In this paper, we examine the role of polarimetry in synthetic aperture radar (SAR) interferometry. We first propose a general formulation for vector wave interferometry that includes conventional scalar interferometry as a special case. Then, we show how polarimetric basis transformations can be introduced into SAR interferometry and applied to form interferograms between all possible linear combinations of polarization states. This allows us to reveal the strong polarization dependency of the interferometric coherence. We then solve the coherence optimization problem involving maximization of interferometric coherence and formulate a new coherent decomposition for polarimetric SAR interferometry that allows the separation of the effective phase centers of different scattering mechanisms. A simplified stochastic scattering model for an elevated forest canopy is introduced to demonstrate the effectiveness of the proposed algorithms. In this way, we demonstrate the importance of wave polarization for the physical interpretation of SAR interferograms. We investigate the potential of polarimetric SAR interferometry using results from the evaluation of fully polarimetric interferometric shuttle imaging radar (SIR)-C/X-SAR data collected during October 8-9, 1994, over the SE Baikal Lake Selenga delta region of Buriatia, Southeast Siberia, Russia.

Polarimetric SAR interferometry

: This report discusses the use of modern 2-D spectral estimation algorithms for SAR imaging, and makes two principal contributions to the field of adaptive SAR imaging. First, it is a comprehensive comparison of 2-D spectral estimation methods for SAR imaging. It provides a synopsis of the algorithms available, discusses their relative merits for SAR imaging, and illustrates their performance on simulated and collected SAR imagery. The discussion of autoregressive linear predictive techniques (ARLP), including the Tufts Kumaresan variant, is somewhat more general than appears in most of the literature, in that it allows the prediction element to be varied throughout the subaperture. This generality leads to a theoretical link between ARLP and one of Pisarenko's methods. The report also provides a theoretical analysis that predicts the impact of the adaptive sidelobe reduction (ASR) algorithm on target to clutter ratio and provides insight into order and constraint selection. Second, this work develops multi-channel variants of three related algorithms, minimum variance method (MVM), reduced rank MVM (RRMVM), and ASR to estimate both reflectivity intensity and interferometric height from polarimetric displaced-aperture interferometric data. Examples illustrate that MVM and ASR both offer significant advantages over Fourier methods for estimating both scattering intensity and interferometric height, and allow empirical comparison of the accuracies of Fourier, MVM, and- ometric height estimates.

SAR Imaging via Modern 2-D Spectral Estimation Methods. Volume 1. Imaging Methods.

In synthetic aperture radar (SAR) signal processing, an accurate Doppler centroid is required for most applications involving target motion estimation and antenna pointing direction estimation. In some cases the Doppler centroid can be sufficiently determined using available information regarding the terrain topography, the relative motion between the sensor and the terrain, and the antenna pointing direction. But most often, a highly accurate Doppler centroid value has to be derived by analyzing the received SAR signal itself. This kind of signal processing is referred to as Doppler centroid estimation (DCE). This correspondence briefly describes two DCE algorithms, provides a performance summary for these algorithms, and presents the experimental results. These algorithms include a previously reported one and a newly developed one that is optimized for quasi-homogeneous sources. The performance enhancement achieved by the optimal DCE algorithm is clearly demonstrated by the experimental results.

Optimal Doppler centroid estimation for SAR data from a quasi-homogeneous source

Microwave imaging employs detection techniques to evaluate hidden or embedded objects in a structure or media using electromagnetic (EM) waves in the microwave range, 300 MHz-300 GHz. Microwave imaging is often associated with radar detection such as target location and tracking, weather-pattern recognition, and underground surveillance, which are far-field applications. In recent years, due to microwaves' ability to penetrate optically opaque media, shortrange applications, including medical imaging, nondestructive testing (NDT) and quality evaluation, through-the-wall imaging, and security screening, have been developed. Microwave near-field imaging most often occurs when detecting the profile of an object within the short range (when the distance from the sensor to the object is less than one wavelength to several wavelengths) and depends on the electrical size of the antenna(s) and target.

Advances in Microwave Near-Field Imaging: Prototypes, Systems, and Applications

In January 1986, the design of a high-resolution airborne C-band synthetic aperture radar (SAR) started at the Electromagnetics Institute of the Technical University of Denmark. The initial system test flights took place in November and December 1989. The authors describe the design of the system, its implementation, and its performance. They show how digital technology has been utilized to realize a very flexible radar with variable resolution, swath-width, and imaging geometry. The motion-compensation algorithms implemented to obtain the high resolution and the special features built into the system to ensure proper internal calibration are outlined. The data processing system, developed for image generation and quality assurance, is sketched, with special emphasis on the flexibility of the system. >

The Danish SAR system: design and initial tests

High-Resolution Microwave Imaging

In Spaceborne SAR studying and designing, raw date simulation is a common tool. The method of Spaceborne SAR Raw Data Simulation is presented. This method is based on elliptical orbit model. Based on this method, a simulator has been applied to our Spaceborne SAR test. The simulator can deal with real radar sensor parameters and orbit data, and the result of simulation is closed to the fact. In the end, the results of the point target and the three-dimensional (3D) extended scenes are explained. It shows that the Spaceborne SAR raw data simulation is very efficient.

Research on Spaceborne SAR Raw Data Simulation

The most important specifications of spaceborne Synthetic Aperture Radar (SAR) are spatial resolution and swath width. But in conventional SAR, there is a well known trade-off between them because of the pulse mode. A method named Multiple Azimuth Beam (MAB) with single transmitter is proposed to solve these difficulties in previous articles. By this method the swath is about N (beam number) times wider than that of the equivalent conventional SAR, or the azimuth resolution can be improved by a factor of approximately N. Meanwhile, stepped-frequency waveform is often used to obtain large effective bandwidth for high range resolution by transmitting the pulses with sequentially changing carrier frequency. In this paper, a method named sub-aperture sub-band technique is adopted to achieve wide swath and two-dimension high resolution simultaneously.

High Resolution, Wide Swath SAR using Sub-aperture Sub-band Technique

Autofocus algorithm is one of the key technologies for high-resolution SAR signal processing. High-resolution SAR is a coherent imaging system.

Autofocus Algorithm for SAR

Three-stage inversion process is one of the most frequently used methods with PolInSAR data for extracting forest heights. According to this method, forest heights and ground topography can be extracted based on interferometric coherence using a random volume over ground model. In this paper, a coherence value estimation method with adaptive averaging window derived from coherence region shape parameters is presented to improve the accuracy of complex coherence estimate. Moreover, coherence region boundary extraction algorithm is applied to resolve the ambiguity estimation problem of volume decorrelation. Finally, the proposed algorithm is validated by simulated PolInSAR data for canopy simulated by PolInSAR data simulator of PolSARpro software developed by ESA (European Space Agency).

Improved three-stage inversion process for forest height inversion with PolInSAR data

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