Subpixel centroid estimation is the most important star image location method of star tracker. This paper presents a theoretical analysis of the systematic error of subpixel centroid estimation algorithm utilizing fre...Subpixel centroid estimation is the most important star image location method of star tracker. This paper presents a theoretical analysis of the systematic error of subpixel centroid estimation algorithm utilizing frequency domain analysis under the con-sideration of sampling frequency limitation and sampling window limitation. Explicit expression of systematic error of cen-troid estimation is obtained, and the dependence of systematic error on Gaussian width of star image, actual star centroid loca-tion and the number of sampling pixels is derived. A systematic error compensation algorithm for star centroid estimation is proposed based on the result of theoretical analysis. Simulation results show that after compensation, the residual systematic errors of 3-pixel-and 5-pixel-windows’ centroid estimation are less than 2×10-3 pixels and 2×10-4 pixels respectively.展开更多
Wireless Sensor Network(WSN)based applications has been extraordinarily helpful in monitoring interested area.Only information of surrounding environment with meaningful geometric information is useful.How to design t...Wireless Sensor Network(WSN)based applications has been extraordinarily helpful in monitoring interested area.Only information of surrounding environment with meaningful geometric information is useful.How to design the localization algorithm that can effectively extract unknown node position has been a challenge in WSN.Among all localization technologies,the Distance Vector-Hop(DV-Hop)algorithm has been most popular because it simply utilizes the hop counts as connectivity measurements.This paper proposes an improved DV-Hop based algorithm,a centroid DV-hop localization with selected anchors and inverse distance weighting schemes(SIC-DV-Hop).We adopt an inverse distance weighting method for average distance amelioration to improve accuracy.Also in this paper,we propose an inclusive checking rule to select proper anchors to avoid the inconsistency existing in centroid localization schemes.Finally,an improved multilateration centroid method is presented for the localization.Simulations are conducted on two different network topologies and experiments results show that compared with existing DV-Hop based algorithms,our algorithm can significantly improve the performance meanwhile cost less network resource.展开更多
文摘Subpixel centroid estimation is the most important star image location method of star tracker. This paper presents a theoretical analysis of the systematic error of subpixel centroid estimation algorithm utilizing frequency domain analysis under the con-sideration of sampling frequency limitation and sampling window limitation. Explicit expression of systematic error of cen-troid estimation is obtained, and the dependence of systematic error on Gaussian width of star image, actual star centroid loca-tion and the number of sampling pixels is derived. A systematic error compensation algorithm for star centroid estimation is proposed based on the result of theoretical analysis. Simulation results show that after compensation, the residual systematic errors of 3-pixel-and 5-pixel-windows’ centroid estimation are less than 2×10-3 pixels and 2×10-4 pixels respectively.
基金This research is supported by Research Foundation for Returned Scholars,Nanjing Tech University[No.39809110].The author JW received the grant in 2017.
文摘Wireless Sensor Network(WSN)based applications has been extraordinarily helpful in monitoring interested area.Only information of surrounding environment with meaningful geometric information is useful.How to design the localization algorithm that can effectively extract unknown node position has been a challenge in WSN.Among all localization technologies,the Distance Vector-Hop(DV-Hop)algorithm has been most popular because it simply utilizes the hop counts as connectivity measurements.This paper proposes an improved DV-Hop based algorithm,a centroid DV-hop localization with selected anchors and inverse distance weighting schemes(SIC-DV-Hop).We adopt an inverse distance weighting method for average distance amelioration to improve accuracy.Also in this paper,we propose an inclusive checking rule to select proper anchors to avoid the inconsistency existing in centroid localization schemes.Finally,an improved multilateration centroid method is presented for the localization.Simulations are conducted on two different network topologies and experiments results show that compared with existing DV-Hop based algorithms,our algorithm can significantly improve the performance meanwhile cost less network resource.
