Key Techniques Of Signal Processing For Distributed Satellite Interferometic Synthetic Aperture Radar

It is of great importance to acquire digital elevation model (DEM) of the Earth's surface with high accuracy in the fields of military application as well as national economic construction. Interferometric synthetic aperture radar (InSAR) has tremendous potential and broad prospects in generating highly accurate DEM. Distributed satellite InSAR is capable of acquiring large-scale DEM effectively and accomplishing global DEM generation, possessing fabulous advantages compared with other topography measuring methods.The dissertation, with DEM generation by distributed satellite InSAR as the main line, focuses on several key techniques of signal processing. The whole dissertation is composed of the following two parts:In the first part, the single-baseline distributed satellite InSAR (i.e., single pass of two formation-flying satellites) technique is studied. For general topographies, the conventional single-baseline InSAR system with two antenna phase centers has been proved to have the capability to provide the DEMs with high accuracy. However, for complicated topographies containing highly sloping regions or discontinuous surfaces (such as man-made buildings, canyons and steep mountains that exist numerously on the Earth), the performance decreases severely due to the serious undersampling phases and layover phenomena. In this case, the multibaseline InSAR is an effective technique to overcome the drawbacks. Therefore, the second part investigates the multibaseline distributed satellite InSAR (including multi-pass of two formation-flying satellites and single-pass of multiple formation-flying satellites).The main work of the dissertation is summarized as follows:1. In Chapter 2, an improved method for InSAR azimuth prefiltering is proposed based on the principle of coherence. InSAR data processing requires high coherence between the interferometric SAR images, which directly determines the accuracy of the DEM. For the decorrelation induced by the spatial baseline (including the along-track and cross-track baselines), the azimuth and range prefiltering is performed to increase the coherence effectively. Based on the theoretic analysis of the InSAR imaging geometry and signal models, the principle of coherence is revealed, and then we propose that only the radar echoes received by the space sampling positions with the same azimuth angles are coherent, i.e., available for interferometric processing. An improved method for InSAR azimuth prefiltering is proposed according to the same azimuth angle extension. The computer simulation is also carried out to prove that the proposed algorithm has the ability to improve the coherence between interferometric SAR images.2. Chapter 3 presents SAR image coregistration and interferometric phase filtering algorithms based on coarse DEM. On the one hand, InSAR data processing requires high accuracy for the SAR image coregistration. Due to the heavy computation burden, the conventional coregistration algorithms compute the two-dimensional offsets by polynomial fitting of a few control points. However, for complicated topographies or large-scale scenes, the offsets obtained by simply polynomial fitting results in unexpected errors. On the other hand, the phase filtering algorithms always make the assumption that the samples in the local window obey the independent and identically distributed (i.i.d) conditions. But in fact, the obtained samples in the filtering window do not always satisfy the i.i.d conditions due to the terrain changes over the window, thus degrading the phase filtering performance. In order to deal with the above problems, we propose the method that makes full use of the available coarse DEM to assist the operations of SAR image coregistration and interferometric phase filtering with the purposes of increasing the performance and decreasing the computation burden. The proposed method firstly computes the two dimensional shift amounts of each pixel in SAR images according to the coarse DEM and InSAR system parameters. For phase filtering, in order to obtain more i.i.d. samples, we use the interferogram generated by the coarse DEM to compensate the terrain phases of the whole scene.3. InSAR data processing in the combination with the single-pass and multi-pass data is investigated in Chapter 4. For the areas with moderately sloped topographies, the conventional single-baseline InSAR system has the ability to generate the DEMs with high accuracy. However, in order to obtain DEMs for hilly and mountainous areas, the multibaseline InSAR is necessary. There exist various ways to acquire multibaseline InSAR data. In practice, it is a feasible way to obtain multibaseline interferometric data by employing repeat passes of a single-baseline InSAR system that exists already. In this case, the methods for estimating the effective baseline length and coregistering interferograms between multiple pass SAR images are proposed. For baseline estimation, the proposed method unwraps local region phases to acquire the heights of multiple ground scattering units by combining multi-pass interferometric data, and then makes full use of multiple targets'heights and the multi-pass interferogram to estimate the effective baseline length. For interferogram coregistration, an innovative strategy is proposed based on the phase gradient, which avoids the difficulties induced by the serious temporal and spatial baseline decorrelation for the coregistration operation of multiple pass SAR images.4. Chapter 5 deals with the problem of retrieving heights of layovered terrains using multibaseline InSAR. On the basis of studying conventional methods resolving the layover problem, the drawbacks under the narrow band assumption are revealed, especially for the case of high resolutions and long baselines. In order to complete the envelope alignment, the narrowband array echo model is substituted by the wideband array signal model. Two strategies to solve the wideband array model are proposed, with one called the aligning method and the other the joint range cell processing method. Both of the two strategies have the ability to eliminate or mitigate the effects of envelope misalignment and to increase the robustness of height estimation greatly.