本文關(guān)鍵詞：機載多傳感器系統(tǒng)的協(xié)同跟蹤與調(diào)度研究　出處：《浙江大學》2017年碩士論文　論文類型：學位論文

  更多相關(guān)文章： 機載平臺 機動目標 協(xié)同跟蹤 智能調(diào)度

【摘要】：隨著科學技術(shù)的不斷發(fā)展,傳感器性能逐漸提升,傳感器數(shù)量與種類的增加,為現(xiàn)代作戰(zhàn)系統(tǒng)帶來了新的變化與思考。單一傳感器信息獲取已不能滿足作戰(zhàn)需要,為獲得最佳作戰(zhàn)效果,多種傳感器的合作不可或缺。為解決多傳感器系統(tǒng)的協(xié)同跟蹤與智能調(diào)度問題,本文結(jié)合實際機載環(huán)境與目標特性對系統(tǒng)的融合濾波算法與智能調(diào)度方案做出了一些改進。首先,以機載紅外傳感器與機載相控陣雷達為對象,結(jié)合最小二乘時間配準技術(shù)、基于最小均方誤差估計的異質(zhì)觀測融合技術(shù)和無跡交互式多模型濾波算法,提出了一種面向機動目標的異步異質(zhì)多傳感器融合跟蹤技術(shù),仿真驗證了該算法在異步非線性跟蹤融合時具有比降頻融合和普通的擴展交互多模型濾波算法更為優(yōu)越的跟蹤精度,可以滿足機動目標的跟蹤要求。其次,針對資源有限條件下的多傳感器調(diào)度問題,綜合考慮了環(huán)境條件、任務(wù)要求、目標狀態(tài)與傳感器特性,提出了一種基于修正的效能函數(shù)的多傳感器管理算法。該算法實現(xiàn)了機載傳感器在環(huán)境和資源有限約束條件下的面向跟蹤精度的自適應(yīng)調(diào)度。并以機載PAR、IRST和ESM為背景,仿真驗證了該調(diào)度方法的有效性。
[Abstract]:With the development of science and technology, the performance of sensors is gradually improved, and the number and types of sensors increase. It has brought new changes and thoughts to the modern combat system. The single sensor information acquisition can no longer meet the operational needs, in order to obtain the best combat results. The cooperation of multiple sensors is indispensable to solve the problems of cooperative tracking and intelligent scheduling in multi-sensor systems. In this paper, the fusion filtering algorithm and intelligent scheduling scheme of the system are improved by combining the actual airborne environment and target characteristics. Firstly, the airborne infrared sensor and airborne phased array radar are taken as the object. Combining the least square time registration technique, the heterogeneous observation fusion technique based on the least mean square error estimation and the unscented interactive multi-model filtering algorithm are proposed. An asynchronous heterogeneous multi-sensor fusion tracking technique for maneuvering targets is proposed. The simulation results show that the algorithm has better tracking accuracy than frequency reduction fusion and extended interactive multi-model filtering algorithm in asynchronous nonlinear tracking fusion. It can meet the tracking requirements of maneuvering targets. For the multi-sensor scheduling problem with limited resources, the environmental conditions, task requirements, target state and sensor characteristics are comprehensively considered. A multi-sensor management algorithm based on modified efficiency function is proposed, which realizes the adaptive scheduling of airborne sensors for tracking accuracy under the condition of limited environment and resource constraints, and uses airborne PAR. Based on IRST and ESM, the effectiveness of the proposed scheduling method is verified by simulation.
【學位授予單位】：浙江大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP212

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