# On-Board Decentralized Observation Planning for LEO Satellite Constellations
## 3 Improved CBBA
### Bundle Construction
To validate the effectiveness of the proposed algorithm, we carry out experiments on series instances with different targets and constellations. From the experimental results, we can see that, the communication number increases with the number of satellites and the number of tasks, but it is not simply linear or exponential. ICBBA greatly saves the communication cost compared with CNP. The optimization performance of ICBBA can be controlled by designing the DMG calculation function. Using DMG(P/S) on global targets and DMG(P-L) on regional targets can lead to a better solution. The number of repeated claims decreases with the number of iterations in the whole constellation, which proves that the consensus check phase plays an important role in the convergence of ICBBA. In addition, ICBBA can effectively handle dynamically arrived tasks and rapidly achieve re-convergence. Conceptualization, B.S. and Q.Y. ; methodology, B.S. and Q.Y. ; software, B.S. ; validation, Y.Z. and S.X. ; data curation, Y.Z. and S.X. ; writing--original draft preparation, B.S. and Q.Y. ; writing--review and editing, Y.C. ([PERSON]) and Y.C. ([PERSON]); visualization, Y.Z. and S.X. ; supervision, Y.C. ([PERSON]) and Y.C. ([PERSON]); project administration, Y.C. ([PERSON]) and Y.C. ([PERSON]); funding acquisition, Y.C. ([PERSON]) and Y.C. ([PERSON]) All authors have read and agreed to the published version of the manuscript. This work was supported by the National Natural Science Foundation of China (Grant numbers: 72001212, 72201272, 71901213). The instances for MSOOP used in this paper can be downloaded at [[https://github.com/haohaoaxueifalunwen/ICBBA](https://github.com/haohaoaxueifalunwen/ICBBA)]([https://github.com/haohaoaxueifalunwen/ICBBA](https://github.com/haohaoaxueifalunwen/ICBBA)) (accessed on 3 January 2023). The authors declare no conflict of interest. ## References

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