基于高斯滤波运动预测模型改进RSSI测距算法研究

Research on Improved RSSI Positioning and Ranging Algorithm Based on Gaussian Filtering Motion Prediction Model

在测距模型中有多种信号传播模型,经常被用到的是RSSI(Received Signal Strength Indication)测距。由于复杂的室内环境对信号的强度变化影响很大,传统的RSSI测距已经不能满足实际应用的需求,为了减小对实测信号的扰动,在RSSI基本测距算法的基础上,提出一种改进的RSSI测距算法——基于高斯滤波运动预测模型的改进RSSI测距算法,仿真结果表明改进后的算法相比传统的RSSI测距算法在精度上有了明显的提高。

There are many signal propagation models in the ranging model, and RSSI(Received Signal Strength Indication) ranging is often used. Because the complex indoor environment has a great influence on the change of signal strength, the traditional RSSI ranging can no longer meet the needs of practical applications. In order to reduce the disturbance to the measured signal, this article proposes a basic ranging algorithm based on the RSSI. Improved RSSI ranging algorithm--Improved RSSI ranging algorithm based on Gaussian filter motion prediction model. Simulation results show that the improved algorithm has a significant improvement in accuracy compared with the traditional RSSI ranging algorithm.