Research on Data Compression Technology of Satellite-Based Electromagnetic Spectrum Monitoring System

At present, the satellite-based electromagnetic spectrum (EMS) monitoring system has been developed to a certain extent, and there are already some corresponding applications in global radio information monitoring, signal source positioning, surveillance of maritime traffic, etc. This is accompanied by a large amount of growth in monitoring data. However, the satellite platform load is limited, on which we cannot storage or process massive amount of data. So, it is particularly important for us to develop a new monitoring data compression technique. In this paper, we comprehensively use the method of comparative analysis and the method of computer modeling, distinguish between lossy and lossless compression algorithms, and select three widely used compression algorithms, namely, Huffman, LZW, and DCT transform-based compression algorithms for comparison. The experimental results show that the DCT transform-based compression algorithm is significantly better than the other two in terms of compression rate and compression/decompression time, however with distortions in the data. Between two lossless algorithms, the LZW algorithm is better than the Huffman algorithm. This shows that the satellite-based EMS monitoring data is highly compressible. Focusing on the cyclical changes of satellite-based EMS data, new compression algorithm should be developed based on lossy compression, under the premise of retaining the data integrity as much as possible.