Abstract: An object tracking method, device, backend, and medium. The object tracking method includes: obtaining raw sensor data sent by a sensor array, the sensor array including a plurality of magnetic field sensors, the raw sensor data including magnetic field strengths at locations of the magnetic field sensors; determining the presence of a target magnet based on the raw sensor data, where the target magnet is a permanent magnet provided on a target object; when the target magnet is present, tracking the target magnet based on the raw sensor data. The method enables permanent-magnet-based object tracking.

Abstract: A spatial autocorrelation machine learning-based downscaling method of satellite precipitation data includes obtaining the TRMM precipitation data and the land surface parameters; preprocessing the land surface parameters to obtain DEM, day land surface temperature, night surface land temperature, day-and-night land surface temperature difference and NDVI with spatial resolutions of 1 km and 25 km; performing a spatial autocorrelation analysis of the TRMM precipitation data to obtain an estimated spatial autocorrelation value of the precipitation data with a spatial resolution of 25 km; downscaling the spatial resolution of the spatial autocorrelation value of the precipitation data from 25 km to 1 km; establishing a nonlinear regression model; obtaining a precipitation downscaling data with a spatial resolution of 1 km based on the nonlinear regression model. A system and a terminal are also provided.

Abstract: A spatial autocorrelation machine learning-based downscaling method of satellite precipitation data includes obtaining the TRMM precipitation data and the land surface parameters; preprocessing the land surface parameters to obtain DEM, day land surface temperature, night surface land temperature, day-and-night land surface temperature difference and NDVI with spatial resolutions of 1 km (0.621 miles) and 25 km (15.534 miles); performing a spatial autocorrelation analysis of the TRMM precipitation data to obtain an estimated spatial autocorrelation value of the precipitation data with a spatial resolution of 25 km (15.534 miles); downscaling the spatial resolution of the spatial autocorrelation value of the precipitation data from 25 km (15.534 miles) to 1 km (0.621 miles); establishing a nonlinear regression model; obtaining a precipitation downscaling data with a spatial resolution of 1 km (0.621 miles) based on the nonlinear regression model. A system and a terminal are also provided.