This paper proposes a design method for a channel-type sheep dynamic weighing system to address the current problems encountered by pastoralists at home and abroad, such as time-consuming sheep weighing, difficulties with data collection, and management of the stress response in sheep. The complete system includes a hardware structure, dynamic characteristics, and a Kalman-aggregate empirical modal decomposition algorithm (Kalman-EEMD algorithm) model for dynamic data processing. The noise suppression effects of the Kalman filter, the empirical modal decomposition (EMD), and the ensemble empirical modal decomposition (EEMD) algorithms are discussed for practical applications. Field tests showed that the Kalman-EEMD algorithm model has the advantages of high accuracy, efficiency, and reliability. The maximum error between the actual weight of the goats and the measured value in the experiments was 1.0%, with an average error as low as 0.40% and a maximum pass time of 2 s for a single goat. This meets the needs for weighing accuracy and goat flock weighing rates.