Abstract-In repeat-pass interferometric synthetic aperture radar (SAR), man-made scene disturbances are commonly detected by identifying changes in the mean backscatter power of the scene or by identifying regions of low coherence. Change statistics such as the sample mean backscatter-power ratio and the sample coherence, however, are susceptible to high false-alarm rates unless the change in the mean backscatter power is large or there is sufficient contrast in scene coherence between the changed and unchanged regions of the image pair. Furthermore, as the sample mean backscatter-power ratio and sample coherence measure different properties of a SAR image pair, both change statistics need to be considered to properly characterize scene changes. In this paper, models describing the changed and unchanged regions of a scene are postulated, and the detection problem is expressed in a Bayesian hypothesis-testing framework. Forming the loglikelihood ratio gives a single sufficient statistic, encoding changes in both the coherence and the mean backscatter power, for discriminating between the unchanged-and changed-scene models. The theoretical detection performance of the change statistic is derived and shows a significant improvement over both the sample mean backscatter-power ratio and sample coherence change statistics. Finally, the superior detection performance of the loglikelihood change statistic is demonstrated using experimental data collected using the Defence Science and Technology Organisation's Ingara X-band airborne SAR.

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In repeat pass Synthetic Aperture Radar Interferometry (MAR) Scene disturbances may be identified as areas coefficient. The backscatter coefficient is dependent on the while the coherence is sensitive to changes in the distribution An examination of Q shows that a number of parameters of scattering elements within resolution cells. The coherence and may be used to discriminate between possible backscatter coefficient thus provide complementary information Scene disturbances and the undisturbed The RCS regarding possible disturbances in the underlying scattering bances using changes in backscatter coefficient or Coherence respectively are determined by " w a l and dielectric however is limited bv hieh false alarm rates unless sienificant moverties of the scatterine medium. Thus anv man-made topography [I]. The magnitude of the complex correlation coefficient y. termed the coherence, models the sources of of low coherence or possibly as areas of changed backscatter temporal change in the Scene [21 as well as decorrelation Structure and dielectric of the ,,,dum arising from system noise and processing aberrations [31.mechanisms. The ability to detect subtle man-made distur-parameters and of the primary and repeat pass images . I I aseraging is carried out resulting in a degradation in the resolution of the change maps. In this paper, models describing the changed and unchanged regions of a scene are postulated and the detection problem is expressed in a hypothesis testing framework. Forming the log likelihood ratio gives a single statistic, encoding both coherence and RCS changes, for discrimating between the unchanged and changed scene models. Expressions for the probability of detection and false alarm are derived for the likelihood ratio and show a significant improvement over both the RCS ratio and sample coherence change statistics. Finally the impmved detection performance is demonstrated using data collected in a repeat pass interferometry experiment with the DSTO Ingara X-baud airborne SAR.