Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Target estimation algorithm design using quantity data and target feature | Lu and Lin EURASIP Journal on Advances in Signal Processing 2011 2011 7 http content 2011 1 7 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Target estimation algorithm design using quantity data and target feature Chung-Lain Lu and Chih-Min Lin Abstract 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. Keywords Quantity data Target feature Data association Adaptive estimator Introduction In the tracking procedure estimation algorithm is the key technique for multiple-target tracking systems. Once target measurements are received an important process denoted data association must be applied to determine the exact associated relationship between measurements and predicted objects. In the literatures some popular algorithms for data association were addressed such as the joint probabilistic data association JPDA 1 one-step conditional maximum likelihood algorithm 2 and some applications using neural networks to tracking systems 3 4 . In real applications the moving targets usually include both maneuvering and non-maneuvering situations. If the targets are with maneuvering the acceleration of targets usually causes the tracking in the radar system deviated from the trajectory. Consequently how to detect and estimate the maneuvering status effectively is very important. The .
