Study on ENVISAT ASAR Image Geolocation Method
ENVISAT ASAR影像地理定位方法

As the ASAR sensor has successfully passed the primary validation period, more and more users in China will be able to get ASAR data in the near future. If users apply the data to practical mapping, the first key problem which should be solved is to geolocate the SAR image. Based on Range-Doppler(RD) model, a geolocation method has been developed for the major imaging products of ENVISAT Advanced SAR (ASAR). As one special contribution of this paper, the way to construct range equations for different ASAR products has been solved successfully. The range function of slant range image products is just a linear equation in one order, which can be defined by the first range distance and the range pixel spacing. For precision ground range products, the one and only SRGR record provided by the metadata can be used directly to construct the range equation. But for median resolution ground range products, several SRGR records have been provided by the metadata, the range function should be established through interpolation method according to the relation between the azimuth time for each image line and the azimuth updating time for each SRGR records. Five scenes of ASAR image have been geolocated with this method and the relative geolocation accuracy has been evaluated taking the geographic locations of four image corners derived from SAR metadata as reference. The geographic locations of the four image corners have been calculated and stored in the metadata of SAR image product by the original SAR processor. The product type ID for the five image products is APP -1P, APM -1P, APS -1P, IMP -1P and IMM -1P respectively. It has been shown that the location error in both latitude and longitude direction is below 1.0 meter for precision products such as APP -1P, APS -1P and IMP -1P; For median resolution products such as APM -1P and IMM -1P, the maximum longitude error is 59.73 m, about 0.8 times of the image pixel space; and the maximum latitude error is 83.38m, about 1.1 times of the image pixel space. It shows that the geolocation result achieved by the developed method is quite consistent with that achieved by the SAR processor to produce these ASAR image products. Also, the result will be useful for the development of orth-rectification and the other relevant processing algorithms for ASAR image products.