Unmanned aerial vehicle target detection method based on Bayesian multi-source fusion

The invention discloses an unmanned aerial vehicle target detection method based on Bayesian multi-source fusion, and the method comprises the following steps: S1, carrying out the target detection of an optical image of a detection region, and obtaining a first vectorization result; S2, performing target detection on the communication signal of the detection area, and obtaining a second vectorization result; S3, enabling the first vectorization result and the second vectorization result to serve as input of a Bayesian function respectively, performing multi-source fusion, and completing unmanned aerial vehicle target detection. Aiming at the problem of high false alarm probability and missing detection probability of single signal source detection, the invention provides a parallel distributed multi-source fusion strategy for unmanned aerial vehicle detection, an optical image and an unmanned aerial vehicle communication signal are used as two signal sources, the two signal sources are independently decided