測(cè)量噪聲相關(guān)線性系統(tǒng)異類傳感器航跡融合
Tracking Fusion with Dissimilar Sensors for Linear Systems with Correlated Measurement Noises
-
摘要: 研究了異類傳感器航跡融合問(wèn)題。在測(cè)量噪聲相關(guān)的條件下，利用線性無(wú)偏最小方差估計(jì)的基本理論，通過(guò)對(duì)異類傳感器的狀態(tài)估計(jì)采用順序?yàn)V波的方法，得到了相關(guān)測(cè)量噪聲線性系統(tǒng)異類傳感器測(cè)量融合算法和狀態(tài)矢量融合算法。計(jì)算機(jī)數(shù)字仿真結(jié)果表明，由于考慮了測(cè)量噪聲之間的相關(guān)性，該算法比噪聲不相關(guān)融合算法具有更好的跟蹤性能，航跡跟蹤的精度得到了改善。Abstract: Tracking fusion with dissimilar sensors, which is a challenge work in multisensor fusion, is studied. Under the condition of general correlated measurement noises, the centralized and distributed tracking fusion question is investigated based on linear unbiased minimum variance estimation theory. The basic algorithms of measurement fusion and state vector fusion are presented in linear system with dissimilar sensors by the way of sequential filtering. These algorithms involve with not only the correlated measurement noises but also the configuration difference in local sensors, so information about multi-sensors fusion is increased. Through a simulation example it is indicated that the results of proposed algorithm is better than that classic ones where the measurement noises and processing noises are assumed to be uncorrelated.
-
Alouani A T, Rice T R. Linear data fusion. Proc. of the Annual Southeastern Symposium on System Theory, Knoxville, 1986:246 - 249.[2]Saha R K. Track-to-track fusion with dissimilar sensors. IEEE Trans. on AES 1996, 32(3): 1021 - 1029.[3]左東廣,韓崇昭,魏瑞軒,等.相關(guān)噪聲情況下航跡的關(guān)聯(lián)及融合算法.電子學(xué)報(bào),2002,30(8):1117-1120.[4]韓崇昭,王月娟,萬(wàn)百五.隨機(jī)系統(tǒng)理論.西安:西安交通大學(xué)出版社,1987.[5]Y Bar Shalom. On the track-to-track correlation problem. IEEE Trans. onAC, 1981, 26(2): 571 - 572.[6]何友,王國(guó)宏,彭應(yīng)寧,等.多傳感器信息融合及應(yīng)用.北京:電子工業(yè)出版社,2000. -
計(jì)量
- 文章訪問(wèn)數(shù): 2090
- HTML全文瀏覽量: 98
- PDF下載量: 1197
- 被引次數(shù): 0
下載:
