I'm utilizing the LM algorithm to solve a trakcing problem. I found that sometimes the LM algorithm will converge to the wrong position at the beginning, and then continue to converge to the wrong position.I would like to know, given the input data and initial parameters of LM, is it possible to model the event that the LM algorithm converges correctly? I want to infer the probability that the LM algorithm converges to the correct value.
Currently I can only adjust the initial parameters as close as possible to the initial position of the object I'm tracking to ensure initial convergence.