| Synthetic Aperture Radar(SAR) is a kind of all-weather and all-time remote sensing tools, through which high resolution image can be obtained. SAR has a capability of obtaining high resolution that no ordinary radar can be comparable with, therefore, it is one of the significant directions for the modern radar development. At the same time, the microwave with long wavelength is able to penetrate foliage and the earth's surface, which is unsurpassable by other remote sensing ways, such as visible light and infrared ray. SAR has been applied widely to many fields of civil economy and national defense, such as terrain mapping, waterlog surveillance, ocean pollution surveillance, forest and crop investigation, military reconnaissance, etc.As the development of Synthetic Aperture Radar(SAR), the amount of the raw data of SAR is so large that it is difficult to be downlink and stored. So, it is one of good ideal to compress the raw data . This paper is aimed at study on the compression arithmetic of the SAR raw data.For background purpose, the statiscal property of the received electromagnetic waves were introduced, and elaborates the role and signification of SAR raw data compression. Several common compression arithmetic of SAR raw data were introduced and a systematic evaluation environment of SAR raw data was presented in this paper. We also suggested a number of additional metrics.The dissertation analyzes the Block adaptive Quantization (BAQ) algorithrn that is simple,real-time and fast. This paper utilizes emulational data and actual SAR raw data to evaluate BAQ algorithrn on different data separation scheme and compression ratio respectively. Numerical experiments show different data separation scheme have a little influence to evaluation parameters in appropriate scheme and BAQ algorithrn could have achieved better compression performance.The last part of thesis sums up the whole work and puts forward the assumption and expectation of the study about BAQ compression algorithm. |
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