Moate

用matlab编写,由浅入深实现卡尔曼滤波器跟踪,滤波功能()

这是一份低轨道卫星建模的资料，比较简洁适合学习(This is a low-orbit satellite modelling data, relatively simple and suitable for learning, recommend to see)

在信号发送后，接收方需要实现位同步才能正确解码(after signal is sent, receiver need bit syn to decode correctly)

可以实现利用chan算法完成三维空间目标定位(Chan algorithm can be used to complete the three-dimensional space target location.)

一个简单的verlog HDL教程，内容比较详细，可读性较高。(A simple verlog HDL tutorial, more detailed content, high readability.)

说明：  利用Matlab软件来实现基于滤波的正交频分复用F-OFDM(use the matlab to achieve the F-OFDM)

说明：  前已提出的频谱感知方法主要包括匹配滤波器检测、 能量检测、 循环平稳特征检测以及多分辨率频谱感知. 这些方法均为单节点感知方法.然而，在阴影和深度衰落情况下， 单个节点的感知结果并不可靠， 因此， 需要对多个节点的感知结果进行融合，以提高检测可靠性， 即协作感知技术. 文献采用“或” 准则对各个 CR 感知结果进行融合. 文献则提出了基于 D-S 证据理论的协作频谱感知算法，虽然该算法的性能比“或” 准则或“与”准则要好， 但需要存储大量历史信息， 算法的计算复杂度也很高. 文献中分析了采用似然比检测(likelihood ratio test， LRT) 的软判决与采用“与” 准则的硬判决的性能， 结果表明采用软判决的协作感知性能更优(Previously proposed spectrum sensing methods mainly include matched filter detection, energy detection, cyclostationary feature detection and multi-resolution spectrum sensing. These methods are all single node sensing methods. However, in the case of shadow and deep fading, the sensing results of single node are not reliable, so, It is necessary to fuse the sensing results of multiple nodes to improve the detection reliability, i.e. cooperative sensing technology. In the literature, "or" criterion is used to fuse the CR sensing results. In the literature, a cooperative spectrum sensing algorithm based on D-S evidence theory is proposed. Although the performance of the algorithm is better than "or" criterion or "and" criterion, a large amount of historical information needs to be stored, The computational complexity of the algorithm is also very high. In the literature, the performance of the soft decision based on the likelihood ratio test)

用MATLAB实现ook调制方式的信号误码率仿真(Simulation of signal error rate of ook modulation using MATLAB)

PSK Uniform Fading using SNR and BER

MIMO下天线选择matlab仿真实现，比较简单(MIMO antenna selection under)