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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/11849

Title: 應用多偵測系統於雷達追蹤架構之研究
The Research of Applying a Multi-observation System to Radar Tracking Algorithm
Authors: 鍾翼能
Contributors: 電機工程學系
Keywords: 雷達追蹤系統;資料融合;多偵測器系統
Radar systems;Multiple sensor fusion algorithm;Multi-observation
Date: 2004-08
Issue Date: 2012-07-02T02:12:39Z
Publisher: 行政院國家科學委員會
Abstract: 在日新月異的航空及國防技術,由於目標物的性能速度,數目及變異性等皆較以往進步許多,為因應日益複雜的目標追蹤環境,雷達追蹤系統的性能必須同步提昇,才能達到洞燭先機,決戰千里之外的最高戰術目的。在目標的追蹤上,追蹤多個目標時比較複雜,也會常常造成感測器判斷上的錯誤,或者造成追蹤上極大的誤差,假設只用一個感測器偵測的話,通常會因偵測範圍過大,造成掃瞄間隔太大,以致於造成量測資料的遺失,若使用多個感測器來偵測目標的資料,可降低追蹤的錯誤率,使追蹤目標的誤差變小。此外,感測器之間的資料融合技術也是非常重要的。本研究計畫主要是探討多偵測器系統的估測方法,並處理資料間的融合和目標追蹤的相關問題,本研究計畫將結合不同位置感測器的資料,以改善追蹤上的問題,進而產生一個總體的估測值。
In the multi-target tracking systems, there are many disturbances from the outside environments to influence the estimated correctness. Moreover, when radar systems detect a large area and only use single sensor, it needs longer sampling interval to execute the tracking process and it may lost some data. Therefore, it is important to design a new structure of the radar systems to enhance the system performance. In this project, a mutiple sensor fusion algorithm is proposed to improve the tracking capability. This improved filter constructs of the Kalman filter and the adaptive procedure, and integrates some related techniques included one-step conditional maximum likelihood, recursive computation method, and multi-observation. By this way, we can diminish the errors resulted from producing maneuvering targets, then, the systems will get the better tracking results.
Relation: 計畫編號:NSC93-2212-E212-006; 研究期間:200408-200507
Appears in Collections:[電機工程學系] 國科會計畫

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