Image fusion techniqes for remote sensing applications

Image fusion refers to the acquisition, processing and synergistic combination of information provided by various sensors or by the same sensor in many measuring contexts. The aim of this survey paper is to describe three typical applications of data fusion in remote sensing. The first study case considers the problem of the Synthetic Aperture Radar (SAR) Interferometry, where a pair of antennas are used to obtain an elevation map of the observed scene; the second one refers to the fusion of multisensor and multitemporal (Landsat Thematic Mapper and SAR) images of the same site acquired at different times, by using neural networks; the third one presents a processor to fuse multifrequency, multipolarization and mutiresolution SAR images, based on wavelet transform and multiscale Kalman filter. Each study case presents also results achieved by the proposed techniques applied to real data

Interferometric Synthetic Aperture Sonar Signal Processing for Autonomous Underwater Vehicles Operating Shallow Water

The goal of the research was to develop best practices for image signal processing method for InSAS systems for bathymetric height determination. Improvements over existing techniques comes from the fusion of Chirp-Scaling a phase preserving beamforming techniques to form a SAS image, an interferometric Vernier method to unwrap the phase; and confirming the direction of arrival with the MUltiple SIgnal Channel (MUSIC) estimation technique. The fusion of Chirp-Scaling, Vernier, and MUSIC lead to the stability in the bathymetric height measurement, and improvements in resolution. This method is computationally faster, and used less memory then existing techniques

Weighted Kalman filter phase unwrapping algorithm based on inSAR image

The Kalman filter deals simultaneously with phase unwrapping and noise elimination procedure. But the errors produced by the original radar signal and post-processing can cause phase discontinuity so that the unwrapped result is not accurate. Therefore, the weighted Kalman filter phase unwrapping algorithm based on InSAR image is proposed. Through the low-quality region where the wrapped phase is masked, the Kalman filter phase unwrapping algorithm is implemented in the high-quality region. When the high-quality region is correctly unwrapped, the weighted Kalman filter phase unwrapping algorithm is implemented in masking off the low-quality region, and as a consequence a reliable result is obtained. In this paper InSAR data is chosen for performing the experiment, and for comparison with both a network flow algorithm and a quality map guided algorithm. It is subsequently verified that the proposed algorithm is effective and reliable

Unwrapped phase estimation via normalized probability density function for multibaseline InSAR

Interferometric synthetic aperture radar (InSAR) is a powerful technique for obtaining terrain information based on the interferometric phase. Multibaseline (MB) InSAR is an extension of the conventional InSAR and is used to improve the estimation accuracy and reliability of the unwrapped phase. Based on a newly defined normalized phase probability density function (pdf), a novel wrapped-to-unwrapped phase (W2UP) estimation method is proposed for MB-InSAR. First, the concept of the normalized pdf is introduced to overcome the limitation of the fixed 2π period for different baseline cases. Then, a new maximum likelihood estimation is established using the MB normalized pdfs, which has a much steeper peak around the true phase value than the single baseline case and leads to higher estimation accuracy. The proposed W2UP method estimates the unwrapped phase from multiple filtered interferograms, so it is less influenced by the phase noise. Both the theoretical analysis and results using the simulated and real MB data are provided to verify the effectiveness of the proposed method

Interferometric synthetic aperture sonar system supported by satellite

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

High-accuracy digital elevation model generation and ship monitoring from synthetic aperture radar images: innovative techniques and experimental results.

In this Thesis several state-of-the-art and innovative techniques for Digital Elevation Model (DEM) generation from Synthetic Aperture Radar (SAR) images are deeply analyzed, with a special focus on the methods which allow the improvement of the accuracy of the DEM product, which is directly related to the geolocation accuracy of geocoded images and is considered as an enabling factor for a large series of civilian and Defence applications. Furthermore, some of the proposed techniques, which are based both on phase and amplitude information, are experimented on real data, i.e. COSMO-SkyMed (CSK) data, assessing the achievable performances compared with the state-of-the-art, and pointing out and quantitatively highlighting the acquisition and processing strategies which would allow to maximize the quality of the results. Moreover, a critical analysis is performed about the main errors affecting the applied techniques, as well as the limitations of the orbital configurations, identifying several complementary techniques which would allow to overcome or mitigate the observed drawbacks. An innovative procedure for on-demand DEM production from CSK SAR data is elaborated and proposed, as well as an auto-validation technique which would enable the validation of the produced DEM also where vertical ground truths are not available. Based on the obtained results and on the consequent critical analysis, several interferometric specifications for new generation SAR satellites are identified. Finally, a literature review is proposed about the main state-of-the-art ship monitoring techniques, considered as one of the main fields of application which takes benefit from SAR data, based on single/multi-platform multi-channel SAR data, with a focus on TanDEM-X (TDX). In particular, in Chapter 1 the main concepts concerning SAR operating principles are introduced and the main characteristics and performances of CSK and TDX satellite systems are described; in Chapter 2 a review is proposed about the state-of-the-art SAR interferometric techniques for DEM generation, analyzing all the relevant processing steps and deepening the study of the main solutions recently proposed in the literature to increase the accuracy of the interferometric processing; in Chapter 3 complementary and innovative techniques respect to the interferometric processing are analyzed to mitigate disadvantages and to improve performances; in Chapter 4 experimental results are presented, obtained in the generation of high accuracy DEM by applying to a dataset of CSK images properly selected state-of-the-art interferometric techniques and innovative methods to improve DEM accuracy, exploring relevant limitations, and pointing out innovative acquisition and processing strategies. In Chapter 5, the basic principles of Ground Moving Target Indication (GMTI) are described, focusing on Displaced Phase Center Antenna (DPCA) and Along-Track Interferometry (ATI) techniques

Monitoring land surface deformation using persistent scatterers interferometric synthetic aperture radar technique

Land subsidence is one of the major hazards occurring globally due to several reasons including natural and human activities. The effect of land subsidence depends on the extent and severity. The consequences of this hazard can be seen in many forms including damaged of infrastructures and loss of human lives. Although land subsidence is a global problem, but it is very common in urban and sub urban areas especially in rapidly developing countries. This problem needs to be monitored effectively. Several techniques such as land surveying, aerial photogrammetry and Global Positioning System (GPS) can be used to monitor or detect the subsidence effectively but these techniques are mostly expensive and time consuming especially for large area. In recent decades, Interferometric Synthetic Aperture Radar (InSAR) technique has been used widely for the monitoring of land subsidence successfully although this technique has several limitations due to temporal decorrelation, atmospheric effects and so on. However, the uncertainties related to InSAR technique have been reduced significantly with the recent Persistent Scatterers Interferometric Synthetic Aperture Radar (PSInSAR) technique which utilized a stack of interferograms generated from several radar images to estimate deformation by finding a bunch of stable points. This study investigates the surface deformation focusing on Kuala Lumpur, a rapidly growing city and Selangor using PSInSAR technique with a set of ALOS PALSAR images from 2007 to 2011. The research methodology consists of several steps of image processing that incudes i) generation of Differential Interferometric Synthetic Aperture Radar (DInSAR), ii) selection of Persistent Scatterers (PS) points, iii) removal of noise, iv) optimization of PS point selection, and v) generation of time series deformation map. However, special consideration was given to optimize the PS selection process using two master images. Results indicate a complete variation of mean line-of-sight (LOS) velocities over the study area. Stable areas (mean LOS=1.1 mm/year) were mostly found in the urban center of Kuala Lumpur, while medium rate of LOS (from 20 mm/year to 30 mm/year) was observed in the south west area in Kuala Langat and Sepang districts. The infrastructures in Kuala Lumpur are mostly stable except in Kuala Lumpur International Airport (KLIA) where a significant subsidence was detected (28.7 mm/year). Meanwhile, other parts of the study area such as Hulu Langat, Petaling Jaya and Klang districts show a very low and non-continuous movement (LOS < 20 mm/year), although comparatively higher subsidence rate (28 mm/year) was detected in the mining area. As conclusion, PSInSAR technique has a potential to monitor subsidence in urban and sub urban areas, but optimization of PS selection processing is necessary in order to reduce the noise and get better estimation accuracy