TY - GEN
T1 - A Multi-UAVs Cooperative Spectrum Sensing Method Based on Improved IDW Algorithm
AU - Shi, Jie
AU - Chong, Jingzheng
AU - Huang, Zejiang
AU - Yang, Zhihua
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - With the development of spatial information networks, the perceptual allocation of spectrum resources has become a research hotspot. To solve the problems of low accuracy and efficiency in traditional single uav spectrum sensing, a multi-UAVs collaborative spectrum sensing method based on improved IDW algorithm is proposed in this paper. Firstly, a spectrum sensing model for collaborative exploration of multiple UAVs was constructed; Secondly, a spectral intensity cost factor is added to the cost function of UAV path planning, enabling UAVs to explore electromagnetic environment more efficiently; Finally, the accuracy of spectrum data completion is improved by combining IDW algorithm with propagation model. The simulation results show that the task completion time is reduced compared to current advanced path planning methods, and the accuracy of the completion algorithm is nearly 10dB higher than that of IDW and tensor completion methods, which has high practical value.
AB - With the development of spatial information networks, the perceptual allocation of spectrum resources has become a research hotspot. To solve the problems of low accuracy and efficiency in traditional single uav spectrum sensing, a multi-UAVs collaborative spectrum sensing method based on improved IDW algorithm is proposed in this paper. Firstly, a spectrum sensing model for collaborative exploration of multiple UAVs was constructed; Secondly, a spectral intensity cost factor is added to the cost function of UAV path planning, enabling UAVs to explore electromagnetic environment more efficiently; Finally, the accuracy of spectrum data completion is improved by combining IDW algorithm with propagation model. The simulation results show that the task completion time is reduced compared to current advanced path planning methods, and the accuracy of the completion algorithm is nearly 10dB higher than that of IDW and tensor completion methods, which has high practical value.
KW - Inverse Distance Weighting Method
KW - Path Planning
KW - Spectrum Sensing
KW - Unmanned Aerial Vehicle
UR - https://www.scopus.com/pages/publications/85190639437
U2 - 10.1007/978-981-97-1568-8_13
DO - 10.1007/978-981-97-1568-8_13
M3 - 会议稿件
AN - SCOPUS:85190639437
SN - 9789819715671
T3 - Communications in Computer and Information Science
SP - 150
EP - 163
BT - Space Information Networks - 7th International Conference, SINC 2023, Revised Selected Papers
A2 - Yu, Quan
PB - Springer Science and Business Media Deutschland GmbH
T2 - 7th International Conference on Space Information Network, SINC 2023
Y2 - 12 October 2023 through 13 October 2023
ER -