Maximum Likelihood Joint Tracking and Association in Strong Clutter
نویسندگان
چکیده
We have developed a maximum likelihood formulation for a joint detection, tracking and association problem. An efficient non‐combinatorial algorithm for this problem is developed in case of strong clutter for radar data. By using an iterative procedure of the dynamic logic process “from vague‐to‐crisp” explained in the paper, the new tracker overcomes the combinatorial complexity of tracking in highly‐cluttered scenarios and results in an orders‐of‐magnitude improvement in signal‐ to‐clutter ratio.
منابع مشابه
Maximum Likelihood Joint Tracking and Association in a Strong Clutter
We have developed an efficient algorithm for the maximum likelihood joint tracking and association problem in a strong clutter for GMTI data. By using an iterative procedure of the dynamic logic process “from vague-to-crisp,” the new tracker overcomes combinatorial complexity of tracking in highly-cluttered scenarios and results in a significant improvement in signal-to-clutter ratio.
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