目前基于无线设备的室内指纹定位技术因为其设备普及且定位准确而受到人们的广泛关注。针对传统室内指纹定位方式中定位阶段特征匹配时没有考虑当前环境相对于基准环境的变化因素这一不足,提出了一个基于CSI(Channel State Information...目前基于无线设备的室内指纹定位技术因为其设备普及且定位准确而受到人们的广泛关注。针对传统室内指纹定位方式中定位阶段特征匹配时没有考虑当前环境相对于基准环境的变化因素这一不足,提出了一个基于CSI(Channel State Information)的自适应修正模型定位算法。该算法通过引入一个衡量当前室内环境变化的指标PEM(Percentage of nonzero Elements)来表示室内人数增加时子载波波动程度的变化;同时又通过设计一个新的修正匹配模型来补偿因多径造成的指纹特征的衰减。实验结果充分证明了该定位方案相比于之前的指纹定位系统FIFS和CSI-MIMO,准确率分别提高了30%和15%。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
文摘目前基于无线设备的室内指纹定位技术因为其设备普及且定位准确而受到人们的广泛关注。针对传统室内指纹定位方式中定位阶段特征匹配时没有考虑当前环境相对于基准环境的变化因素这一不足,提出了一个基于CSI(Channel State Information)的自适应修正模型定位算法。该算法通过引入一个衡量当前室内环境变化的指标PEM(Percentage of nonzero Elements)来表示室内人数增加时子载波波动程度的变化;同时又通过设计一个新的修正匹配模型来补偿因多径造成的指纹特征的衰减。实验结果充分证明了该定位方案相比于之前的指纹定位系统FIFS和CSI-MIMO,准确率分别提高了30%和15%。
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.
