相位响应固定幅度响应约束的稳健波束形成方法

传统的幅度约束波束形成器是一个非凸问题,需将原始模型化为线性规划进行间接求解。该文针对均匀线阵提出一种相位响应固定幅度响应约束(PFMC)的稳健波束形成方法。利用权矢量逆序列对应的传递函数与阵列响应函数只差一个相位因子这一性质,将阵列响应的相位设置为固定的线性相位,仅对阵列响应的实数幅度进行约束,从而得到一个凸的代价函数,最优权矢量可以利用内点法求出。同时考虑到协方差矩阵误差,利用最坏(WC)情况性能最优原理提出PFMC-WC算法改善PFMC的性能。与传统幅度约束波束形成器相比,减少了约束个数并省掉了恢复权矢量过程,从而降低了计算量。此外,由于相位响应得到保证,该文算法相对于传统算法具有更好的性能。仿真实验验证了该文算法的有效性。     

基于相关法的分布式全相参雷达相干参数估计及相参性能

针对一般结构的分布式全相参雷达,研究了基于相关法的时延差和相位差估计性能以及输出信噪比增益(oSNRg)。首先分别建立多输入多输出(MIMO)模式和全相参(FC)模式下的信号模型。然后重点分析估计相位差时的相位模糊问题,并提出一种有效的解模糊方法。数值实验结果表明：当输入信噪比足够高时,相关法能够获得稳健的相干参数估计,且oSNRg接近理想值。     

大规模MIMO时分双工系统的鲁棒预编码设计

对于采用大规模MIMO技术的时分双工系统,天线互易误差会破坏上下行信道互易特性,大幅降低预编码算法下行传输性能。由于实际系统难以完全消除天线互易误差,该文以最大化各用户平均信泄噪比为目标,根据天线互易误差的统计特性,设计了对该误差具有鲁棒性的线性预编码算法。同时为了进一步降低用户接收端的等效噪声功率,该文还将该线性鲁棒预编码算法扩展为基于矢量扰动的非线性鲁棒预编码算法,并通过减格辅助技术降低其扰动矢量求解复杂度,使其更适用于大规模MIMO系统应用。计算机仿真结果表明在存在基站天线互易误差条件下,该文所提出的线性与非线性鲁棒性预编码算法的性能均优于传统预编码算法的性能。     

Phenyl Sulphonyl Acetaldehyde Diethyl Acetal: A New Robust 1,2-Diol Protective Group

Abstract

A simple preparation of a novel resilient protective group for 1,2-diols is described herein which is remarkably stable in the presence of extremely harsh basic conditions as well as acidic media. The title reagent's versatility is detailed with numerous examples.

     

Pathwise superhedging for time-dependent barrier options on càdlàg paths—Finite or infinite tradeable European,One-Touch,lookback or forward starting options

We establish pathwise duality using simple predictable trading strategies for the robust hedging problem associated with a barrier option whose payoff depends on the terminal level and the infimum of a càdlàg strictly positive stock price process, given tradeable European options at all strikes at a single maturity. The result allows for a significant dimension reduction in the computation of the superhedging cost, via an alternate lower-dimensional formulation of the primal problem as a convex optimization problem, which is qualitatively similar to the duality which was formally sketched using linear programming arguments in Duembgen and Rogers [10] for the case where we only consider continuous sample paths. The proof exploits a simplification of a classical result by Rogers (1993) which characterizes the attainable joint laws for the supremum and the drawdown of a uniformly integrable martingale (not necessarily continuous), combined with classical convex duality results from Rockefellar (1974) using paired spaces with compatible locally convex topologies and the Hahn–Banach theorem. We later adapt this result to include additional tradeable One-Touch options using the Kertz and Rösler (1990) condition. We also compute the superhedging cost when in the more realistic situation where there is only finite tradeable European options; for this case we obtain the full duality in the sense of quantile hedging as in Soner (2015), where the superhedge works with probability $1?\epsilon$ where $\epsilon$ can be arbitrarily small), and we obtain an upper bound for the true pathwise superhedging cost. In Section 5, we extend our analysis to include time-dependent barrier options using martingale coupling arguments, where we now have tradeable European options at both maturities at all strikes and tradeable forward starting options at all strikes. This set up is designed to approximate the more realistic situation where we have a finite number of tradeable Europeans at both maturities plus a finite number of tradeable forward starting options.¹     

Design of robust differential microphone arrays with the Jacobi–Anger expansion

Due to their small size, differential microphone arrays (DMAs) are very attractive. Moreover, they have been effective in combating noise and reverberation. Recently, a new class of DMAs of different orders have been developed with the MacLaurin’s series and the frequency-independent patterns. However, the MacLaurin’s series does not approximate well the exponential function, which appears in the general definition of the beampattern, when the intersensor spacing is not small enough. To circumvent this problem, we propose in this paper to approximate the exponential function with the Jacobi–Anger expansion. Based on this approximation and the frequency-independent Chebyshev patterns, we derive first-, second-, and third-order DMAs. Furthermore, in order to improve the robustness of DMAs against white noise amplification, we propose to use more microphones combined with minimum-norm filters. It is also shown that the Jacobi–Anger expansion is optimal from a mean-squared error perspective. Simulations are carried out to evaluate the performance of the proposed DMAs.     

A robust adaptive weighted constant modulus algorithm for blind equalization of wireless communications systems under impulsive noise environment

A robust adaptive weighted constant modulus algorithm is proposed for blind equalization of wireless communication systems under impulsive noise environment. The influence of the impulsive noise is analyzed based on numerical analysis method. Then an adaptive weighted constant modulus algorithm is constructed to adaptively suppress impulsive noise. Theoretical analysis is provided to illustrate that the proposed algorithm has a robust equalization performance since the impulsive noise is adaptively suppressed. Moreover, the proposed algorithm has stable and quick convergence due to avoidance of large misadjuntment and adoption of large step size. Simulation results are presented to show the robust equalization performance and the fast convergence speed of the proposed algorithm under both impulsive noise and Gaussian noise environments.     

Phase unwrapping by accumulation of residual maps

We present a path independent (global) algorithm for phase unwrapping based on the minimisation of a robust cost function. The algorithm incorporates an outlier rejection mechanism making it robust to large inconsistencies and discontinuities. The proposal consists on an iterative incremental scheme that unwraps a sub-estimation of the residual phase at each iteration. The sub-estimation degree is controlled by an algorithm׳s parameter. We present an efficiently computational multigrid implementation based on a nested strategy: the process is iterated by using multiple resolutions. The proposal׳s performance is demonstrated by experiments with synthetic and real data, and successfully compared with algorithms of the state of the art.