ID	原文	译文
7044	在译码复杂度方面,两种方案对原始消息传递算法(message passing algorithm,MPA)的译码复杂度无影响,但采用E-rotation方案时,接收端采用PEIT-MPA,译码复杂度更低。	In decoding complexity, two kinds of solutions to the original message passing algorithm (message passing algorithm, MPA) the decoding complexity of no effect, but the E - rotation, the receiver USES the PEIT - MPA, lower decoding complexity.
7045	针对传统无迹卡尔曼滤波(unscented Kalman filter,UKF)在系统状态发生突变时估计精度下降的问题,将改进的强跟踪滤波算法与基于高斯概率密度高阶导的无迹卡尔曼滤波算法(high order probability density derivative,HUKF)相结合,提出了高阶强跟踪无迹卡尔曼滤波方法(high order strong tracking UKF,HSUKF)。	For no trace traditional Kalman filter (unscented Kalman filter, UKF) in mutations in estimates of the decline of the precision of the system state, will improve the strong tracking filtering algorithm based on gaussian probability density high derivative no trace of the Kalman filtering algorithm (high order aim-listed probability density derivative, HUKF), the combination of the tracking no trace of higher-order strong Kalman filtering method (high order strong tracking UKF, HSUKF).
7046	该算法采用高斯概率密度函数高阶导数的极值作为Sigma样点进行无迹转换,通过样本点捕捉更高阶的中心矩来提高非线性变换近似精度。	The algorithm USES the gaussian probability density function of higher derivative extremum as Sigma sample to convert the no trace, through the center of the sample points to capture a higher order moment to improve the nonlinear transform approximation accuracy.
7047	将改进的强跟踪滤波算法引入到HUKF中,通过渐消因子修正预测新息协方差和预测互协方差矩阵,强迫新息正交,在不增加计算复杂度的前提下提高了算法在状态发生突变时的适应能力。	Will improve the strong tracking filtering algorithm is introduced into the HUKF, new interest through the fading factor revision covariance and predicted covariance matrix, forcing new orthogonal breath, without any increase in computational complexity under the premise of improving the mutations in the adaptability of the state.
7048	将本文算法应用于时差频差的无源跟踪中,通过对目标状态发生突变的跟踪问题进行数值仿真和实例论证表明HSUKF算法兼具了计算复杂度低和估计精度高的特性,且在系统状态发生突变的情况下表现出良好的滤波性能。	The algorithm was applied to the time difference frequency offset in the passive tracking, through to the target state mutates tracking problem of numerical simulation and an argument shows HSUKF algorithm combines the characteristics of the low computational complexity and high estimation precision, and in the case of system state mutates showed good filtering performance.
7049	在信号相关杂波背景下,现有方法大部分均基于频域进行雷达估计波形设计,这将引起相位信息的缺失从而导致波形变换到时域后性能降低。	Under the background of the clutter signal, most existing methods are based on frequency domain is used to estimate the radar waveform design, this will cause the lack of phase information leading to the waveform transformation after the time domain performance degradation.
7050	针对上述问题,同时兼顾放大器的非线性特性,提出了一种基于时域的低峰均比(peak-to-average power ratio,PAR)估计波形设计方法。	Aiming at these problems, both the nonlinear characteristics of the amplifier, this paper proposes a resources based on time domain than (peak - to - business power thewire, PAR) estimated waveform design method.
7051	首先,根据最大互信息准则在时域上构建了优化问题模型;	First of all, based on maximum mutual information criterion in time domain, optimization model is constructed,
7052	然后,基于序列线性规划思想,将非凸的优化问题松弛为凸问题,并求得波形矩阵的近似解;	Then, based on the sequential linear programming ideas, will the nonconvex optimization problem for convex relaxation, and the approximate solution of waveform matrix is obtained;
7053	最后,对该波形矩阵解进行逼近,使得新的波形矩阵满足Toeplitz结构,进而提取出波形向量解。	Finally, the waveform matrix solution is approaching, make new waveform matrix satisfy Toeplitz structure, and then extract the wave vector solution.