# An Observation Scheduling System for Radio Telescope Array
## 5 Discussion and Conclusions  
This paper discusses the observational requirements for the 4 \(\times\) 4.5 m radio telescope array at Guizhou Normal University and outlines the development of an observation scheduling system. The code of this system software is publicly available on Github ([[https://github.com/MC-git37/astronomical-observation](https://github.com/MC-git37/astronomical-observation)]([https://github.com/MC-git37/astronomical-observation](https://github.com/MC-git37/astronomical-observation)), accessed on 11 October 2024). Designed for any antenna array and any geographical location, the system is built using Python and Qt Designer and offers the following capabilities: predicting the azimuth and elevation changes in target sources over the upcoming 24 h based on the current antenna position, with visualization; scheduling and processing target source collections; visualizing calibration sources across all sky regions; and _uv_ mapping for any antenna array. The system is compatible with both Windows and Linux operating systems and  
Figure 16: _uv_ coverage ratio distribution of the three array configurations. Figure 15: _uv_ coverage maps of the Y-shaped array for observation durations of 1, 2, 4, 8, 12, and 24 h.  
boasts a user-friendly, intuitive interface, along with strong versatility, portability, and expandability. Since its deployment in June 2022 for daily observations of the 4 \(\times\) 4.5 m array at Guizhou Normal University, by combining this system and the telescope control system to predict the trajectory of pulsars, two typical pulsars have been successfully detected: PSR B0329+54 (J0332+5434) and PSR B0833-45 (J0835-4510), as shown in Figure 17 and Figure 18, respectively. Note that since there is no calibration in our system, we use the pdv package in PSRCHIVE [28] to give the relative flux density, which is the \"intensity\" axis shown in the tow figures. Looking ahead, the system will be integrated with upgraded arrays or other arrays to identify and address any deficiencies and areas for improvement. Currently, the system may face challenges in scheduling when observation periods have extremely low or high \(\theta_{\rm el}\) values, requiring manual insertion of calibrators post-scheduling. Future development will focus on optimizing \(\theta_{\rm el}\) value selection to enhance the efficiency of target observations and automating the insertion of calibrators after scheduling. Figure 17: PSR B0329+54 integral profile, and the upper part is the spectrum of integral profile; The lower part is the integrated profile within 7000 s.  
**Author Contributions:** Conceptualization, R.Z. and B.L. ; methodology, H.L. ; software, Z.Y. and C.M. ; validation, W.X., H.L. and R.Z. ; formal analysis, R.Z. ; investigation, W.X. ; resources, B.L. ; data curation, C.M. ; writing--original draft preparation, R.Z. and C.M. ; writing--review and editing, B.L. and C.M. ; visualization, W.X. ; supervision, R.Z. ; project administration, B.L. ; funding acquisition, R.Z. and Z.Y. All authors have read and agreed to the published version of the manuscript. **Funding:** We gratefully acknowledge the financial support received from various funding sources for this work. This includes the National SKA Program of China (Grants Nos. 2022 SKA0130100, 2022 SKA0130104), the National Natural Science Foundation of China (Grants No. 12103013), the Foundation of Science and Technology of Guizhou Province (Grants No. (ZK(2021)023)), the Foundation of Guizhou Provincial Education Department (Grants No. (KY(2020)003, KY(2023)059), the Guizhou Province Science and Technology Support Program (General Project) (No. Qianhe Support [2023] General 333), Liupanshui Science and Technology Development Project (No. 52020-2024-PT-01).