TOA Localization Algorithm Based on Least Squares Method and LM Algorithm Neural Network

A Time of Arrival (TOA) algorithm based on the signal arrival time from the neural network training method trainlm is proposed because different complicated indoor settings result in low positioning accuracy and diverse influencing factors. Additionally, simulation experiments were carried out based on the BP neural network algorithm in order to identify the model [1], and the trainlm training method was employed in order to lessen the influence of the surrounding environment, noise, and other factors on the outcomes. Following several trials, the data from the landing sites' densest areas were selected as performance evaluation indicators. Furthermore, the least squares method and trainlm are well-known and highly effective algorithms that can greatly increase localization accuracy. Additionally, research has shown that the technique is highly useful in a variety of settings.