TerraSAR-X payload data processing — First Experiences

NovaSAR-1 is the latest entrant in the Small Satellite category comprising an S-Band Synthetic Aperture Radar (SAR) payload and an Automatic Identification System (AIS) payload. It has been designed and developed by SSTL (Surrey Satellite Technology Limited, UK) in collaboration with Airbus and COMDEV. The SAR payload provides medium resolution SAR data ranging from 6m-45m. The AIS instrument operating in VHF is used to collect data simultaneously along with SAR imagery of the same area for ship detection. The data has immense potential for applications like flood monitoring agricultural crop assessment, forest monitoring, land use mapping, disaster management and maritime applications.National Remote Sensing Centre (NRSC) has been entrusted with the responsibility of Ground segment realization for scheduling, reception, processing and dissemination of NovaSAR data at the Integrated Multi-Mission Ground Segment for Earth Observation Satellites (IMGEOS), to Indian and SAARC users as per the ISRO Pricing policy. NRSC has developed, customized and established the framework of automated workflows for generation of Scene-Based Analysis Ready Data Products (ARD) for NovaSAR. This manuscript describes the NovaSAR process flow in IMGEOS from generation to dissemination of Scene-based ARD products for various SAR imaging modes with a theme-based analysis of the derived Radar backscatter at S-band. The AIS data exploitation with respect to ship detection is also presented. The paper also highlights the primary data quality parameters evaluated on the various imaging modes of NovaSAR.

Abstract. Today's SAR sensors provide a variety of different image modes particularly with regard to multipolarised acquisitions. Until now, each polarisation mode requires a special decomposition which is a severe drawback when designing processing chains. Therefore, a new description for multipolarized SAR data based on the well-known Kennaugh matrix was developed that enables the uniform description and processing of SAR data independent of its polarisation by separating backscattering strength from polarimetric information. This mathematical approach subsequently is extended to the processing of multitemporal SAR data in order to stabilize the polarimetric information over longer periods of time and to enhance temporal changes in the polarimetric backscattering. Because of the high sensitivity of the Kennaugh elements a novel multilooking technique based on the Gaussian pyramid is used that locally adapts the look factor and thus selects the optimal balance between radiometric accuracy and geometric resolution. This methodology is applied to two dual-co-polarized TerraSAR-X acquisitions over the RAMSAR testsite "Upper Rhine" in order to generate value-added products that help to map land cover and land cover changes in consequence of water level changes. The first results are very promising although the interpretation of the observed polarimetric changes is not yet validated. The aim of this paper is to present a further application of the (Differential) Kennaugh matrix which will be the kernel of a polarimetry and change detection processor to be implemented in the coming years.

Flights into the past: full-waveform airborne laser scanning data for archaeological investigation

If one sees a satellite as being a remote sensing platform or as a communication path between two terminals on the Earth, one can appreciate that the spacecraft and its complementary ground infrastructure are essentially electronic devices handling data for the benefit of a ground-based investigator or user. As such, there is a space data-handling system which comprises an onboard and a ground segment. Both segments cover the functions of data collection, data distribution, data processing and storage, data encoding and decoding, timing and synchronisation of events, and data transmission and reception currently forming the well known telemetry data link and the telecommand data link (TTC).

The NOAA-NASA jointly-acquired Joint Polar Satellite System (JPSS) will replace the afternoon orbit component and ground processing system of the current Polar-orbiting Operational Environmental Satellites (POES). The ground system, known as the ‘Common Ground System (CGS)’, and developed by Raytheon Intelligence, Information and Services (IIS) provides command, control, and communications (C3) and data processing and product delivery. The CGS currently flies the Suomi NPP satellite and routes mission data to U.S. ground facilities, where it processes the data into mission products and provides them to US weather centrals. The CGS also supports various levels of data acquisition, routing and processing for multiple other missions across the globe today, with plans for incorporation of more missions in the future. This paper describes discuss the direct contribution of sensors, data routing and processing, and product delivery to the benefit of society. This includes the value chain for sounding data to Global Forecast Models (GFS, NAVGEM, ECMWF) [NWS, DoD, International], Cloud Cover Analysis [USAF], Tropical Storm [NWS, USN, USCG], Soil Moisture [US Army, USDA], Ice Data [USCG, USN], and various unique missions, such as Forest Fire management and Post-Event Power Outage Assessments.

The new ITRF20 includes a geocenter motion (GCM) model and seasonal station corrections, both with annual and semi-annual periods. The GCM model is recommended to be applied when processing space-geodetic observation data and the seasonal station corrections should be applied if no non-tidal modelling is applied for the station coordinates. In the case of the Copernicus Precise Orbit Determination (CPOD) Service this applies to the processing of GNSS data of the Sentinel satellites for precise orbit determination (POD) and to the processing of Satellite Laser Ranging (SLR) tracking data for validation of the estimated Sentinel orbits. The CPOD Service delivers, as part of the Ground Segment of the Copernicus Sentinel-1, -2, -3, and -6 missions, orbital products and auxiliary data files for their use in the corresponding Payload Data Ground Segment (PDGS) processing chains at ESA and EUMETSAT, and to external users through the newly available Copernicus Data Space Ecosystem (https://dataspace.copernicus.eu/). It generates routinely several types of orbital products for Sentinel-1, -2, -3 and -6: predictions, near-real time (< 10 min), short-time critical (< 1.5 days) and non-time critical (< 25 days). The POD quality control within the service is based on comparing the CPOD orbit products to orbit solutions provided by members of the accompanying Copernicus POD Quality Working Group (QWG). A combined orbit generated by CPOD from all available orbit solutions serves as reference for the comparisons. The new ITRF20 modelling opens the door to different Centre-of-Network (CoN) or Centre-of-Mass (CoM) frame realisations, so in order to avoid inconsistencies between the solutions when doing the combination and comparisons, special care must be taken. This study aims to analyse the impact of the new ITRF20 GCM model and the seasonal station corrections on the CPOD Service products. Sentinel orbit comparisons and the corresponding processing metrics are analysed when applying the GCM model or not, with a focus on the geocenter motion modelling used by the different CPOD QWG centres. In the SLR validation, station range biases are routinely estimated as part of the residuals analysis. Preliminary results reveal that the estimates of these range biases show smaller seasonal variations when applying the seasonal station corrections. Detailed analyses will be shown and discussed.

This paper introduces procedures which facilitate the development of and the linking between modular data processing operations into different and versatile system solutions. Based on the concept of data flow diagrams, processes and data flows are considered. With the ability of a process to harness any amount of in-and outputs with different sources and destinations, it is possible to model any conceivable data processing problem. By aggregating a diagram as a new process, it is possible to outsource partial process chains to different abstraction levels. As a result, even very complex solutions can be modelled and explained in a clear way. The introduced uniform execution flow while traversing the graph creates a good readability which facilitates the detection of weaknesses. Moreover, the solution is comprehensive and advances the cooperation in teams and development.

With the support of cloud computing, large quantities of data collected from various WSN applications can be managed efficiently. However, maintaining data security and efficiency of data processing in cloud- WSN (C-WSN) are important and challenging issues. In this paper, we present an efficient data outsourcing scheme based on CP-ABE, which can not only guarantee secure data access, but also reduce overall data processing time. In our proposed scheme, a large file is divided into several data blocks by data owner (DO) firstly. Then, the data blocks are encrypted and transferred to the cloud server in parallel. For data receiver (DR), data decryption and data transmission is also processed in parallel. In addition, data integrity can be checked by DR without any master key components. The security analysis shows that the proposed scheme can meet the security requirement of C-WSN. By performance evaluation, it shows that our scheme can dramatically improve data processing efficiency compared to the traditional CP-ABE method.

In this paper a data acquisition system which is a combination of hardware and software modules provide solution for high frequency data acquisition and processing for the upcoming satellites. The data acquisition system consists of FPGA based hardware for high frequency satellite data reception, preprocessing along with software modules for few elements of higher level processing thus providing near real time processed output products. The demodulator which receives the Intermediate Frequency data demodulates it, can also archive data in the raw form without any preprocessing done on it. But with the in house developed hardware presented in this paper, it enables us to receive and process the demodulated signal from the demodulator on this hardware and transfer to the system housing the hardware, thereby enabling real time data processing of data and structured data archival on system for further processing in near real time. Thus the FPGA provides the service of data acquisition and processing for all the missions in the ground station before it is archived for permanent and structured data. A new high frequency data acquisition system designed to receive data at 2.88 GHz coming from satellites are encoded, encrypted and compressed which are decoded, decrypted and decompressed in the hardware using the data acquisition system. The FPGA hardware, software and server architecture enable us to receive and process high frequency satellite data, such as those transmitted by Cartosat-2S, Cartosat-3 and the upcoming NISAR.

RADARSAT is a Canadian polar orbiting remote sensing satellite launched in November 1995. Its only instrument is a synthetic aperture radar (SAR) that is capable of operating in a number of imaging modes, including the first operational ScanSAR in space. As one of the data reception, processing, and archive facilities for RADARSAT data, the Alaska SAR Facility (ASF) has responded to its science users by establishing a RADARSAT processing system to handle the data processing of all RADARSAT modes. This paper outlines the ASF RADARSAT data processing requirements as driven by the science users and describes the RADARSAT processing system design and implementation approach to meet the challenge of providing ASF with an integrated operational SAR image production facility. Design and implementation attributes that facilitate system growth in handling future SAR missions such as Envisat and HIROS are also addressed.

A simple and direct procedure for the rectification of a certain class of airborne SAR data is presented. The relief displacements of SAR data are effectively removed by means of a digital elevation model and the image is transformed to the ground coordinate system. SAR data from the Danish EMISAR is used. The EMISAR produces data with a geometrical resolution of 2.0 meters. The corrected image is tested against photogrammetric control measurements and an accuracy better than 0.5 pixel corresponding to 0.75 meters is obtained. The results indicate promising possibilities for the application of SAR data in the difficult process of map revision and updating.

In this work, we have extended a procedure for the spatial decorrelation of fully developed speckle, originally developed for single-polarization SAR data, to fully-polarimetric SAR data. Assuming that the SAR processor is the same for all the polarimetric channels, the noise-whitening procedure can be performed applying the decorrelation stage to each channel, separately. Equivalently, the noise-whitening stage is applied to each element of the scattering matrix, before any multilooking operation, either coherent or not, is performed. In order to evaluate the impact of speckle decorrelation on the performance of classical polarimetric despeckling filters, we make use of simulated PolSAR data. We optionally introduce a spatial correlation of the noise in the simulated data by means of a 2D separable Hamming window; then we remove such a correlation by using the whitening procedure and compare the despeckling performance for the three following cases: uncorrelated, correlated, and whitened correlated SLC images. Simulation results show a steady improvement of performance scores, e.g., ENL, which are better after decorrelation than those measured with correlated noise and closely attain those of the uncorrelated case. Also, qualitative results on a true RADARSAT-2 image confirm the trend of the simulated data.

Abstract. The Philippines’s PHL-Microsat program aims to launch its first earth observation satellite, DIWATA, on the first quarter of 2016. DIWATA’s payload consists of a high-precision telescope (HPT), spaceborne multispectral imager (SMI) with liquid crystal tunable filter (LCTF), and a wide field camera (WFC). Once launched, it will provide information about the Philippines, both for disaster and environmental applications. Depending on the need, different remote sensing products will be generated from the microsatellite sensors. This necessitates data processing capability on the ground control segment. Rather than rely on commercial turnkey solutions, the PHL-Microsat team, specifically Project 3:DPAD, opted to design its own ground receiving station data subsystems. This paper describes the design of the data subsystems of the ground receiving station (GRS) for DIWATA. The data subsystems include: data processing subsystem for automatic calibration and georeferencing of raw images as well as the generation of higher level processed data products; data archiving subsystem for storage and backups of both raw and processed data products; and data distribution subsystem for providing a web-based interface and product download facility for the user community. The design covers the conceptual design of the abovementioned subsystems, the free and open source software (FOSS) packages used to implement them, and the challenges encountered in adapting the existing FOSS packages to DIWATA GRS requirements.

The European Space Operations Centre (ESOC) is currently carrying out an ambitious program to standardize the infrastructure used throughout its ground segments in an effort to improve the reliability, cost effectiveness and interoperability. The end product of this program will be the ESA Ground Operation System (EGOS). This paper summarizes the program rational, its goals, the architecture, development approach and current status. I. Introduction A. Overview SOC is responsible for the provision of ground segments for the operation and control of many ESA missions. The scope of the ground segment encompasses the elements required on ground to provide the requisite monitoring and control capabilities. This ranges from the groundstations, through the mission control and flight dynamics functionality, to the archiving and distribution of data to the science community and, in some cases, the initial processing of science data. The provision of simulators for training and operations validation purposes is also covered. Many of the systems that are used in the ground segment have been developed in the past using a variety of different technologies and policies, quite often as standalone projects which did not take into account other developments. EGOS is therefore intended to provide a more standardised infrastructure, which encourages systematic reuse and thus reduce development and maintenance costs. The approach adopted is to use well established S/W engineering principles, build on existing systems and experience, use international standards where available and avoid proprietary systems/standards where possible. Initially EGOS is concentrating on the areas of mission control systems, simulators and some of the ground station equipment, in particular the base-band systems and ground station monitoring and control. In the longer term it is envisaged that the scope will be extended to cover satellite electrical ground support equipment (EGSE), flight dynamics and mission planning systems. EGOS must also permit easy expandability, as it is not possible to forecast with certainty future system requirements. The approach adopted in the architecture is one of a service oriented system based on component application development. The service and component architectures represent two views of the system and are therefore not mutually exclusive, but complementary. Within the overall architecture categories of components have been identified. The first of these are the Core components, these provide the essential services and functionality on which the other components are built. Next come the Common components, these provide widely used services such as file archiving, user management etc. The Core and Common components can effectively be thought of as middleware for the ground data systems. The third category, Custom components, consists of the applications that implement the end user needs. These map roughly onto subsystems, e.g. telemetry chain, telecommanding chain, onboard software maintenance system etc. Encapsulating the overall EGOS architecture is the Service Management Framework (SMF). This provides the mechanism through which the underlying systems expose services to external users and systems in a well defined and controlled manner. To avoid unnecessary dependencies between a set of rules has been prepared specifying whether the different categories of components may utilise the services provided by other components categories. * Head of the Ground Station Backend Section, OPS-GIB † Senior Software Engineer, Data System Infrastructure Division, OPS-GI ‡ Head of the Product Maintenance & Support Section, OPS-GIM § Head of the Operation Centre System Infrastructure Section, OPS-GIC ** Head of the Data System Infrastructure Division, OPS-GI

D-InSAR technique has been widely adopted to monitor land subsidence caused by withdrawal of water, oil, gas, and other minerals. Though many cities in China have seriously suffered from land subsidence caused by ground water over-extracting, few of them have enough money to do the leveling control of the subsidence. Compared with leveling and GPS surveying, D-InSAR is more cost-efficient and precise. As Tianjin city has scores of ERS-1/2 SAR data, thousands of valuable leveling data, smooth topography and severe subsidence, it is an ideal place to test and analyze D-lnSAR technique. However, D-InSAR is liable to be contaminated by atmosphere delay, temporal decorrelation and baseline errors. As these errors cannot be removed by SAR data processing, some auxiliary data such as leveling data and DEM data have been introduced into D-InSAR data processing. Therefore, This work accurately analyzes the features of atmosphere delay and temporal decorrelation with the auxiliary data in Tianjin urban area. The results demonstrate that D-InSAR can detect subsidence within three months. Further actions will be undertaken to improve the D-InSAR subsidence monitoring system, such as using Envisat data, gathering GPS zenith delay data to eliminate the atmosphere delay, and so on. The ultimate interest of our research is to establish a robust, cost efficient city subsidence monitoring system by using D-InSAR technique and other measurement.