数据融合matlab代码传感器融合示例 传感器融合和因子图实验的示例。 包含以下数据： 全球定位系统 国际货币联盟 晴雨表 相机功能轨迹 导航传感器数据以格式存储。 感谢FFI的优秀同事允许共享这些数据！ 可执行文件： ：绘制原始数据。 ：GPS-IMU批量融合。 ：GPS-IMU固定滞后融合。 ：GPS-IMU与ISAM2融合。 安装依赖项 从头开始的Ubuntu的详细过程。 选择您需要的部分。 要点：安装编译器，cmake，curl和git sudo apt install -y \ build-essential \ cmake \ curl \ git \ wget 安装本征 我们可以使用apt安装足够的Eigen版本。 另外，我们安装了blas和lapack。 sudo apt install -y \ libblas-dev \ liblapack-dev \ libeigen3-dev 安装Sophus # Clone the repository (download the code) from GitHub. git clone --depth 1 https://g

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Because of their high noise immunity and low static power supply drain, complementary metal-oxide-semiconductor (CMOS) devices produce less heat than other forms of logic and allow a high density of logic functions on a chip. These beneficial characteristics have fueled the use of CMOS image sensors in consumer electronics, robot vision, biotechnology, and medicine. With the introduction of smart functions in CMOS image sensors, even more versatile applications are now possible. Exploring this popular technology, Smart CMOS Image Sensors and Applications focuses on the smart functions implemented in CMOS image sensors as well as the applications of these sensors. After discussing the history of smart CMOS image sensors, the book describes the fundamental elements of CMOS image sensors. It covers some optoelectronic device physics and introduces typical CMOS image sensor structures, such as an active pixel sensor (APS). Subsequent chapters elucidate the functions and materials of smart CMOS image sensors and present examples of smart imaging. The final chapter explores various applications of smart CMOS image sensors. Several appendices supply a range of information on constants, illuminance, MOSFET characteristics, and optical resolution. This book provides a firm foundation in existing smart CMOS image sensor technology and applications, preparing you for the next phase of smart CMOS image sensors.