CAJ | 학술논문

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。
RSSI측거실현간단，무수첨가외부설비，단측거정도교저、역수배경영향。위료강저RSSI측거재NLOS배경중적오차，제출료일충기우이차수정적RSSI측거산법。수선용잡이만려파대RSSI치진행예처리，연후채용최소이승법의합출전파방정，최후이용무적잡이만려파구출거리치。실험결과표명，해산법능강저NLOS배경중적측거오차，제고측거정도。
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.