海杂波频谱的多重分形特性分析

本文主要研究海杂波频谱的多重分形特性并分析其影响因素．首先介绍了将多重分形理论引入到海杂波频谱分析中的理论基础，然后，采用X波段与S波段相参雷达实测数据验证海杂波频谱的多重分形特性，并采用多重分形去趋势起伏分析（MF-DFA）法对海杂波频谱进行多重分形特性分析、分析结果表明海杂波频谱是一种受长程相关性和概率分布共同影响的多重分形序列，并且频域多重分形参数广义Hurst指数对海杂波单元与目标单元具有一定的区分能力．此外．通过分析广义Hurst指数的影响因素还发现FFT时所采用的时间序列长度对广义Hurst指数影响相对较大，而FFT点数对其影响相对较小．     

带扰动的两类索赔模型的破产概率

本文考虑带随机干扰因素的两类索赔模型的破产问题,研究轻尾随机变量风险和过程的Lundberg指数,并给出了破产概率的表达式。     

变分蒙特卡罗方法及其对t-J模型的处理

本文介绍了蒙特卡罗方法的由来并简要地阐述了变分蒙特卡罗方法,给出了利用这种数值方法来处理超导理论中的t-J模型,讨论了在半满情况下t-J模型的能量基态,得到的数值结果支持A nderson所提出的RVB态就是或从某种程度上接近强关联系统的基态。     

测均匀激光器增益的新方法

在变耦合率测激光器增益方法的基础上，通过测定最佳输出耦合率和适当的数字变换，得到确定激光介质小信号增益的新方法。该方法避免了变耦合率方程拟合法所存在的问题，     

蒸发波导环境中基于ZMNL的海杂波仿真

针对海上蒸发波导环境中雷达目标的识别,提出了蒸发波导中基于零记忆非线性变换(ZMNL)的海杂波实现方法。该方法确定了海杂波K分布参数与蒸发波导高度间的关系,可得到不同蒸发波导高度、不同探测距离处的相关K分布杂波序列。给出了应用该方法产生杂波的具体步骤,仿真实验证明了该方法用于蒸发波导中海杂波建模的有效性。     

未知相关噪声下的广义波达方向估计算法

针对未知相关噪声情况下信源波达方向的估计,提出一种适用于均匀线阵的广义波达方向估计算法。该算法利用修正后的协方差差分算法,有效地消除了阵元间的相关噪声的影响。不同于以前的算法,提出的算法通过对接收数据的前后向空间平滑协方差矩阵进行共轭运算得到新的变换矩阵,因此修正后的协方差差分矩阵是个实部为零的厄米特矩阵,从而有效地降低了特征分解过程的计算量。本算法能解决相关噪声下,同时分辨相干与非相干信源的问题。理论分析和仿真结果均表明所提算法的有效性。     

Research on the frequency domain ∑△-DPCA

The frequency domain ∑A-DPCA processing （F-∑A-DPCA） is investigated in details and an improved scheme for the F-∑A-DPCA is proposed, which can significantly reduce the computational burden. In practice, because of the sum and difference beam pattern designed independently and other system errors, the clutter suppression of the time domain ∑A-DPCA processing （T-∑A-DPCA） is significantly degraded. However, the F-∑A-DPCA adaptively calculates the optimum gain ratio for motion compensation within each Doppler cells which is robust to system errors. Theoretical analysis and simulation results are presented to validate that the F-∑A-DPCA can achieve superior performance of clutter cancellation than the time domain processing, and its performance can be significantly increased if more pulses are used for the Doppler filtering. The improved approach is efficient, and feasible for real-time application.     

Krylov subspace method based on data preprocessing technology

The performance of adaptive beamforming techniques is limited by the nonhomogeneous clutter scenario. An augmented Krylov subspace method is proposed, which utilizes only a single snapshot of the data for adaptive processing. The novel algorithm puts together a data preprocessor and adaptive Krylov subspace algorithm, where the data preprocessor suppresses discrete interference and the adaptive Krylov subspace algorithm suppresses homogeneous clutter. The novel method uses a single snapshot of the data received by the array antenna to generate a cancellation matrix that does not contain the signal of interest （SOI） component, thus, it mitigates the problem of highly nonstationary clutter environment and it helps to operate in real-time. The benefit of not requiring the training data comes at the cost of a reduced degree of freedom （DOF） of the system. Simulation illustrates the effectiveness in clutter suppression and adaptive beamforming. The numeric results show good agreement with the proposed theorem.     

地物杂波特性的分析及抑制

本文讨论杂波的频谱分布,目标特性。FFT分析指出杂波频谱的数学模型及杂波频谱截止频率与风速的关系。设计一实用的抑制杂波系统,利用其正,负多卜勒分别处理为正、负电平,长时间积分可检测强杂波中的慢速目标。对CW雷达回波振幅统计特性作了理论探讨。     

Novel clutter map CFAR algorithm with amplitude limiter

The traditional clutter map constant false alarm rate (CM-CFAR) detector is affected by interference and self-masking[1] which will cause the low probability of detection. To solve these problems, a novel algorithm named clutter map CFAR with amplitude limiter (ALCM-CFAR) is proposed, in which the amplitude of the input signal is limited by a filter. The simulation results prove the effectiveness of ALCM-CFAR algorithm.