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  本文選題：MIMO雷達 + 遺傳算法��； 參考：《電子科技大學》2017年碩士論文

【摘要】：多輸入多輸出(MIMO)雷達作為一種新體制雷達,因其良好的空間分集增益和多路增益,使其在克服目標雷達截面積(RCS)閃爍及抗干擾等方面具有優(yōu)勢。其中分布式MIMO雷達擁有廣布的天線,其性能很大程度上依賴于雷達天線的位置,若不對其雷達站點進行優(yōu)化布站,其性能將會受到限制。分布式MIMO雷達布站要同時考慮多個天線的位置,是一個復雜高維問題,鑒于智能算法在解決這類問題上的優(yōu)勢,因此基于智能算法的分布式MIMO雷達布站問題也成為國內外學者的研究熱點。以往的研究未有效考慮變化的監(jiān)視需求,未有效利用雷達網(wǎng)絡相關的大數(shù)據(jù)信息,往往難以滿足實際的監(jiān)視需求。本文針對分布式MIMO雷達布站的實際需求,在智能算法求解的基礎上,研究了基于變化監(jiān)視需求和基于大數(shù)據(jù)的布站方法,具體如下:1.針對分布式MIMO雷達布站問題,確立了以覆蓋率為優(yōu)化指標的問題模型,將監(jiān)視區(qū)域離散化為多個分辨單元,若雷達系統(tǒng)對該單元的檢測概率達到某一門限,則認為該單元被覆蓋,在此基礎上推導出了檢測概率的簡化表達式。2.針對變化的監(jiān)視需求,研究了一種基于遺傳算法的MIMO雷達動態(tài)部署方法,并對該方法與窮舉法進行了計算量上的對比分析。仿真實驗證實我們算法不僅擁有良好的布站效果且在計算量上相比窮舉法具有巨大優(yōu)勢。3.針對復雜的布站環(huán)境,研究了環(huán)境背景數(shù)據(jù)(包括高程數(shù)據(jù),城市未來規(guī)劃數(shù)據(jù)等)的獲取,并研究了基于環(huán)境背景數(shù)據(jù)的布站問題,最后利用仿真實驗驗證了該方法的實效性。4.針對監(jiān)視區(qū)域目標的活動規(guī)律,研究了基于雷達歷史回波數(shù)據(jù)的監(jiān)視區(qū)域目標熱度圖構建方法,在此基礎上,研究了基于目標熱度圖的布站算法,最后仿真實驗證實了基于目標熱度圖布站算法的有效性。以上方法的實效性均通過仿真實驗驗證,仿真結果表明,所研究方法能夠有效解決布站問題的實際需求,具有很大的實際意義。
[Abstract]:As a new type of radar, multiple input multiple output (MIMO) radar has advantages in overcoming radar cross sectional area (RCS) flicker and anti-jamming due to its good spatial diversity gain and multi-channel gain. Distributed MIMO radar has a wide range of antennas and its performance depends largely on the position of the radar antenna. If the radar stations are not optimized its performance will be limited. Distributed MIMO radar stations need to consider the location of multiple antennas at the same time, which is a complex high-dimensional problem. In view of the advantages of intelligent algorithms in solving this kind of problems, Therefore, the distributed MIMO radar station placement based on intelligent algorithm has become a hot research topic at home and abroad. Previous studies have not effectively considered the changing requirements of surveillance, and have not effectively used the big data information related to radar networks, so it is often difficult to meet the actual requirements of surveillance. In this paper, according to the actual demand of distributed MIMO radar stations, based on the solution of intelligent algorithm, the method based on the requirement of change monitoring and the method based on big data is studied, which is as follows: 1. To solve the problem of distributed MIMO radar station placement, a problem model with coverage rate as an optimization index is established. The monitoring area is discretized into several resolution units, if the detection probability of the unit reaches a certain threshold. The simplified expression. 2. 2 of the detection probability is derived on the basis of the assumption that the unit is covered. A dynamic deployment method of MIMO radar based on genetic algorithm is studied and compared with exhaustive method. The simulation results show that our algorithm not only has good station layout effect, but also has a great advantage over exhaustive method. In this paper, the acquisition of environmental background data (including elevation data, urban future planning data, etc.) and the problem of station layout based on environmental background data are studied. Finally, the effectiveness of the method is verified by simulation experiments. 4. In view of the activity rule of the target in the surveillance area, the method of constructing the heat map of the target based on the radar historical echo data is studied. On the basis of this, the algorithm of station placement based on the heat map of the target is studied. Finally, the simulation results show the effectiveness of the algorithm based on the thermal map of the target. The effectiveness of the above methods is verified by simulation experiments. The simulation results show that the proposed method can effectively solve the actual demand of the problem of station distribution and has great practical significance.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP18;TN958

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本文編號：2116444