MIMO系统功率比特自适应算法研究

发射功率受限的自适应调制系统,由于调制方式有限,实际使用的发射功率通常小于受限的发射功率,对这一部分剩余功率进行再分配和利用,能够提高频谱效率。文章对M IMO系统中功率和比特自适应算法进行了研究,提出对剩余功率在空域进行再分配的自适应算法。仿真结果表明,在空域采用等功率分配,再进行空域剩余功率再分配,能够提高频谱效率,并且复杂度低,易于实现。     

基于进化神经网络的组合导航系统滤波算法研究

组合导航系统中,卡尔曼滤波算法的估计特性依赖于精确的系统模型和准确的外观测数据.任何一个条件不满足将导致滤波精度下降甚至发散.为此,本文引入进化神经网络和自适应卡尔曼滤波技术.仿真结果证明,文中所提算法能够有效克服常规卡尔曼滤波的缺点,并保持较高的精度.     

探空火箭图像压缩算法研究

结合探空火箭图像系统需求, 提出了一种基于小波变换编码, 即基于MSPIHT的自适应差分算术编码(MSPIHT Adaptive Differential Arithmetic Coding for image, MADAC)的图像压缩算法. 该算法对经过量化编码之后的数据 进行熵编码. 实验结果表明, MADAC算法具备探空火箭图像系统所要求的分辨 率、帧速率及压缩率可调的功能, 且易于硬件实现.     

导航解算中的有色噪声及其协方差矩阵自适应拟合

使用Kalman滤波进行动态导航定位解算需要涉及函数模型和随机模型, 而在实际应用中, 精确的函数模型和随机模型很难直接给出, 因此, 动态Kalman滤波的精度和可靠性将会受到函数模型误差和随机模型误差的影响. 在假设观测噪声和动力学模型噪声主要是具有一阶自相关特性的有色噪声的基础上, 提出了一种基于移动窗口的有色噪声函数模型和随机模型的自适应拟合法. 给出了计算有色噪声估值和噪声协方差矩阵的表达式, 并利用实测数据验证了模型及算法的可行性和实用性. 计算结果表明, 该算法能有效抵制有色噪声对导航滤波结果的影响.     

深空探测器接近段自适应滤波方法研究

天文导航是一种广泛应用于深空探测任务的全自主导航方法.基于状态模型和量测模型的非线性卡尔曼滤波方法在天文导航中被广泛使用.卡尔曼滤波要求状态和量测模型误差是高斯白噪声且先验协方差信息已知,但在深空探测器天文导航系统中,状态模型和量测模型噪声通常不能精确知道且是时变的.因此,自适应卡尔曼滤波器广泛用于解决状态和量测模型误差未知且时变的问题.本文首先结合火星探测器接近段的实际情况分析了火星探测器接近段模型噪声的时变特性,然后对三种常用的在线调节自适应滤波方法在火星探测接近段的滤波表现进行了仿真实验.     

基于变步长LMS算法的空域抗干扰技术研究

信息传输的可靠性、安全性和实时性在国防应用中至关重要。针对复杂且电磁干扰强的战场环境下所需有用信息无法准确接收以及多模块集成化等问题,本文创建函数,经蒙特卡洛实验计算出参数最优值,提出了一种基于椭圆函数的变步长LMS自适应波束形成算法。对比本文算法与其他算法达到稳态的时间,结果表明：在保证稳态误差的前提下,该算法在收敛速度上优于已有的变步长LMS算法,并且运算量小。通过模拟不同来波方向的干扰信号绘制波束方向图,仿真结果证明本文算法指向性强,对干扰的抑制度高,可以实现对有用信号有效地接收、干扰信号有效地抑制及设备集成化小型化的需求。     

Neural adaptive control for a ground experiment of the space proximity operation in a six-degree-of-freedom micro-gravity simulation system

In this study, a neural adaptive controller is developed for a ground experiment with a spacecraft proximity operation. As the water resistance in the experiment is highly nonlinear and can significantly affect the fidelity of the ground experiment, the water resistance must be estimated accurately and compensated using an active force online. For this problem, a novel control algorithm combined with Chebyshev Neural Networks(CNN) and an Active Disturbance Rejection Control(ADRC) is proposed. Sp...     

Application of improved active disturbance rejection control algorithm in tilt quad rotor

The Tilt Quad Rotor(TQR) has complex dynamics characteristics, especially in conversion mode. It is difficult to build the dynamic model of the TQR and the environmental factors have a great influence on it. To solve the problem of control in conversion mode of TQR, this paper carries out the design of the controller based on improved Active Disturbance Rejection Control(ADRC). According to the characteristics of flight in conversion mode, Tracking Differentiator(TD) with explicit model is used ...     

State estimate for stochastic systems with dual unknown interference inputs

Stochastic system state estimation subject to the unknown interference input widely exists in many fields, such as the control, communication, signal processing, and fault diagnosis. However, the research results are mostly limited to the stochastic system in which only the dynamic state model or the measurement model concerns the individual unknown interference input, and the state model and the measurement model are both with the same unknown interference input. State estimate of the stochastic systems where the state model and the measurement model contain dual Unknown Interference inputs (dual-UI) with different physical meanings and mathematical definitions is concerned here. Firstly, the decoupling condition with the Unknown Interference input in the State model (S-UI) is shown, which introduces the decoupled system with the adjacent Measurement concerned Unknown Interference inputs (M-UI) appearing in the state model and the measurement model. Then, through defining the Differential term of the adjacent M-UI (M-UID), the equivalent system with only M-UID in the state model is obtained. Finally, considering the design freedom of the equivalent system, the decoupling filter in the minimum mean square error sense and the adaptive minimum upper filter with different applicable conditions are represented to obtain the optimal and sub-optimal state estimate, respectively. Two simulation cases verify the effectiveness and superiority compared with the traditional methods.     

Hypersonic vehicle aerodynamic design using modified sequential approximate optimization

Hypersonic vehicles are receiving increased attention within the aerospace community due to their high cruise speed and long-range capabilities. In this paper, a modified Sequential Approximate Optimization method is proposed for an optimized aerodynamic design of a hypersonic vehicle. As part of this approach, a constrained experimental design method is developed to handle the constraints more efficiently. A radial basis function is used to surrogate time-consuming CFD analysis. An efficient and more robust numerical mesh morphing scheme for the hypersonic vehicle is developed for the generation of high-quality meshes. Within this paper, a novel adaptive infilling strategy is proposed which uses an inaccurate search technique coupled with an elite archive. This allows the location of a more promising sample region and hence improves the surrogate accuracy, thereby further enhancing the optimization efficiency. A hypersonic vehicle aerodynamic design problem is solved using the proposed approach and satisfactory results are obtained at much lower computational costs. The lift-to-drag ratio is increased by 23.8% when compared with the base configuration while also satisfying the volume and lift constraints. The pressure and Mach contours have been compared with those of the base configuration and the results demonstrate the strength of the optimized configuration. The modified sequential approximate optimization for designing an improved hypersonic vehicle is worth referencing in future work.