified versions, for M postdetection integrated pulses when the operating environment is nonhomogeneous. Analytical results are presented in multiple-target case as well as in regions of clutter power transitions. The primary and the secondary interfering targets are assumed to be fluctuating in accordance with the SWII target fluctuation model. As the number of noncoherently integrated pulses increases,lower threshold values and consequently better detection performances are obtained in both homogeneous and multiple target background models. However, the false alarm rate performance of OSSO-CFAR(Constant False Alarm Rate) scheme at clutter edges is worsen with increasing the postdetection integrated pulses. As predicted, the OSGO-CFAR detector accommodates the presence of spurious targets in the reference window, given that their number is within its allowable range in each local window, and controls the rate of false alarm when the contents of the reference cells have clutter boundaries.
