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www.geospatialworld.net | May-June 2020 50 slant-range resolution) will have more noise than one generated with 150 MHz (1 m slant- range resolution). A wider bandwidth enables beer resolution, but causes more noise in imagery (higher NESZ). Speckle, radiometric resolution, and target detection & identification Speckle is caused by the reflection of the radar signal from multiple objects (scaerers) that are distributed within a resolution cell. e branches and leaves of a tree, grass and rocks in a field, and bricks that make up the walls of a building are examples of objects that have distributed scaerers. e sum of the contribution from all the scaerers results in variation in the intensity of the measured signal in adjacent resolution cells. is varia- bility in image intensity, called speckle, limits the radiometric resolution of a SAR sensor. Speckle in images looks like the snowy noise found on old analog television sets. Speckle makes it harder to distinguish features in SAR images because it corrupts the outline of objects. Radiometric resolution is a metric that describes the ability of a sensor to discriminate between two objects that have similar radar cross sections (i.e., that are radiometrically sim- ilar). Radiometric resolution depends on the measured signal to noise ratio and the number of independent looks from which the pixel was formed. Overcoming speckle and improving radiometric resolution is only possible by averaging multiple SAR images or averaging pixels in a SAR image. is averaging process is commonly referred to as "multi-looking". Multi-looking in single SAR images is most typically done by averaging adjacent pixels. Sometimes this averaging is achieved using sophisticated techniques, but the result is always a loss of resolution compared to the original image. For example, a 4-look 1 m (slant range resolution) × 1 m (azimuth resolution) spotlight image could be created from a SAR acquisition that has a slant range-resolution of 1 m and an azimuth resolution of 0.25 m, by averaging 4 adjacent 0.25 m resolution cells to form a 1 m cell in the azimuth direction. Multi-looking is a common pre-process- ing step for SAR users interested in change detection or in target detection or classifi- cation. We demonstrate the image quality improvement using multi-looking with Capella data. e images in the le column of Figure 4 are from a low-resolution SAR imaging mode that has been multi-looked to reduce speckle and improve radiometric resolution. e boxed sections of the image have been reproduced below to show that the loss of spatial resolution significantly hinders identification of objects in the scene. e images in the middle column are single-look 0.5 m resolution images (both azimuth and ground range) where the speckle in the image hinders the identification of small targets. e Figure 3: NESZ is a metric that informs about the system noise level in a SAR image. NESZ is usually provided as a log- scale quantity in dB, and more negative values indicate beer image quality. For SAR users, the required NESZ depends on the application. Hard target detection and vegetation analysis have very different NESZ and resolution requirements. Figure 4: Low-resolution multi-looked image (le column), high-resolution single-look image (middle column), and high-resolution multi-looked image (right column). ese images highlight that both resolution and speckle affect interpretation of the image. image in the third column is a multi-looked 0.5 m resolution image. e shadow of the air- cra is significantly improved, and the features on the grassy areas are clearly visible. Conclusion In SAR, a few key metrics define the perfor- mance of the system. First, and not surprisingly, resolution is an important measure. Sub-meter resolution is considered a "must have", but as demonstrated in this article, image interpreta- tion is a function of spatial resolution, NESZ, speckle, and radiometric resolution. Low-NESZ imagery is desirable because objects that scaer radar signals weakly are visible in low-NESZ SAR images, but high resolution and low NESZ are not the only factors that influence interpretation and detection in SAR images. Speckle makes it harder to distinguish features in SAR images because it reduces the contrast between objects. us, the interpretability of SAR images is determined by a complex mix of resolution, NESZ, and multi-looking. ese factors are critical but are oen overlooked in common discourse surrounding SAR. Novice and expert SAR users should consider all of these parameters when selecting SAR imagery for their application. Davide Castellei, SAR Technical Product Manager; Gordon Farquharson, Director of Radar Technologies, Capella Space WIDE ANGLE

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