空间不相关信道下STBC-QOTDM性能分析

对准正交时分复用(QOTDM)后的样点序列采用空时分组编码(STBC)构造出STBC-QOTDM方式的多输入多输出(MIMO)系统,利用高斯Q函数的变形表示式、信道衰落的概率密度函数及其特征函数三者之间的积分关系,推导出该系统在空间不相关Rayleigh信道下由样点错误导致的符号错误概率(SEP)的闭式解。并对STBC-QOTDM系统进行Monte Carlo仿真,验证了STBC-QOTDM系统的性能。     

主动声纳梳状谱信号研究

研究了若干种主动声纳梳状谱信号的发射效率、测量精度以及基于多普勒的抗混响性能。给出了一种由多个单频线谱组成的梳状谱信号TP信号的设计方案。仿真及湖试实验结果表明,TP信号具有相对较高的发射效率,相对较高的测量精度,在低多普勒和高多普勒下相对较好的抗混响性能,是浅海中主动声纳的择优信号。     

A moving three-level atom interacting with a two-mode field: some atom–field aspects

In this paper, the interaction of a moving three-level atom and a two-mode quantized electromagnetic cavity field is extended to involve the effects of the atomic motion. Detuning parameters, Kerr nonlinearity, Stark shift contributions and arbitrary forms of intensity-dependent atom–field coupling have been taken into account. The constants of motion and the wave function, when the atom is initially prepared in superposition states and the field is initially prepared in squeezed coherent states, have been obtained. We calculate some statistical aspects such as atomic inversion, purity, Mandel Q-parameter, cross-correlation, momentum increment, momentum diffusion and Husimi Q-function.     

空间相关信道下STBC-QOTDM性能分析

对准正交时分复用(QOTDM)后的样点序列采用空时分组编码(STBC)构造出STBC-QOTDM方式的多输入多输出(MIMO)系统,利用高斯Q函数的变形表示式、信道衰落的概率密度函数及其特征函数三者之间的积分关系推导出该系统在空间相关Rayleigh信道下由样点错误导致的符号错误概率(SEP)的闭式解,该闭式解可以用于评价STBC-QOTDM系统的误符号性能。对STBC-QOTDM系统进行了Monte Carlo仿真,验证了STBC-QOTDM系统SEP的准确性。     

声纳信号抗混响能力和声兼容性分析

作为主动声纳系统设计的三大要素之一,主动声纳波形设计在主动声纳系统设计中占有重要的地位。主动声纳信号波形不仅决定了接收信号的处理方式,还直接影响到系统的分辨率、测量精度、抗干扰能力以及目标跟踪性能等各个方面。利用信号的Q函数和互模糊度函数,研究信号的抗互相能力和声兼容性能。并通过实际的海试数据分析,验证了这种分析方法的可行性、有效性和正确性。     

High-order exponential approximations for the Gaussian Q-function obtained by genetic algorithm

This article presents new and accurate approximations for the Gaussian Q-function, which is an important tool in the field of communication theory. A genetic algorithm was employed to find the optimum coefficients of the proposed approximations. The accuracy of the new approximations was examined and compared with those of previous works in the literature. It was shown that the presented high-order exponential approximations provide better accuracy compared to the previously introduced approximations, in general, at the cost of slightly increased mathematical complexity.     

Design of a completely model free adaptive control in the presence of parametric,non-parametric uncertainties and random control signal delay

In this paper, an adaptive controller is developed for discrete time linear systems that takes into account parametric uncertainty, internal-external non-parametric random uncertainties, and time varying control signal delay. Additionally, the proposed adaptive control is designed in such a way that it is utterly model free. Even though these properties are studied separately in the literature, they are not taken into account all together in adaptive control literature. The Q-function is used to estimate long-term performance of the proposed adaptive controller. Control policy is generated based on the long-term predicted value, and this policy searches an optimal stabilizing control signal for uncertain and unstable systems. The derived control law does not require an initial stabilizing control assumption as in the ones in the recent literature. Learning error, control signal convergence, minimized Q-function, and instantaneous reward are analyzed to demonstrate the stability and effectiveness of the proposed adaptive controller in a simulation environment. Finally, key insights on parameters convergence of the learning and control signals are provided.     

Online optimal and adaptive integral tracking control for varying discrete-time systems using reinforcement learning

Conventional closed-form solution to the optimal control problem using optimal control theory is only available under the assumption that there are known system dynamics/models described as differential equations. Without such models, reinforcement learning (RL) as a candidate technique has been successfully applied to iteratively solve the optimal control problem for unknown or varying systems. For the optimal tracking control problem, existing RL techniques in the literature assume either the use of a predetermined feedforward input for the tracking control, restrictive assumptions on the reference model dynamics, or discounted tracking costs. Furthermore, by using discounted tracking costs, zero steady-state error cannot be guaranteed by the existing RL methods. This article therefore presents an optimal online RL tracking control framework for discrete-time (DT) systems, which does not impose any restrictive assumptions of the existing methods and equally guarantees zero steady-state tracking error. This is achieved by augmenting the original system dynamics with the integral of the error between the reference inputs and the tracked outputs for use in the online RL framework. It is further shown that the resulting value function for the DT linear quadratic tracker using the augmented formulation with integral control is also quadratic. This enables the development of Bellman equations, which use only the system measurements to solve the corresponding DT algebraic Riccati equation and obtain the optimal tracking control inputs online. Two RL strategies are thereafter proposed based on both the value function approximation and the Q-learning along with bounds on excitation for the convergence of the parameter estimates. Simulation case studies show the effectiveness of the proposed approach.     

基于SA-MCMC算法的非线性测量误差模型的影响分析

研究了非线性测量误差模型的影响分析.首先把模型中有误差的不可观测的数据当作是缺失数据,接着用SA-MCMC算法得到了模型参数的最大似然估计,然后考虑用Q函数代替可观测数据的对数似然函数来进行影响分析,得到了建立在Q函数上的局部影响分析的诊断统计量.最后用具体的例子说明了诊断统计量的有效性.