Statistical performance of IF estimation of LFM signals with timevarying amplitude using the peak of WVD

The instantaneous frequency （IF） estimation of the linear frequency modulated （LFM） signals with time-varying amplitude using the peak of the Wigner-Ville distribution （WVD） is studied. Theoretical analysis shows that the estimation on LFM signals with time-varying amplitude is unbiased, only if WVD of time-varying amplitude reaches its maximum at frequency zero no matter in which time. The statistical performance in the case of additive white Guassian noise is evaluated and an analytical expression for the variance is provided. The simulations using LFM signals with Gaussian envelope testify that IF can be estimated accurately using the peak of WVD for four models of amplitude variation. Furthermore the statistical result of estimation on the signals with amplitude descending before rising is better than that of the signals with constant amplitude when the amplitude variation rate is moderate.

THE EFFECTS OF CORRELATED SENSOR SIGNAL FLUCTUATION ON THE STATISTICAL PERFORMANCE OF AN AR HIGH RESOLUTION ARRAY PROCESSOR

The statistical performance of AR high resolution array processor in presence of correlated sensor signal fluctuation is studied. Mean square inverse beam pattern and pointing error are examined. Special attention is paid to the effects of reference sensor and correlation between sensors. It is shown that fluctuation causes broadening or even distortion of the mean square inverse beam pattern. Phase fluctuation causes pointing error. Its standard variance is proportional to that of fluctuation and is related to the number of sensors of the array. Correlation between sensors has important effects on pointing error.

Evaluation of reference evapotranspiration methods for the northeastern region of India

The study planed to identify a suitable alternative to the FAO 56 Penman-Monteith(FAO56PM)equation for calculating reference evapotranspiration(ET_(0))from chosen te mperature and radiation based models utilizing monthly meteorological data from 30 destinations in diverse agro-ecologial regions of the Northeast(NE)India ie,Assam Bengal Plain(ABP),eastern Himalaya(EH),and the northeastern hilly(NEH)region.Radiation-based IRMAK3 most appropriate in the ABP(weighted root mean square deviation,WRMSD=0.17 mm d^(-1),r^(2)=0.98,for Nagrakata),and TURC model being in the first three rank of most of the sites,with the lowest error and highest correlation in NEH(WRMSD=0.10 mm d^(-1),r^(2)=0.92,for Shillong),and EH(WRMSD=0.23 mm d^(-1),r^(2)=-0.95,for Gangtok).Findings reveal that IRMAK3 and TURC models performed equally well and were observed to be the best among selected modets for the majority of stations followed by FAO24 Blaney-Criddle(FAO24BC),and 1957MAKK Pair-wise regession equations were developed for preferred FAO56PM ET_(0) estimates to ET_(0) estimates by alternative methods.Cross-correlation of eighteen chose methods demonstrated that the five equations(i.e.four radiation-and one temperature-based)performed eceptionally well when contrasted with the FAO56PM model,thus being advised for assessing ET_(0)。under limiting data conditions as have yielded a better estimate of ET_(0) with a small error.