Target estimation algorithm design using quantity data and target feature

The estimation algorithm plays an important role in a radar tracking system. An improved estimation approach using both quantity data and target feature is investigated in this article. The advantage of this approach is that the system will have better estimation based on more target information. A data association denoted one-step conditional maximum likelihood algorithm is applied to match between radar measurements and existing target tracks. Moreover, an adaptive estimator is applied to combine the quantity data and target feature for estimation problems. According to the simulation results, this approach can enhance the performance of multiple-target tracking systems.