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In response to the demand for refined management of electromagnetic (EM) space, a reweighting fusion-based EM target situation mapping method with multiple Unmanned Aerial Vehicles (UAVs) is proposed. An improved reweighting fusion algorithm is first presented to complete and fuse the data collected by collaborative UAVs, which effectively solves the reduction of mapping accuracy caused by single-device deviations and environmental noise. Then, an EM target positioning algorithm is designed based on the fused results. Finally, an EM target situation map, which includes both the positions and power information of EM targets, is constructed. Multiple experiments have shown that the ultimate map facilitates high-precision visualization of both the EM targets and the corresponding situational information. When the sampling rate (per UAV) is set to 10%, the normalized root mean square error of EM target sensing is only 0.034.
Peng et al. (Mon,) studied this question.