Current intelligent feeding boats face low efficiency and insufficient positioning accuracy when transferring between multiple ponds. Therefore， a split-type pond-transfer structural design scheme and a fusion positioning algorithm are proposed. This system uses a modular combination of a catamaran and an intelligent feeding vehicle， together with a pond-transfer ramp and docking limit devices. By optimizing the mechanical structure to design a power switching device， the rapid combination and separation of the boat body and feeding vehicle are achieved. An adaptive strong tracking Kalman filter fusion positioning algorithm based on UWB and IMU is proposed to improve positioning accuracy and robustness in complex water environments. The algorithm is simulated and compared using MATLAB， and pond-transfer ramp experiments verify the passability and operational efficiency under different slopes and load conditions. Pond-transfer ramp tests show that the feeding vehicle transfer time is under 25 seconds under various slopes and loads， much shorter than manual transfer time， and operations are smooth. Simulation results of the positioning algorithm indicate that compared to single UWB positioning， the ASTKF algorithm reduces mean square error by 98.9% and maximum error by 70.6%. The ASTKF algorithm has strong real-time response and recovery capabilities against dynamic interference. During actual boat positioning tests， the root mean square error is 5.41 cm， 27.3% lower than the AEKF algorithm. The split-type pond-transfer scheme and the proposed fusion positioning algorithm effectively solve the problems of low transfer efficiency and poor positioning accuracy in traditional feeding boats. This study enhances the level of intelligent operations and economic efficiency in complex water areas， providing reliable technical support and application demonstration for aquaculture automation.