Anders Kusk

Azimuth phase coding for range ambiguity suppression in SAR

A novel ambiguity suppression technique is proposed. Range ambiguities in synthetic aperture radar (SAR) images are eliminated with an azimuth filter after having applied an azimuth phase modulation to the transmitted pulses and a corresponding demodulation to the received pulses. The technique excels by actually eliminating the ambiguities rather than just defocusing them as most other techniques do. This makes the proposed technique applicable to distributed targets. The range ambiguity suppression permits the pulse repetition frequency (PRF) to exceed the upper limit otherwise defined by the antenna elevation dimension. The fundamental antenna area constraint still applies, but the PRF can be chosen with more freedom. In addition to ambiguity suppression, potential applications include nadir return elimination and signal-to-noise ratio improvement

Synthetic aperture radar data processing on an FPGA multi-core system

Synthetic aperture radar, SAR, is a high resolution imaging radar. The direct back-projection algorithm allows for a precise SAR output image reconstruction and can compensate for deviations in the flight track of airborne radars. Often graphic processing units, GPUs are used for data processing as the back-projection algorithm is computationally expensive and highly parallel. However, GPUs may not be an appropriate solution for applications with strictly constrained space and power requirements. In this paper, we describe how we map a SAR direct back-projection application to a multi-core system on an FPGA. The fabric consisting of 64 processor cores and 2D mesh interconnect utilizes 60% of the hardware resources of a Xilinx Virtex-7 device with 550 thousand logic cells and consumes about 10 watt. We apply software pipelining to hide memory latency and reduce the hardware footprint by 14%. We show that the system provides real-time processing of a SAR application that maps a 3000m wide area with a resolution of 2x2 meters.

SAR focusing of P-band ice sounding data using back-projection

SAR processing can be applied to ice sounder data to improve along-track resolution and clutter suppression. This paper presents a time-domain back-projection technique for SAR focusing of ice sounder data. With this technique, variations in flight track and ice surface slope can be accurately accommodated at the expense of computation time. The back-projection algorithm can be easily parallelized however, and can advantageously be implemented on a graphics processing unit (GPU). Results from using the back-projection algorithm on POLARIS ice sounder data from North Greenland shows that the quality of data is improved by the processing, and the performance of the GPU implementation allows for very fast focusing.

Ice flow mapping with P-band SAR

Glacier and ice sheet dynamics are currently mapped with X-, C-, and L-band SAR. With the prospect of a P-band SAR, Biomass, to be launched within the next decade it is interesting to look into the potential of P-band for ice velocity mapping. In this paper first results are presented. Airborne P-band SAR data have been acquired in Greenland, and both offset tracking and DInSAR have been applied to the full resolution data as well as to data degraded to the resolution of Biomass. Generally, ice velocity maps are successfully generated, but in the ablation zone, DInSAR fails in the melt season at both resolutions, while feature tracking fails at the coarser resolution.

P-band radar ice sounding in Antarctica

In February 2011, the Polarimetric Airborne Radar Ice Sounder (POLARIS) was flown in Antarctica in order to assess the feasibility of a potential space-based radar ice sounding mission. The campaign has demonstrated that the basal return is detectable in areas with up to 3 km thick cold ice, in areas with up to several hundred meters thick warm shelf ice, and in areas with up to 700 m thick crevassed glacier ice. However, major gaps in the basal return are observed, presumably due to excessive absorption, scattering from ice inclusions in the firn, low basal reflectivity, and the masking effect of the surface clutter. Internal layers are observed down to depths exceeding 2 km. The polarimetric data show that the internal layers are strongly anisotropic at a ridge, where the ice flow is supposed to be highly unidirectional. In case of space-based ice sounding, the antenna pattern cannot offer sufficient surface clutter suppression, but improved clutter suppression has been demonstrated with novel multi-phase-center techniques.

Improving SAR Automatic Target Recognition Models With Transfer Learning From Simulated Data

Data-driven classification algorithms have proved to do well for automatic target recognition (ATR) in synthetic aperture radar (SAR) data. Collecting data sets suitable for these algorithms is a challenge in itself as it is difficult and expensive. Due to the lack of labeled data sets with real SAR images of sufficient size, simulated data play a big role in SAR ATR development, but the transferability of knowledge learned on simulated data to real data remains to be studied further. In this letter, we show the first study of Transfer Learning between a simulated data set and a set of real SAR images. The simulated data set is obtained by adding a simulated object radar reflectivity to a terrain model of individual point scatters, prior to focusing. Our results show that a Convolutional Neural Network (Convnet) pretrained on simulated data has a great advantage over a Convnet trained only on real data, especially when real data are sparse. The advantages of pretraining the models on simulated data show both in terms of faster convergence during the training phase and on the end accuracy when benchmarked on the Moving and Stationary Target Acquisition and Recognition data set. These results encourage SAR ATR development to continue the improvement of simulated data sets of greater size and complex scenarios in order to build robust algorithms for real life SAR ATR applications.

Multichannel surface clutter suppression: East Antarctica P-band SAR ice sounding in the presence of grating lobes

Abstract Ice sounding with radar is a well-established technique for the retrieval of ice depth, and provides information on ice structures and layering. Airborne radar ice sounders suffer from off-nadir surface clutter that masks the signal from bedrock and ice layers with unwanted but simultaneously received surface reflections. This is of importance for future satellite ice-sounding missions, as the spaceborne geometry leads to strong surface clutter even for deep subsurface returns. This paper presents analysis and comparison of different clutter-suppression techniques applied to data acquired with the European Space Agencys P-band POLarimetric Airborne Radar Ice Sounder (POLARIS). The 4 m long antenna of POLARIS enables simultaneous reception of up to four across-track channels. It was operated in 2011 over Antarctica at a high flight altitude of 3200 m. Different coherent weighting techniques of the receive channels were used to suppress the surface ‘clutter’. However, with a channel spacing of 1.4 times the wavelength, the grating lobe imposes a limitation to the off-nadir angular range in which clutter can be effectively attenuated. Results of ice sounding over Jutulstraumen glacier are described, where we demonstrate a clutter suppression of up to 10 dB.

300 GHz imaging with 8 meter stand-off distance and one-dimensional synthetic image reconstruction

An active system for stand-off imaging operating in a frequency range from 234 GHz to 306 GHz is presented. Imaging is achieved by combining a line array consisting of 8 emitters and 16 detectors with a scanning cylindrical mirror system. A stand-off distance of 7-8 m is achieved using a system of mirrors with effective aperture of 0.5 x 0.5 meter. Information about range and reflectivity of the object are obtained using an active FMCW (frequency modulated continuous wave) radar operation principle. Data acquisition time for one line is as short as 1 ms. Synthetic image reconstruction is achieved in real-time by an embedded GPU (Graphical Processing Unit).

A mul ti-element THz imaging system

We report on a broadband multi-element THz imaging system based on fiber-coupled, integrated photoconductive emitters and detectors. 32 detectors and 32 emitters are arranged in a planar array. Advanced image reconstruction algorithms are employed to reconstruct an object in the imaging plane.

Intercomparison and Validation of SAR-Based Ice Velocity Measurement Techniques within the Greenland Ice Sheet CCI Project

Ice velocity is one of the products associated with the Ice Sheets Essential Climate Variable. This paper describes the intercomparison and validation of ice-velocity measurements carried out by several international research groups within the European Space Agency Greenland Ice Sheet Climate Change Initiative project, based on space-borne Synthetic Aperture Radar (SAR) data. The goal of this activity was to survey the best SAR-based measurement and error characterization approaches currently in practice. To this end, four experiments were carried out, related to different processing techniques and scenarios, namely differential SAR interferometry, multi aperture SAR interferometry and offset-tracking of incoherent as well as of partially-coherent data. For each task, participants were provided with common datasets covering areas located on the Greenland ice-sheet margin and asked to provide mean velocity maps, quality characterization and a description of processing algorithms and parameters. The results were then intercompared and validated against GPS data, revealing in several cases significant differences in terms of coverage and accuracy. The algorithmic steps and parameters influencing the coverage, accuracy and spatial resolution of the measurements are discussed in detail for each technique, as well as the consistency between quality parameters and validation results. This allows several recommendations to be formulated, in particular concerning procedures which can reduce the impact of analyst decisions, and which are often found to be the cause of sub-optimal algorithm performance.