This thesis deals with proposing novel processing techniques with applications in the field of Satellite Synthetic Aperture Radar (SAR) Altimetry. Satellite SAR Altimetry is the technique capable of measuring the altitude of a target (as ocean, coastal waters, sea ice, inland waters, etc.) on Earth from space exploiting the Doppler effect between the satellite and the target. The thesis is based essentially on the exploitation and processing of SAR data from the ESA Earth Explorer CryoSat-2 and the Copernicus mission Sentinel-3, which are the only two missions having on board a SAR altimeter. First, a short summary of the concept of SAR altimetry is given, by reviewing as well the state of the art of the discipline and the latest novelties in the field. Then, the methods used here to enhance the standard SAR Altimetry processing chain (Delay-Doppler Algorithm, K.R. Raney 1998) are presented. The enhancement consists in dedicated processing options at L1b level which may be regarded as complements or additions to the Delay-Doppler algorithm. Furthermore, a new approach in SAR waveform retracking has been proposed in order to retrieve accurate altitude measurements over open ocean, the coastal zone, inland water and sea ice. This consists in a new algorithm to extract the geophysical information from the radar waveforms, which is a modification of the SAMOSA SAR physically-based SAR return waveform model introduced by Ray et al., (2015). Once the evidence was gathered that this SAMOSA-based open ocean retracker was performing properly (see Fenoglio-Marc et al., 2015), an upgrade of the algorithm specifically tailored to the coastal zone and referred to as SAMOSA+ has been developed. This algorithm has been described and validated in Dinardo et al., (2018) with success in the coastal zone. Especially in coastal zone this dedicated coastal SAR retracking has brought a significant improvement with respect to the nominal SAR products from the mission ground segments. Moreover, the algorithm produces very accurate measurements of the sea-ice freeboard as well. This is a significant finding, because obtained by a physically-based retracker originally designed for the coastal zone data exploitation. However, SAMOSA+ has some limitations described in the thesis and does not perform as expected over inland water. For this reason, a further evolution of the SAMOSA+ algorithm, coined SAMOSA++, has been developed. The main novelty consists in accounting for the RIP (Range Integrated Power), which can be regarded as an extra waveform provided by SAR altimetry and has not been exploited by the altimetry community so far. The objective of this last retracker is to be “pan-thematic”, in other words suitable to any possible altimetry application. The results obtained from this novel technique have been extensively presented on different thematic applications such as marine surfaces (both open ocean and the coastal zone) and inland water (over two selected test cases), and are always outperforming the other retrackers. Based on the toolkits developed during this thesis, a SAR altimetry service has been developed and is now operational on the ESA G-POD grid platform. The service has been used to process online and on-demand all the data used in the thesis work and is daily used by experts in the field of altimetry. The validation has been done against in situ data, ocean numerical models and against standard altimetry products processed in SAR mode from the missions’ ground segment altimeter datasets against products processed in Pseudo Low Resolution Mode (PLRM). This last product type corresponds to the conventional processing methodology used before SAR era (referred to commonly as PLRM). These results give strong evidence that the improvement brought by the novel technique is significant over all three thematic applications when compared with the state of the art. All these innovations will help scientists to monitor the sea level in the coastal zone, the inland water management and to improve the computation of the sea ice freeboard.