本文關鍵詞：高頻地波雷達與AIS船只目標航跡關聯(lián)方法研究　出處：《內蒙古大學》2014年碩士論文　論文類型：學位論文

  更多相關文章： 高頻地波雷達 AIS 航跡關聯(lián) 航跡修正

【摘要】：在眾多海上監(jiān)視手段中,高頻地波雷達能夠對監(jiān)視區(qū)域內的合作與非合作目標進行超視距探測和跟蹤,但其不能提供目標的身份信息；艦船自動識別系統(tǒng)(Automatic Identification System, AIS)能提供監(jiān)視區(qū)域內合作目標的信息,為目標的類型和身份識別提供了便利,但AIS不能提供非合作目標的信息。二者各有優(yōu)缺點,提供的信息具有互補性,將二者得到的船只目標探測結果進行航跡關聯(lián),一方面可以解決監(jiān)視區(qū)間中的重復跟蹤問題,提高跟蹤效率,另一方面可以通過排除關聯(lián)的合作目標重點關注沒有身份信息的疑似非合作船只。 本文通過地波雷達與AIS船只目標航跡關聯(lián)分析；發(fā)展適用于地波雷達與AIS的船只目標航跡關聯(lián)算法,實現(xiàn)合作目標和非合作目標的跟蹤探測。論文主要在以下幾個方面做了研究工作： 1.在數(shù)據(jù)預處理方面,分析了地波雷達與AIS點跡與航跡數(shù)據(jù)的特點,并針對二者在時空上的非統(tǒng)一性開展了兩種手段航跡的數(shù)據(jù)預處理。通過基于球體模型的坐標變換和徑向投影變換,實現(xiàn)了坐標統(tǒng)一。采用分段線性插值和外推法對AIS航跡進行時間插值,實現(xiàn)了與地波雷達的時間對準。 2.在航跡關聯(lián)算法方面,提出了基于均值最近鄰的地波雷達與AIS船只目標航跡關聯(lián)方法,并對門限參數(shù)的選取做了分析。該方法采用徑向速度、距離和方向的三維特征信息,用一段時間內的均值最近鄰判據(jù)進行航跡關聯(lián)判定,該航跡關聯(lián)方法比傳統(tǒng)的最近鄰法能夠減小誤判率。 針對航跡較多的復雜情況,提出了模糊雙門限航跡關聯(lián)方法,并對該方法中參數(shù)的選取做了分析。將模糊雙門限方法與均值最近鄰法做了比較,在航跡較復雜或有奇異值的情況下,模糊雙門限的方法具有較強的魯棒性。 基于對航跡關聯(lián)結果的誤差統(tǒng)計,提出了地波雷達航跡修正方法,提高了地波雷達對非合作船只的跟蹤精度。 3.最后,在MATLAB環(huán)境下構建了地波雷達與AIS航跡關聯(lián)軟件系統(tǒng)；系統(tǒng)集成了均值最近鄰和模糊雙門限兩種航跡關聯(lián)算法和航跡修正方法,能夠實現(xiàn)航跡關聯(lián)和修正,可以突出顯示非合作目標的原始及修正航跡。
[Abstract]:Among many marine surveillance methods, HF ground wave radar can detect and track the cooperative and non-cooperative targets in the surveillance area, but it can not provide the identification information of the target. Automatic Identification system (AIS) can provide information about cooperative targets in the monitoring area. It is convenient for the type and identification of the target, but AIS can not provide the information of the non-cooperative target. They have their own advantages and disadvantages, and the information provided is complementary. On the one hand, it can solve the problem of repeated tracking in the monitoring area and improve the tracking efficiency by correlating the ship target detection results obtained by the two methods. On the other hand, we can focus on the suspected non-cooperative ships without identity information by excluding the associated cooperation targets. In this paper, the correlation analysis between ground wave radar and AIS ship target track is carried out. The tracking and detection of cooperative and non-cooperative targets are realized by developing a ship target track association algorithm suitable for ground wave radar and AIS. In this paper, the following research work has been done: 1. In the aspect of data preprocessing, the characteristics of ground wave radar and AIS point track and track data are analyzed. In view of the non-unity of the two methods, the data preprocessing of track is carried out by means of coordinate transformation and radial projection transformation based on sphere model. The method of piecewise linear interpolation and extrapolation is used to interpolate the track of AIS, and the time alignment with ground wave radar is realized. 2. In the aspect of track correlation algorithm, a method of track correlation between ground wave radar and AIS ship target based on mean nearest neighbor is proposed, and the selection of threshold parameters is analyzed. The radial velocity is used in this method. The distance and direction 3D feature information is determined by the mean nearest neighbor criterion in a period of time. The track correlation method can reduce the misjudgment rate compared with the traditional nearest neighbor method. In view of the complex situation of more track, a fuzzy double threshold track correlation method is proposed, and the selection of parameters in the method is analyzed. The fuzzy double threshold method is compared with the mean nearest neighbor method. In the case of complex tracks or singular values, the fuzzy two-threshold method is robust. Based on the error statistics of track correlation results, the track correction method of ground wave radar is proposed, which improves the tracking accuracy of surface wave radar to non-cooperative ships. 3. Finally, the software system of track correlation between ground wave radar and AIS is constructed in MATLAB environment. The system integrates mean nearest neighbor and fuzzy double threshold algorithms and track correction methods, which can realize track correlation and correction, and can highlight the original and modified track of non-cooperative targets.
【學位授予單位】：內蒙古大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN957.52

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