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Lighthouses still play a significant role at present, as they are highly relied on by seafarers when ships depart, return, and navigate nearshore. The traditional method of unmanned aerial vehicle navigation is affected by multipath and dynamic environment interference, resulting in navigation errors. To accurately confirm the working range of lighthouses, a distance measurement technology for aerial robot lighthouses based on trajectory reconstruction and Bayesian inference is proposed. Design inertial trajectory reconstruction technology based on strapdown inertial navigation system to achieve inertial navigation in aerial robot lighthouse distance measurement, and achieve more accurate lighthouse distance measurement. The aerial robot used is the Qianxunyi Q10 composite wing unmanned aerial vehicle flight platform, which performs inertial navigation and collects lighthouse light distance measurement data. Design a multi clue visual attention model based on Bayesian inference to obtain significant maps of lighthouse distance mapping. Build an aerial camera imaging model for lighthouse distance mapping based on the visual attention saliency map, and calculate the lighthouse lighting illumination distance. The test results show that in 12 tests, the average navigation error of the drone is only 0.132mm, and the average lighthouse light distance measurement time is relatively short. After multiple tests, the average lighthouse light distance measurement error is only 27.41cm, indicating a small overall measurement error.