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Top1. Introduction
The SAR has been used widely in both the civil and military fields, due to its high-resolution imaging capability to work under meteorological conditions, such as night or day, rain or snow, and so on (Zhu, et al., 2011; Wang, et al., 2016). The idea of using SAR images are considered in order to obtain high precision for localization (Ender, 1999). In addition, the processing of SAR images provides improved azimuth resolution with the usage of platform movement to produce a synthetic and longer antenna. To ensure better resolution, the acquisition time is quite long. The major limitation is that the processing of SAR has been developed for imaging the non-moving targets. In parallel with the SAR, a number of methods have been developed for processing the moving targets, separately from that of the non-moving ones, and these methods are generally termed as moving targets indicators (MTI) (Taylor, et al., 2017). The SAR data addresses the task of extracting information that describes the moving objects. In general, SAR was designed for imaging only the static objects. However, with advanced methods of processing, information on moving objects are extracted when simultaneously imaging the area of interest. In addition, SAR data can be obtained nearly independent of daylight and weather conditions that provide a unique sensor technology (Maqbali, 2020), which can be used in a wide range of tracking applications (Henke, et al., 2018).
There exist various imperative goals, including vegetation coverage and terrain classification, geodetic surveying, and mapping that could not be performed easily in a single-band SAR system, but can be done in the multi-band SAR system in a successful manner. Hence, the multi-band SAR system is becoming an important aspect in the development of SAR technology in recent years 1999, (Palubinskas, et al., 2007; Wang, et al., 2016). With the increasing needs in military, civilian and medical (Sailee Bhambere, 2017; Sailee D Bhambere 2017) areas, it is highly required that the SAR system needs the capability of detecting, re-locating, and image moving targets in an accurate manner with minimum power (Swamy, et al., 2013). There are various techniques for MTD (Groen, et al., 2009), which can be classified as two classes, namely single-channel methods and multi-channel methods. With the use of a single channel, the MTI and imaging is performed by using the phase and amplitude information (Groen, et al., 2009). However, the signal of a moving target that is within the clutter Doppler width is masked with the stationary clutter, and hence, its indication becomes tedious. To solve this problem, a novel algorithm (Raynal, et al., 2014) is used to find the motion parameter corresponding to fast-moving targets with a single-antenna airborne SAR system. The clutter is effectively suppressed with the help of the de-sampled data, whereas the moving targets with even ambiguities are not capable to be detected and its range curvature is not possible to be corrected. To produce an enhanced clutter suppression result, multi-channel methods, such as space-time adaptive processing are analyzed (Hu, 2020)(Shu, et al., 2011).