基于融合算法的空气污染监测高度测量系统

The Height Measurement System of Air Pollution Monitoring Based on Fusion Algorithm

在空气质量监测中,有时需要在不同的高度上采集空气污染数据,但传统的GPS定位系统对于海拔高度的定位精度较差,为此,设计了由GPS和气压计组成的高度测量系统,通过对气压传感器进行温度补偿,获得高精度的气压高度信息;并对气压计和GPS进行数学建模,建立了卡尔曼滤波算法的状态方程和观测方程,通过离散化对GPS和气压计的高度信息进行在线数据融合,获得高精度的高度信息;最后,通过实验数据验证了该高度测量系统具有较高的精度,可以在空气污染高空监测等领域广泛推广。

In air quality monitoring, and sometimes need to collect air pollution data in different heights. However, the traditional GPS positioning system is not good at altitude. For this reason, the new kind of height measurement system is designed. Through the barometric pressure sensor for temperature compensation, high accuracy pressure altitude information is obtained. GPS and barometer are mathematical modeled. The state equation and observation equation of a Kalman filter are established. Highly information fusion is through discrete model. Finally, the experimental data verifies that the height of the combination system has a high precision. The new kind of height measurement system can be widely promoted in areas such as high-altitude surveillance of air pollution monitoring.