Investigation on the Mechanism and Positioning Error of Multi-Star Spots Extraction of Iteratively Weighted Center of Gravity algorithm

Jun, 张军 Zhang; Yuncai, 郝云彩 Hao; Da, 刘达 Liu

doi:10.3788/aos201535.0204001

“…In those tests, 1000 randomly star spots were generated with Monte Carlo method in any single test to study the positioning accuracy of multi-stars in star tracker under different R and velocity [14] . The signal to noise ratio R is defined as ( ) …”

Section: Simulations and Discussionmentioning

confidence: 99%

“…The absolute positioning error for a single star spot can be error is defined as root mean square for N star spots[14] .The parameters and values of star spot extraction in Monte Carlo simulation have been summarized in table 1.…”

mentioning

confidence: 99%

Generalized dynamic motion compensation technology for star tracker on rotating spacecraft with acceleration

Zhang¹,

Hao²,

Wang³

et al. 2015

SPIE Proceedings

0

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The influence of acceleration resulting from spacecraft maneuvering on star spot positioning and hereafter dynamic motion compensation technology are addressed. Firstly the pattern of the smeared star-spot image under maneuvering condition and the locating error are investigated. It is found that instead of following a symmetrical shaped pattern, the smeared star spot under acceleration is twisted. Simulation verifies that the position error is far beyond Cramer Rao Lower Bound(CRLB) of photoelectric devices under uniform velocity. Then a novel scheme to derive the more general accurate motion compensation is proposed. In this case, an approximate CRLB is derived to give a baseline to measure the performance of any positioning algorithm and motion compensation technique on star tracker. The theory and corresponding simulations show the novel general compensation approach is better than the conventional compensation strategy and close to the approximate CRLB. Therefore, a CRLB position accuracy of star spot is expected to be realized by using the generalized dynamic compensation method on maneuvering spacecraft.

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“…Distance-independent positioning methods do not require distance or angle information between nodes, but instead use network connectivity and other information to achieve positioning. Common algorithms include Approximate Point-In-Triangulation (APIT) 18 – 20 , Centroid Method 21 , Distance Vector Hop (DV-Hop) 22 – 24 , and others.…”

Section: Introductionmentioning

confidence: 99%

Research on WSN reliable ranging and positioning algorithm for forest environment

Wu,

Yu,

Yi

et al. 2024

Sci Rep

0

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Wireless sensor network (WSN) location is a significant research area. In complex environments like forests, inaccurate signal intensity ranging is a major challenge. To address this issue, this paper presents a reliable WSN distance measurement-positioning algorithm for forest environments. The algorithm divides the positioning area into several sub-regions based on the discrete coefficient of the collected signal strength. Then, using the fitting method based on the signal intensity value of each sub-region, the algorithm derives the reference points of the logarithmic distance path loss model and path loss index. Finally, the algorithm locates target nodes using anchor nodes in different regions. Additionally, to enhance the positioning accuracy, weight values are assigned to the positioning result based on the discrete coefficient of the signal intensity in each sub-region. Experimental results demonstrate that the proposed WSN algorithm has high precision in forest environments.

show abstract

“…Distance-independent positioning methods do not require distance or angle information between nodes, but instead use network connectivity and other information to achieve positioning. Common algorithms include Approximate Point-In-Triangulation (APIT) [18][19][20], Centroid Method [21], Distance Vector Hop (DV-Hop) [22][23][24], and others.…”

Section: Introductionmentioning

confidence: 99%

Research on WSN Reliable Ranging and Positioning Algorithm for Forest Environment

Wu,

Yu,

Yi

et al. 2023

Preprint

0

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Wireless sensor network (WSN) location is a significant research area. In complex environments like forests, inaccurate signal intensity ranging is a major challenge. To address this issue, this paper presents a reliable WSN distance measurement-positioning algorithm for forest environments. The algorithm divides the positioning area into several sub-regions based on the discrete coefficient of the collected signal strength. Then, using the fitting method based on the signal intensity value of each sub-region, the algorithm derives the reference points of the logarithmic distance path loss model and path loss index. Finally, the algorithm locates target nodes using anchor nodes in different regions. Additionally, to enhance the positioning accuracy, weight values are assigned to the positioning result based on the discrete coefficient of the signal intensity in each sub-region. Experimental results demonstrate that the proposed WSN algorithm has high precision in forest environments.

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Investigation on the Mechanism and Positioning Error of Multi-Star Spots Extraction of Iteratively Weighted Center of Gravity algorithm

Cited by 4 publications

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Generalized dynamic motion compensation technology for star tracker on rotating spacecraft with acceleration

Generalized dynamic motion compensation technology for star tracker on rotating spacecraft with acceleration

Research on WSN reliable ranging and positioning algorithm for forest environment

Research on WSN Reliable Ranging and Positioning Algorithm for Forest Environment

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