卡尔曼滤波-基于单变量模型的卡尔曼滤波器实现-附项目源码-优质项目分享.zip

 This is a basic kalman filter library for unidimensional models that you can use with a stream of single values like barometric sensors, temperature sensors or even gyroscope and accelerometers. Repository Contents ------------------- * **/examples** - Example sketches for the library (.ino). Run these from the Arduino IDE. * **/src** - Source files for the library (.cpp, .h). * **keywords.txt** - Keywords from this library that will be highlighted in the Arduino IDE. * **library.properties** - General library properties for the Arduino package manager. Basic Usage ------------------- * **e_mea: Measurement Uncertainty** - How much do we expect to our measurement vary * **e_est: Estimation Uncertainty** - Can be initilized with the same value as e_mea since the kalman filter will adjust its value. * **q: Process Variance** - usually a small number between 0.001 and 1 - how fast your measurement moves. Recommended 0.01. Should be tunned to your needs. ```c++ SimpleKalmanFilter kf = SimpleKalmanFilter(e_mea, e_est, q); while (1) { float x = analogRead(A0); float estimated_x = kf.updateEstimate(x); // ... } ``` Example Briefs -------------- * **BasicKalmanFilterExample** - A basic example reading a value from a potentiometer in A0 and SimpleKalmanFilter class to generate estimates. * **AltitudeKalmanFilterExample** - Uses a BMP180 barometric sensor and the SimpleKalmanFilter class to estimate the correct altitude. Additional Documentation ------------------------- * **[Installing Additional Arduino Libraries](https://www.arduino.cc/en/Guide/Libraries)** - Basic information on how to install an Arduino library.