本文選題：目標(biāo)跟蹤 + 卡爾曼濾波　； 參考：《電光與控制》2017年10期

【摘要】：目標(biāo)運(yùn)動狀態(tài)的突變會導(dǎo)致跟蹤算法精度大幅降低。為了提高對目標(biāo)機(jī)動階段的跟蹤性能,提出了一種帶機(jī)動檢測的權(quán)值約束多新息修正算法。首先,為了準(zhǔn)確判斷機(jī)動時機(jī),提出了一種雙誤差橢圓的機(jī)動檢測算法,通過設(shè)置雙邊門限,加強(qiáng)算法對機(jī)動的敏感度;然后,為了降低因延遲修正造成的機(jī)動誤差,以預(yù)測量測與真實(shí)量測間的歐氏距離為基礎(chǔ),建立距離與權(quán)值間的映射關(guān)系,從而獲得之前修正信息的權(quán)值以加大對之前隱含信息的利用率;最后,通過3種場景下的仿真分析說明所提算法的有效性,并經(jīng)過與標(biāo)準(zhǔn)卡爾曼濾波及自適應(yīng)漸消卡爾曼濾波的對比,證明所提算法在跟蹤強(qiáng)機(jī)動目標(biāo)及弱機(jī)動目標(biāo)情況下均具有較高的費(fèi)效比。
[Abstract]:The sudden change of the moving state of the target will result in a significant decrease in the accuracy of the tracking algorithm. In order to improve the tracking performance of target maneuvering phase, a weighted constrained multi-innovation correction algorithm with maneuvering detection is proposed. First of all, in order to judge the timing of maneuver accurately, a dual-error ellipse maneuver detection algorithm is proposed. The sensitivity of the algorithm to maneuvering is enhanced by setting bilateral threshold, and then, in order to reduce the maneuvering error caused by delay correction, Based on the Euclidean distance between the predicted and real measurements, the mapping relationship between distance and weights is established to obtain the weights of the previously modified information in order to increase the utilization rate of the previously implied information. The effectiveness of the proposed algorithm is demonstrated by simulation analysis in three scenarios, and compared with standard Kalman filter and adaptive fading Kalman filter. It is proved that the proposed algorithm has a high cost effectiveness ratio in tracking strong maneuvering targets and weak maneuvering targets.
【作者單位】： 中國民用航空飛行學(xué)院;
【基金】：中國民用航空飛行學(xué)院面上項(xiàng)目(J2016-68) 中國民用航空局科研項(xiàng)目(MHRD20150228) 國家自然科學(xué)基金民航聯(lián)合研究項(xiàng)目(U1433126)
【分類號】：E91;TN713

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本文編號：1827549