Robert Grover Brown , Patrick Y. C. Hwang 经典的卡尔曼滤波书籍，清晰第4版。 In this updated edition the main thrust is on applied Kalman filtering. Chapters 1-3 provide a minimal background in random process theory and the response of linear systems to random inputs. The following chapter is devoted to Wiener filtering and the remainder of the text deals with various facets of Kalman filtering with emphasis on applications. Starred problems at the end of each chapter are computer exercises. The authors believe that programming the equations and analyzing the results of specific examples is the best way to obtain the insight that is essential in engineering work.

This is a practical guide to building Kalman filters that shows how the filtering equations can be applied to real-life problems. Numerous examples are presented in detail, showing the many ways in which Kalman filters can be designed. Computer code written in FORTRAN, MATLAB®, and True BASIC accompanies all of the examples so that the interested reader can verify concepts and explore issues beyond the scope of the text. In certain instances, the authors intentionally introduce mistakes to the initial filter designs to show the reader what happens when the filter is not working properly. The text carefully sets up a problem before the Kalman filter is actually formulated, to give the reader an intuitive feel for the problem being addressed. Because real problems are seldom presented as differential equations, and usually do not have unique solutions, the authors illustrate several different filtering approaches. Readers will gain experience in software and performance tradeoffs for determining the best filtering approach. The material that has been added to this edition is in response to questions and feedback from readers. The third edition has three new chapters on unusual topics related to Kalman filtering and other filtering techniques based on the method of least squares.Chapter 17 presents a type of filter known as the fixed or finite memory filter, which only remembers a finite number of measurements from the past. Chapter 18 shows how the chain rule from calculus can be used for filter initialization or to avoid filtering altogether. A realistic three-dimensional GPS example is used to illustrate the chain-rule method for filter initialization. Finally, Chapter 19 shows how a bank of linear sine-wave Kalman filters, each one tuned to a different sine-wave frequency, can be used to estimate the actual frequency of noisy sinusoidal measurements and obtain estimates of the states of the sine wave when the measurement noise is low.

QRD-RLS Adaptive Filtering Jos´e Antonio Apolin´ario Jr. I feel very honoured to have been asked to write a brief foreword for this book on QRD-RLS Adaptive Filtering – a subjectwhich has been close to my heart for many years. The book is well written and very timely – I look forward personally to seeing it in print. The editor is to be congratulated on assembling such a highly esteemed team of contributing authors able to span the broad range of topics and concepts which underpin this subject. In many respects, and for reasons well expounded by the authors, the LMS algorithm has reigned supreme since its inception, as the algorithm of choice for practical applications of adaptive filtering. However, as a result of the relentless advances in electronic technology, the demand for stable and efficient RLS algorithms is growing rapidly – not just because the higher computational load is no longer such a serious barrier, but also because the technological pull has grown much stronger in the modern commercial world of 3G mobile communications, cognitive radio, high speed imagery, and so on.

随机过程和滤波理论 作者：Andrew H

卡尔曼滤波比较好的一本书，

汉宁窗傅里叶变换matlab代码Matlab音频过滤 为了充分了解设备的性能，还必须在频域中分析信号。 这正是频谱分析仪的工作。 但是，应该指出的是，随着数字技术的飞速发展，这种区别变得越来越模糊。 一些示波器可以执行矢量信号分析，并且信号分析仪现在具有大量的时域测量功能。 但是，示波器针对时域测量进行了优化，而信号分析仪是频域测量的首选工具。 在频域中，复数信号（例如，包括一个以上的频率）被分离为它们的频率分量，并显示每个频率下的电平。 频域测量具有几个明显的优势。 首先，在频谱分析仪上很容易发现示波器上看不到的信息。 由于频谱分析仪能够缩小测量带宽，因此使用频谱分析仪测量信号还可以大大减少测量中存在的噪声量。 此外，当今的许多设备本质上都是面向频域的，因此必须在频域中进行分析，以确保不会受到相邻频率的干扰。 利用频谱的频域视图，可以轻松测量信号频率，功率，谐波含量，调制，杂散和噪声。 测量这些量后，仅使用频谱分析仪即可确定总谐波失真，占用带宽，信号稳定性，输出功率，互调失真，功率带宽，载波噪声比以及其他一系列测量结果。 频域测量（频谱分析）可以使用快速傅立叶变换（FFT）分析仪或通

卡尔曼滤波入门的经典教材

比较好的介绍kalman的书，Charles K.Chui，Guanrong Chen编写。第四版。

Recurrent neural networks are popular tools used for modeling time series. Common gradient-based algorithms are frequently used for training recur- rent neural networks. On the other side approaches based on the Kalman filtration are considered to be the most appropriate general-purpose training algorithms with respect to the modeling accuracy.

ROAD_MODEL_FUSION 用于AD / ADAS功能的道路模型融合 0.简介：- 我们在自驾车前安装了一系列摄像头传感器，用于ADAS / AD应用。该项目的目标是估算包括Ego Lane几何图形和Road Grid在内的道路模型 图1 ：（输入）测量值：自我通道边界相机的检测以类波峰参数的形式出现 1.估算输出： 1.1道路模型（自我车道边界线融合+道路几何+道路网格）：- 2.高级设计： 2.1到线迹关联的线测量以进行自我车道边界估计：- 2.2自我通道中线估计：- 2.3道路模型计算： 3.高级融合架构： 4.道路网格参数化：