本文提出了一种新的自动换合成孔径雷达（SAR）时间序列检测技术，即广义有序序列分析方法。-This paper presents a new automatic change de-

tection technique for synthetic aperture radar (SAR) time se-

ries, i.e., Method for generalIzed Means Ordered Series Analysis

(MIMOSA). The method compares only two different temporal

means between the amplitude images, whatever the length of the

time series. The method involves three different steps: 1) estima-

tion of the amplitude distribution parameters over the images

2) computation of the theoretical joint probability density function

between the two temporal means　and 3) automatic thresholding

according to a given false alarm rate, which is the only change

detection parameter. The procedure is　d with a very low

computational cost and does not require any spatial speckle fi lter-

ing. Indeed, the full image resolution is used. Due to the temporal

means, the data volume to process is reduced, which is very help-

ful.Moreover, the two means can be simply updated using the new

incoming images only. Thus, the full