基于模糊綜合函數(shù)的航跡關(guān)聯(lián)算法
TRACK CORRELATION ALGORITHMS BASED ON FUZZY SYNTHETIC FUNCTION
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摘要: 本文運(yùn)用現(xiàn)代數(shù)學(xué)中的綜合分析方法,提出了模糊綜合航跡關(guān)聯(lián)算法,文中詳細(xì)討論了狀態(tài)估計(jì)向量間模糊綜合相似度的計(jì)算和評(píng)價(jià)方法,導(dǎo)出了三種典型模糊綜合函數(shù)的遞推式,研究了模糊綜合航跡關(guān)聯(lián)準(zhǔn)則,并通過仿真將它與兩種經(jīng)典方法進(jìn)行了比較。仿真結(jié)果表明,在密集目標(biāo)環(huán)境下和/或交叉、分岔和機(jī)動(dòng)航跡較多的場(chǎng)合,模糊航跡關(guān)聯(lián)算法的性能明顯優(yōu)于傳統(tǒng)方法,其正確關(guān)聯(lián)率比傳統(tǒng)方法提高了大約40％。Abstract: This paper presents fuzzy synthetic track correlation algorithms by using the synthetic analysis method in modern mathematics. In this paper, the computation and evaluation methods of the fuzzy synthetic measure of similarity between two state estimation vectors are discussed in detail, the recursive forms of three typical fuzzy synthetic functions are derived, the fuzzy synthetic track correlation criterion is described as well. Moreover, the algorithm is compared with two classical methods through simulation. The simulation results show that the performance of the fuzzy synthetic track correlation algorithm is much better than that of the classical methods in dense multitarget environments, more cross, split and maneuvering track situations. Under above situations, its correct correlation rate is improved about 40 percent over that of the classical methods.
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