A Hybrid Multi-sensor Multi-target Tracking Scheme with MLE and ANFIS

Abstract

Abstract−The Joint Probabilistic Data Association (JPDA) solves single sensor multi-target tracking in clutter, but it cannot be used directly in multi-sensor multi-target tracking (MMT) and has high computational complexity with the number of targets and the number of returns. This paper presents a hybrid method to implement MMT by combing Maximum Likelihood Estimation (MLE) with Adaptive Neuro-Fuzzy Inference System (ANFIS). The MLE is applied to classify the same source observations at one time into the same set, then the cheap JPDA(CJPDA) approach is used to calculate the data association probability, and ANFIS is used to realize the MMT. The computer simulations indicate that this scheme achieves MMT perfectly with higher precision and easy realization.