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The electromagnetic (EM) target situation map can visualize the situation and locations of multiple EM targets in the three-dimensional (3D) space. It is vital for the spectrum activity monitoring, radiation source localization, frequency resource management, and so on. Traditional studies focused on the radio environment map construction, and the characteristics such as locations of EM targets are not accurate due to reconstruction deviation and environmental noise. This paper presents a 3D EM target situation map construction scheme based on multiple unmanned aerial vehicle collaboration. Firstly, an improved maximum and minimum distance clustering-based algorithm is proposed to estimate the number and rough location of EM targets directly by utilizing the original sparse sampling data. Then, to improve the accuracy of situational awareness, a re-weighted map fusion algorithm is used to update the raw EM characteristics results. Finally, we calculate the self-information of different targets and optimize the previous location results. Compared with other conventional methods, numerical results demonstrate that the proposed method has higher mapping accuracy under the same low sampling rate.
Peng et al. (Fri,) studied this question.