Patrik Dammert

C-band repeat-pass interferometric SAR observations of the forest

Properties of ERS-1 C-band repeat pass interferometric SAR information for a forested area are studied. The intensity information is rather limited but, including coherence and effective interferometric SAR (INSAR) height, more information about the forest parameters can be obtained via satellite. Such information is also important for correction of INSAR derived topographic maps. Coherence properties have been used to identify forested/nonforested areas and the interferometric effective height of the forest determined by comparison to a DEM of the area. The authors have developed a model to relate basic forest properties to INSAR observations. These show that the coherence and interferometric effective height of a forested area change between image pairs. The model demonstrates how these properties are related to the temporal decorrelation and the scattering from the vegetation canopy and the ground surface. Gaps in the vegetation are found to be important in the characterization of boreal forests.

X-Band Interferometric SAR Observations of Baltic Fast Ice

Detailed mapping of fast-ice deformation can be used to characterize the rheological behavior of fast ice and subsequently improve sea ice modeling. This study uses interferometric synthetic aperture radar to map fast-ice deformation with unprecedented spatial resolution (meter range) and sensitivity (cm-mm range). Two interferometric acquisitions, each with a temporal baseline of 24 h, were performed by the X-band SAR satellite constellation Cosmo-SkyMed over the northeast Bay of Bothnia in the middle of the 2012 ice season. The first interferogram shows deformation of the fast ice due to force from impinging drift ice, and the normal strain within the fast ice is measured. Complementary intensity correlation measurements reveal a slow movement of the drift ice toward the fast ice. The second interferogram exhibits a low fringe rate over the fast ice with fringes being aligned along the coastline. Deformation appears to be stronger around leads, skerries, and grounded ice ridges. It is also observed that the coherence images provide information that is complementary to the information in the backscatter images.

An Efficient Solution to the Factorized Geometrical Autofocus Problem

This paper describes a new search strategy within the scope of factorized geometrical autofocus (FGA) and synthetic-aperture-radar processing. The FGA algorithm is a fast factorized back-projection formulation with six adjustable geometry parameters. By tuning the flight track step by step and maximizing focus quality by means of an object function, a sharp image is formed. We propose an efficient two-stage approach for the geometrical variation. The first stage is a low-order (few parameters) parallel search procedure involving small image areas. The second stage then combines the local hypotheses into one global autofocus solution, without the use of images. This method has been applied successfully on ultrawideband CARABAS II data. Errors due to a constant acceleration are superposed on the measured track prior to processing, giving a 6-D autofocus problem. Image results, including resolution, peak-to-sidelobe ratio and magnitude values for point-like targets, finally confirm the validity of the strategy. The results also verify the prediction that there are several satisfying autofocus solutions for the same radar data.

The Stability of UWB Low-Frequency SAR Images

This letter presents an analysis of prefiltered clutter ultrawideband (UWB) very high frequency synthetic aperture radar (SAR) images. The image data are reorganized into subvectors based on the observation of the image-pair magnitude samples. Based on this approach, we present a statistical description of the SAR clutter obtained by the subtraction between two real SAR images. The statistical analysis based on bivariate distribution data organized into different intervals of magnitude can be an important tool to further understand the properties of the backscattered signal for low-frequency SAR images. In this letter, it is found that, for “good” image pairs, the subtracted image has Gaussian distributed clutter backscattering and that the noise mainly consists of the thermal noise and, therefore, speckle noise does not have to be considered. This is a consequence of the stable backscattering for a UWB low-frequency SAR system.

SAR image statistics and adaptive signal processing for change detection

The paper represents investigations on SAR image statistics and adaptive signal processing for change detection. The investigations show that the amplitude distributions of SAR images with possibly detected changes, that is retrieved with a linear subtraction operator, can approximately be represented by the probability density function of the Gaussian or normal distribution. This allows emerging the idea to use the available adaptive signal processing techniques for change detection. The experiments indicate the promising change detection results obtained with an adaptive line enhancer, one of the adaptive signal processing technique. The experiments are conducted on the data collected by CARABAS, a UWB low frequency SAR system.

False Alarm Reduction in Wavelength-Resolution SAR Change Detection Using Adaptive Noise Canceler

This paper introduces a method to reduce false alarms in wavelength-resolution synthetic aperture radar (SAR) change detection and aims at very high frequency-band systems like the Coherent All Radio Band System (CARABAS). The false alarms are usually caused by the elongated structures, such as power lines and fences, which stand out from the background. The responses of elongated structures are sensitive to flight path. The introduced method aims at minimizing the false alarms caused by the elongated structures and is based on the well-known adaptive processing mechanism, i.e., the so-called adaptive noise canceler (ANC) where a separate reference signal is required. The changes between measurements are considered by the input signal of ANC while the separate reference signal comes from the measurements without change. Hence, the method requires three SAR images associated with three measurements, with no changes between two of them. The reference data for the study are provided by CARABAS. The experimental results indicate that the method can reduce false alarms significantly and provide high probability of detection (≥98%). The experimental results also show that the method still works well even in the case where the flight tracks of the SAR system in the change detection measurements are slightly different.

Polarimetric subsurface SAR imaging outcome of theoretical development and CARABAS III tests

This is a preliminary report on theoretical and experimental results regarding SAR imaging of buried targets. The work has been motivated by the CARABAS III radar development ongoing at Saab. The radar operates in the two bands with centre frequencies 55 and 220 MHz and with a bandwidth equal to the centre frequency. The radar design went partly parallel with a theoretical modelling work for subsurface targets. Theory predicted that the best options for discriminating the weak subsurface returns from surface returns was to use of shallow depression angles and polarimetry. However in this case returns will be very weak and radar operation must be short range. The radar is designed to comply with these requirements and performing our first dedicated subsurface detection experiments in the autumn 2013, the results obtained vividly support the theoretical predictions made.

Autofocus and analysis of geometrical errors within the framework of fast factorized back-projection

This paper describes a Fast Factorized Back-Projection (FFBP) formulation that includes a fully integrated autofocus algorithm, i.e. the Factorized Geometrical Autofocus (FGA) algorithm. The base-two factorization is executed in a horizontal plane, using a Merging (M) and a Range History Preserving (RHP) transform. Six parameters are adopted for each sub-aperture pair, i.e. to establish the geometry stage-by-stage via triangles in 3-dimensional space. If the parameters are derived from navigation data, the algorithm is used as a conventional processing chain. If the parameters on the other hand are varied from a certain factorization step and forward, the algorithm is used as a joint image formation and autofocus strategy. By regulating the geometry at multiple resolution levels, challenging defocusing effects, e.g. residual space-variant Range Cell Migration (RCM), can be corrected. The new formulation also serves another important purpose, i.e. as a parameter characterization scheme. By using the FGA algorithm and its inverse, relations between two arbitrary geometries can be studied, in consequence, this makes it feasible to analyze how errors in navigation data, and topography, affect image focus. The versatility of the factorization procedure is demonstrated successfully on simulated Synthetic Aperture Radar (SAR) data. This is achieved by introducing different GPS/IMU errors and Focus Target Plane (FTP) deviations prior to processing. The characterization scheme is then employed to evaluate the sensitivity, to determine at what step the autofocus function should be activated, and to decide the number of necessary parameters at each step. Resulting FGA images are also compared to a reference image (processed without errors and autofocus) and to a defocused image (processed without autofocus), i.e. to validate the novel approach further.

Factorized geometrical autofocus: On the geometry search

This paper deals with local geometry optimization within the scope of Factorized Geometrical Autofocus (FGA). The FGA algorithm is a Fast Factorized Back-Projection (FFBP) formulation with six free geometry parameters. These are tuned until a sharp image is obtained, i.e. with respect to an object function. To optimize the geometry (from a focus perspective) for a small image area, we propose an efficient routine based on correlation, sensitivity analysis and Broyden-Fletcher-Goldfarb-Shanno (BFGS) minimization. The new routine is evaluated using simulated Ultra-WideBand (UWB) data. By applying the FGA algorithm step-by-step, an erroneous geometry is compensated. This gives a focused image. In regard to run time, the new routine is approximately 100 times faster than a brute-force approach, i.e. for this FGA problem. For a general problem, the run time reduction will be far greater. To be more specific: with x parameters and N values to assess for each parameter; it is anticipated that the computational effort will decrease exponentially by a factor close to Nx.

Likelihood ratio test for incoherent wavelength-resolution SAR change detection

The paper introduces a new likelihood ratio test for incoherent wavelength-resolution SAR change detection where the assumption of bivariate zero-mean circular Gaussian processes for noise and clutter is replaced by bivariate Rayleigh processes. This replacement brings a higher average probability of detection and/or lower false alarm rate. Hence, the experimental result shows that an average probability of detection is up to 98% with few low false alarms.