NLOS环境中基于二次修正的RSSI测距算法

摘要

RSSI ranging is quite simple to achieve even without external devices, but the accuracy is low and sensitive to the environment. In order to reduce the RSSI ranging error in NLOS environments, proposes an RSSI ranging algorithm based on the sec⁃ond correction. Firstly, we preprocess the RSSI value with a Kalman filter. Then, we fit the propagation equation using the least square method. Lastly, we calculate the range value using an unscented Kalman filter. Experimental result indicates that the algo⁃rithm can reduce the ranging error and improve the ranging accuracy in NLOS environments.%RSSI测距实现简单，无需添加外部设备，但测距精度较低、易受环境影响。为了降低RSSI测距在NLOS环境中的误差，提出了一种基于二次修正的RSSI测距算法。首先用卡尔曼滤波对RSSI值进行预处理，然后采用最小二乘法拟合出传播方程，最后利用无迹卡尔曼滤波求出距离值。实验结果表明，该算法能降低NLOS环境中的测距误差，提高测距精度。