SunV1

PLL的simulink仿真模型，希望能有用，谢谢大家(PLL in simulink simulation models, hoping to be useful, thank you)

Selective Harmonic Elimination PWM

共最简单的时间序列的预测入门，最后一直讲到ARMA模型，有理论和matlab程序(Total easiest time series prediction entry, the last has been talked about ARMA model theory and matlab program)

将带噪声的音频文件中的噪声滤除掉，得到原始音频信号(The noisy audio file noise filtered out to obtain the original audio signal)

解BSDE方程的欧拉算法 采用显式格式 隐式格式需要进行皮卡迭代(Euler-Maruyama Method for BSDEs )

五元十字阵的目标被动声定位算法仿真，给出目标方位角估计精度、俯仰角估计精度及距离估计精度，以及目标测向和测距的精度(Five-goal cross array orientation algorithm for passive acoustic simulation)

这是阵列信号处理中的一种music算法进化版，root music算法。(this is a matlab program about root_music.)

在运载体运动情况下,提出了一种适用于捷联惯导系统(SINS)初始对准的新算法,该算法以惯性空 间为过渡参考基准,即建立了初始时刻惯性坐标系(i0系)和初始时刻捷联惯组惯性坐标系(ib0系)两个惯性坐标 系。将捷联惯组坐标系(b系)与导航坐标系(n系)之间的初始对准姿态矩阵的实现分解为三步骤:(1)通过地理 位置和初始对准时间求解i0系至n系的变换矩阵 (2)通过惯导比力方程变形,引入测速仪速度辅助,求解从ib0 系至i0系的常值变换矩阵 (3)使用姿态更新算法实时计算b相对于ib0系的变换矩阵。最后,载车运动环境下的 初始对准试验结果表明航向角对准精度达到了0.1b(1R)。 (On the moving base, a new initial alignment algorithm for strapdown inertial navigation system (SINS) is proposed. In this algorithm, two special inertial frames, the initia-l time inertial frame (i0frame) and the initia-l time SINS body inertial frame (ib0frame), are defined and are selected as transition reference frames. The calculation of initial alignment direction cosine matrix (DCM) between SINS body frame (bframe) and nav- igation reference frame (nframe) is expanded into three parts: (1) the DCM betweeni0frame andnframe is easily obtained via local geographical coordinates and initial alignment time (2) by expressing SINS specific force equation inbframe and by the aid of external velocity log, the constant DCM fromib0frame toi0frame is achieved (3) attitude updating using gyro samples gets the DCM betweenbframe andib0frame. In the end, some vehicular tests are carried out on the moving base and the accuracy of azimuth reaches about 0.1b(1R). )

太阳方位计算，通过输入当地经度纬度，以及时间时区，计算当地任意时刻太阳样的高度角方位角。matlab程序(sun position)

又一个计算kalman滤波器的matlab程序！(Another calculation kalman filter matlab program!)