基于多速率運動模型的多幀概率數(shù)據(jù)關聯(lián)算法
A Multi-scan Probabilistic Data Association Algorithm Based on Multi-rate Kinematic Model
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摘要: 該文指出Hong(2001)在多速率運動模型中關于過程噪聲的一處錯誤,提高了多速率運動模型狀態(tài)估計效果,并在此基礎上建立了多幀概率數(shù)據(jù)關聯(lián)算法.在確定多幀量測數(shù)據(jù)有效回波時,提出雙重門限方法,有效減少了多幀概率數(shù)據(jù)關聯(lián)算法的計算量.最后針對各種雜波密度情況對多幀量測數(shù)據(jù)概率數(shù)據(jù)關聯(lián)算法的性能進行了分析.Abstract: In this paper, a mistake made the multi-rate kinematic model is improv by Hong （2001） is pointed ed. And then, a multi-scan out and corrected, and the estimation performance of probabilistic data association algorithm is presented With the introduction of double gates, the calculation amount of the presented algorithm is decreased efficiently. Finally, the performance of multi-scan probabilistic data association is studied under different clutter density.
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