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
We introduce Tsallis mapping in Bianconi-Barabgsi （B-B） fitness model of growing networks. This mapping addresses the dynamical behavior of the fitness model within the framework of nonextensive statistics mechanics...We introduce Tsallis mapping in Bianconi-Barabgsi （B-B） fitness model of growing networks. This mapping addresses the dynamical behavior of the fitness model within the framework of nonextensive statistics mechanics, which is characterized by a dimensionless nonextensivity parameter q. It is found that this new phenomenological parameter plays an important role in the evolution of networks： the underlying evolving networks may undergo a different phases depending on the q exponents, comparing to the original B-B fitness model, and the corresponding critical transition temperature Tc is also identified.展开更多
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.
基金Supported by the National Natural Science Foundation of China under Grant No. 10875058the Initiative Plan of Shanghai Education Committee under Grant No. 10YZ76the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry (SRF for ROCS,SEM)
文摘We introduce Tsallis mapping in Bianconi-Barabgsi （B-B） fitness model of growing networks. This mapping addresses the dynamical behavior of the fitness model within the framework of nonextensive statistics mechanics, which is characterized by a dimensionless nonextensivity parameter q. It is found that this new phenomenological parameter plays an important role in the evolution of networks： the underlying evolving networks may undergo a different phases depending on the q exponents, comparing to the original B-B fitness model, and the corresponding critical transition temperature Tc is also identified.
