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Wireless sensor networks (WSN) usually have limited energy and transmission capacity, which can't match the transmission of a large number of data collected by sensor nodes. So, it is necessary to perform in-network data compression in the WSN. This paper proposes an algorithm of data compression based on multiple principal component analysis (multiple-PCA), iteratively using PCA method in multiple layers. Theoretically and experimentally, the proposed algorithm can efficiently remove the correlation between the raw sensor measurements and also that between the principal components (PC) of the neighboring cluster heads, and efficiently improve the data compression ratio under the premise of ensuring the data reconstruction accuracy, thus better reduce the energy consumption of sensor nodes.