The Localization Algorithm Based on Maximum Likelihood Loops

For indoor localization based on ultrawideband (UWB), a high-precision localization algorithm based on maximum likelihood estimation (MLE) is proposed. The proposed algorithm employs the MLE principle to construct the likelihood function and optimizes it by the adaptive moment estimation (Adam) due to the unique property of the extremum of the likelihood function. The optimization limited range is determined by the “ $3\sigma $ ” rule, which can reduce search time and improve optimization efficiency. Compared with the conventional trilateration algorithm based on the least-squares method, the proposed algorithm makes comprehensive use of a priori probability knowledge and exhibits enhanced accuracy and robustness. It is demonstrated by both simulation experiments and experiments based on UWB scenarios.