最大概似法在多普勒激光测风雷达中的应用研究

为了从相干多普勒测风激光雷达的微弱气溶胶后向散射信号中高效、准确地提取多普勒频移信息,得到最接近CRB极限的无偏估计,利用气溶胶后向散射信号统计特性,建立了相干多普勒激光雷达仿真模型,并用最大概似法(ML)推导了在功率谱宽度已知情况下多普勒频率的估计算法。利用1.54μm全光纤相干激光雷达系统获得风场测量数据,用ML算法进行多普勒频移估计,并将结果与传统的周期图最大值法(PM)所得结果进行比较。对比表明,ML算法与PM算法的数据处理结果有较好的一致性,并且ML算法的多普勒频率探测能力更优。

RECURSIVE FILTERING RADON-AMBIGUITY TRANSFORM ALGORITHM FOR DETECTING MULTI-LFM SIGNALS

In multi-LFM signal condition, Radon-Ambiguity Transform (RAT) of the strongLFM component has strong suppression effect on that of the weak LFM component. A methodnamed as Recursive Filtering RAT (RFRAT) Mgorithm is proposed for solving this problem. Byfully using of the Maximum Likelihood (ML) estimation value of the frequency modulation rategot by RAT. RFRAT can detect the noisy multi-LFM signals out step by step. The merit of thisnew method is validated by an illustrative example in low Signal-to-Noise-Ratio (SNR) condition.

ESTIMATION OF CARRIER FREQUENCY OFFSETS FOR MIMO SYSTEMS WITH DISTRIBUTED TRANSMIT ANTENNAS

The problem of estimating the carrier frequency offsets in Multiple-Input Multiple-Output (MIMO) systems with distributed transmit antennas is addressed. It is supposed that the transmit antennas are distributed while the receive antennas are still centralized, and the general case where both the time delays and the frequency offsets are possibly different for each transmit antenna is considered. The channel is supposed to be frequency flat, and the macroscopic fading is also taken into consideration. A carrier frequency offset estimator based on Maximum Likelihood (ML) is proposed, which can separately estimate the frequency offset for each transmit antenna and exploit the spatial diversity. The Cramer-Rao Bound (CRB) for synchronous MIMO (i.e., the time delays for each transmit antenna are all equal) is also derived. Simulation results are given to illustrate the per- formance of the estimator and compare it with the CRB. It is shown that the estimator can provide satisfactory frequency offset estimates and its performance is close to the CRB for the Signal-to-Noise Ratio (SNR) below 20dB.

华梵前山校区风速统计分布之探讨

研究针对华梵前山气象站2002年5月至2006年12月之小时风速资料进行统计分析,探讨华梵前山风速资料之分布是否合乎韦伯分布(Weibull distribution)及莱利分布(Rayleigh distribution)。研究中韦伯分布使用动差法(Method of moment)及最大概似法(Method of maximumlikelihood)求取参数;莱利分布使用动差法求取参数。进一步以K-S检定,判断各理论累积机率分布与观测值之累积机率是否相符;再以误差绝对值之总和判断何种分布较为适合。分析结果显示:韦伯分布与莱利分布均可适用于描述全部数据之机率分布。将资料分为夏半年(4-9月)与冬半年(10月至翌年3月)时,韦伯分布为最适用之机率分布函数;且夏半年之参数以最大概似法求得最佳,而冬半年则以动差法较佳。此结果可作为校区风蚀、防灾、生态、环境风场特性及评估风能潜势研究之参考。

Composite interval mapping of QTL for dynamic traits

Many economically important quantita- tive traits in animals and plants are measured re- peatedly over time. These traits are called dynamic traits. Mapping QTL controlling the phenotypic pro- files of dynamic traits has become an interesting topic for animal and plant breeders. However, statistical methods of QTL mapping for dynamic traits have not been well developed. We develop a composite in- terval mapping approach to detecting QTL for dy- namic traits. We fit the profile of each QTL effect with Legendre polynomials. Parameter estimation and statistical test are performed on the regression coefficients of the polynomials under the maximum likelihood framework. Maximum likelihood estimates of QTL parameters are obtained via the EM algorithm. Results of simulation study showed that composite interval mapping can improve both the statistcial power of QTL detecting and the accuracy of parameter estimation relative to the simply interval mapping procedure where only one QTL is fit to each model. The method is developed in the context of an F2 mapping population, but extension to other types of mapping populations is straightforward.