本文選題：空中交通管制 + 低空救援　； 參考：《西南交通大學(xué)學(xué)報》2016年06期

【摘要】：針對低空救援航跡易受到側(cè)風(fēng)影響難以獲得準(zhǔn)確的航跡規(guī)劃路徑問題,采用數(shù)據(jù)融合方法預(yù)測低空風(fēng),修正航空器的低空規(guī)劃航跡.首先,將飛行區(qū)域內(nèi)的國際交換站作為觀測點,通過應(yīng)用基于無跡卡爾曼濾波(UKF)的數(shù)值氣象預(yù)報釋用技術(shù),將觀測點的風(fēng)速、風(fēng)向記錄數(shù)據(jù)與預(yù)報值進(jìn)行融合,建立低空風(fēng)預(yù)測模型;其次,利用該模型,校正預(yù)報數(shù)據(jù)的系統(tǒng)誤差,得出修正的風(fēng)預(yù)測值;最后,結(jié)合航空器的爬升率、巡航速度等性能參數(shù)與所經(jīng)航路點的風(fēng)速、風(fēng)向信息,依據(jù)速度矢量合成原理,修正各航路點的過點時刻.仿真實驗表明,與傳統(tǒng)的卡爾曼濾波預(yù)測方法相比,由UKF方法預(yù)測得到的風(fēng)速、風(fēng)向RM_SE分別減少了12.88%與17.50%,對初始規(guī)劃航跡的修正更為精確.
[Abstract]:Aiming at the problem that the low altitude rescue track is easy to be affected by crosswind and it is difficult to obtain accurate track planning path, the method of data fusion is used to predict the low altitude wind and to correct the low altitude planning track of aircraft. First of all, the international exchange station in the flight area is used as the observation point. By applying the numerical weather forecast interpretation technology based on the unscented Kalman filter (UKF), the wind speed, wind direction record data of the observation point and the forecast value are fused. A low-altitude wind prediction model is established. Secondly, the system error of the forecast data is corrected by the model, and the modified wind prediction value is obtained. Finally, combining the performance parameters of the aircraft, such as climbing rate, cruise speed, and the wind speed of the passage point, According to the principle of velocity vector synthesis, wind direction information is used to correct the crossing time of each route point. The simulation results show that compared with the traditional Kalman filtering method, the wind speed and wind direction RM_SE predicted by the UKF method are reduced by 12.88% and 17.50%, respectively, and the correction of the initial planned track is more accurate.
【作者單位】： 南京航空航天大學(xué)民航學(xué)院;
【基金】：國家自然科學(xué)基金資助項目(U1233101,71271113,U1633119) 中央高�；究蒲袠I(yè)務(wù)費(fèi)專項基金資助項目(NS2016062)
【分類號】：V355
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本文編號：1782129