Employing the Received Signal Strength Indicator (RSSI) from ZigBee is an economical and power-saving way of implementing Indoor distance measurement, leading to its widespread use in indoor applications. However, multipath effects, signal deterioration, and obstruction can compromise measurement precision. To tackle these challenges, this study provides an overview of methods of addressing the difficulties in ZigBee indoor distance measurement, primarily focusing on a recent combined filtering approach. This approach integrates filtering techniques, which include Kalman, Gaussian, Dixon’s Q-test, and Mean filtering. It utilizes losses that occur when signals are propagated to evaluate how the filtering algorithm affects precision in distance measurement. The result from the experiment reveals that the combined filtering method significantly enhances conventional ZigBee indoor distance measurement using RSSI. The mean of the error in the distance measurements, around 0.46 m, was significantly less than the errors obtained from unfiltered RSSI data. As a result, this approach achieves greater precision, making it highly efficient for indoor positioning applications.