基于稳健估计的射频参数求解及抗差能力探测

Radio Frequency Parameter Solving and Robust Resistance Detection Based on Robust Estimation

由于环境的影响使射频数据中存在粗差,这将对求解射频中对数距离路径损耗模型中的未知参数有一定的影响,使得定位时求出的距离产生偏差。针对这一问题,该项目使用稳健估计法对射频数据进行预处理,并且将稳健估计处理结果与最小二乘估计结果进行对比。结果表明:当粗差存在时,稳健估计法计算精度优于最小二乘估计,且该方法能够有效抵抗由于粗差的存在而导致对数距离路径损耗模型的崩溃。若将稳健估计方法应用于求解对数距离路径损耗模型中未知参数,将有益于射频的室内定位。

Due to the influence of environment, there will always be a gross difference in the RF data, which will have a certain influence on solving the unknown parameters in the log-distance path loss model in the radio frequency, which will cause the deviation of the distance obtained during positioning. In response to this problem, the idea of robust estimation was used to preprocess RF data and the robust estimation processing results were compared with the least squares estimation results. The results show that the robust estimation accuracy is better than the least squares estimation when the gross error exists. This method can effectively resist the log-distance path loss model collapse due to the existence of gross error. If the robust estimation method is applied to solve the unknown parameters in the model, this will be beneficial for indoor positioning of the radio frequency.