分布式艦載雷達(dá)目標(biāo)跟蹤和數(shù)據(jù)融合仿真
發(fā)布時間:2018-10-19 10:03
【摘要】:本文重點研究了適用于DMS-SWR系統(tǒng)的數(shù)據(jù)融合算法,研究了目標(biāo)跟蹤算法、航跡關(guān)聯(lián)算法及航跡融合算法等關(guān)鍵算法在本課題背景中的應(yīng)用方案,并且研究了艦載雷達(dá)相對目標(biāo)運動所引起的對系統(tǒng)整體跟蹤精度的影響。 首先,針對地波雷達(dá)所存在的角度分辨率低、非線性度強和虛警率高等特點,提出了適用于艦載地波雷達(dá)多目標(biāo)跟蹤的算法——基于不敏卡爾曼濾波的聯(lián)合概率數(shù)據(jù)關(guān)聯(lián)(JPDA/UKF)算法。仿真結(jié)果表明,本文采用的JPDA/UKF算法整體的濾波性能均優(yōu)于基于擴展卡爾曼濾波的聯(lián)合概率數(shù)據(jù)關(guān)聯(lián)(JPDA/EKF)算法。 然后,針對DMS-SWR系統(tǒng)所需要的航跡關(guān)聯(lián)問題,本文提出了一種基于曲線擬合的航跡關(guān)聯(lián)算法,該算法不會出現(xiàn)漏關(guān)聯(lián)的情況,也無需多義性處理,原理簡單,易于實現(xiàn)。仿真結(jié)果表明,,在一定條件下,它能得到比傳統(tǒng)的加權(quán)法與序貫法更高的關(guān)聯(lián)正確率。 接著,對分布式系統(tǒng)常采用的簡單凸組合(SF)融合算法、協(xié)方差加權(quán)航跡(WCF)融合算法和無反饋最優(yōu)分布式航跡融合算法進行了理論研究與論證,并對三種算法進行了仿真分析,結(jié)果顯示,對于DMS-SWR系統(tǒng),這三種融合算法的性能雖略有差別,但差別不大;同時發(fā)現(xiàn)融合算法能有效提高系統(tǒng)的跟蹤精度。 最后,分別對含有2、3、4艘軍艦的DMS-SWR系統(tǒng)進行研究,得出隨著可融合軍艦數(shù)目的增多在一定程度上可以提高整個系統(tǒng)的跟蹤精度。對由相同精度雷達(dá)組成的DMS-SWR系統(tǒng)跟蹤精度的影響因素的研究發(fā)現(xiàn):艦船編隊離目標(biāo)的距離越遠(yuǎn),所得到的跟蹤精度越差;艦船編隊的運動對目標(biāo)的位置上的改善程度越好,所得到的的跟蹤精度越高。
[Abstract]:In this paper, the data fusion algorithm suitable for DMS-SWR system is studied, and the key algorithms, such as target tracking algorithm, track association algorithm and track fusion algorithm, are studied in this paper. The influence of the relative target motion of shipborne radar on the overall tracking accuracy of the system is also studied. First of all, aiming at the characteristics of low angle resolution, strong nonlinearity and high false alarm rate of ground wave radar, In this paper, an algorithm for multi-target tracking of shipborne ground wave radar is proposed, which is a joint probabilistic data association (JPDA/UKF) algorithm based on unsensitive Kalman filter. Simulation results show that the overall filtering performance of the proposed JPDA/UKF algorithm is better than that of the extended Kalman filter based joint probabilistic data association (JPDA/EKF) algorithm. Then, in order to solve the problem of track association in DMS-SWR system, this paper presents a curve fitting based track association algorithm. The algorithm does not have the case of missing association and does not need ambiguity processing. The principle is simple and easy to implement. The simulation results show that under certain conditions, it can get a higher accuracy than the traditional weighting method and sequential method. Then, the simple convex combination (SF) fusion algorithm, covariance weighted track (WCF) fusion algorithm and the optimal distributed track fusion algorithm without feedback are theoretically studied and proved, and the three algorithms are simulated and analyzed. The results show that for DMS-SWR systems, the performance of the three fusion algorithms is slightly different, but the difference is not significant, and it is found that the fusion algorithm can effectively improve the tracking accuracy of the system. Finally, the DMS-SWR system with 4 warships of 2 / 3 is studied, and it is concluded that the tracking accuracy of the whole system can be improved to a certain extent with the increase of the number of fusible warships. The research on the factors influencing the tracking accuracy of the DMS-SWR system composed of the same precision radar shows that the farther the ship formation is from the target, the worse the tracking accuracy is, and the better the ship formation motion improves the position of the target. The higher the tracking accuracy is.
【學(xué)位授予單位】:哈爾濱工業(yè)大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2014
【分類號】:TN953
[Abstract]:In this paper, the data fusion algorithm suitable for DMS-SWR system is studied, and the key algorithms, such as target tracking algorithm, track association algorithm and track fusion algorithm, are studied in this paper. The influence of the relative target motion of shipborne radar on the overall tracking accuracy of the system is also studied. First of all, aiming at the characteristics of low angle resolution, strong nonlinearity and high false alarm rate of ground wave radar, In this paper, an algorithm for multi-target tracking of shipborne ground wave radar is proposed, which is a joint probabilistic data association (JPDA/UKF) algorithm based on unsensitive Kalman filter. Simulation results show that the overall filtering performance of the proposed JPDA/UKF algorithm is better than that of the extended Kalman filter based joint probabilistic data association (JPDA/EKF) algorithm. Then, in order to solve the problem of track association in DMS-SWR system, this paper presents a curve fitting based track association algorithm. The algorithm does not have the case of missing association and does not need ambiguity processing. The principle is simple and easy to implement. The simulation results show that under certain conditions, it can get a higher accuracy than the traditional weighting method and sequential method. Then, the simple convex combination (SF) fusion algorithm, covariance weighted track (WCF) fusion algorithm and the optimal distributed track fusion algorithm without feedback are theoretically studied and proved, and the three algorithms are simulated and analyzed. The results show that for DMS-SWR systems, the performance of the three fusion algorithms is slightly different, but the difference is not significant, and it is found that the fusion algorithm can effectively improve the tracking accuracy of the system. Finally, the DMS-SWR system with 4 warships of 2 / 3 is studied, and it is concluded that the tracking accuracy of the whole system can be improved to a certain extent with the increase of the number of fusible warships. The research on the factors influencing the tracking accuracy of the DMS-SWR system composed of the same precision radar shows that the farther the ship formation is from the target, the worse the tracking accuracy is, and the better the ship formation motion improves the position of the target. The higher the tracking accuracy is.
【學(xué)位授予單位】:哈爾濱工業(yè)大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2014
【分類號】:TN953
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