In this paper, an advanced technique for the generation of deformation maps using synthetic aperture radar (SAR) data is presented. The algorithm estimates the linear and nonlinear components of the displacement, the error of the digital elevation model (DEM) used to cancel the topographic terms, and the atmospheric artifacts from a reduced set of low spatial resolution interferograms. The pixel candidates are selected from those presenting a good coherence level in the whole set of interferograms and the resulting nonuniform mesh tessellated with the Delauney triangulation to establish connections among them. The linear component of movement and DEM error are estimated adjusting a linear model to the data only on the connections. Later on, this information, once unwrapped to retrieve the absolute values, is used to calculate the nonlinear component of movement and atmospheric artifacts with alternate filtering techniques in both the temporal and spatial domains. The method presents high flexibility with respect to the required number of images and the baselines length. However, better results are obtained with large datasets of short baseline interferograms. The technique has been tested with European Remote Sensing SAR data from an area of Catalonia (Spain) and validated with on-field precise leveling measurements.

The paper presents a new inverse synthetic aperture radar (ISAR) algorithm intended for radar cross-section (RCS) imaging and measurement from scattered fields. The method, based on a spherical-wave near-field illumination of the target, overcomes the requirement for an expensive compact range facility to produce a plane wave illumination. The formulation and the implementation of the algorithm are described. Some experimental results obtained in an anechoic chamber are presented to show RCS results similar to the conventional plane wave methods.

In this paper, a geosynchronous synthetic aperture radar (SAR) (GEOSAR) mission for atmospheric phase screen (APS) retrieval using a long coherent integration of pulses is analyzed. The nearly fixed position of the geosynchronous platforms makes GEOSAR systems suitable for continuous monitoring applications. However, using moderate transmitted powers and antenna sizes, very long integration times up to hours are required. In GEOSAR, the two-way propagation of radar signals can decorrelate significantly due to atmospheric changes during the long data take, resulting in an APS which can cause image defocusing and artifacts. In this paper, the APS effects are analyzed, and an APS correction algorithm from short-term periodic acquisitions (subapertures) of the whole long-term GEOSAR synthetic aperture is described. The results obtained from the APS retrieval algorithm in a simulated GEOSAR acquisition affected by atmospheric decorrelation are presented. Finally, an experimental test of the APS algorithm performance with a long-integration ground-based SAR acquisition is shown.

In this paper, the performance of a nearly zero inclination and low eccentricity geosynchronous synthetic aperture radar (GEOSAR) mission for midlatitude (30°-60°) Earth observation is analyzed. The slow motion of such satellites with respect to the Earth's surface makes it necessary to consider long coherent combination of pulses during hours to reach the desired along-track resolution. A system based on moderate transmitted powers and antenna sizes is considered. The necessary sensitivity in such GEOSAR system is obtained from the accumulated energy of the raw data using a pulse repetition frequency above the Doppler bandwidth and a long integration time. Several issues as a result of the long acquisition, such as target and atmospheric phase screen decorrelation, speckle noise impact on the received signal, and satellite station-keeping requirements, are analyzed. The feasibility of such systems to be placed on a broadcasting communication satellite makes nearly zero inclination GEOSAR a low-cost alternative of current SAR missions.

Detection systems with distributed sensors and data fusion are increasingly used by surveillance systems. A system formed by N inhomogeneous constant false alarm rate (CFAR) detectors (cell-averaging (CA) and ordered statistic (OS) CFAR detectors) is studied. A recursive formulation of an algorithm that permits a fixed level of false alarms in the data fusion center is presented, to set the optimum individual threshold levels in the CFAR receivers and the optimum `K out of N' decision rule in order to maximize the total probability of detection. The algorithm also considers receivers of different quality or with different communication channel qualities connecting them with the fusion center. This procedure has been applied to several hypothetical networks with distributed CA-CFAR and OS-CFAR receivers and for Rayleigh targets and interference, and it was seen that in general the fusion decision OR rule is not always the bestPeer ReviewedPostprint (published version

In this paper, the capability of ultra-wide-band (UWB) sensor arrays for tomographic radar of electrically large objects is presented. The major concern when imaging is extended to real objects is to achieve a correct reconstruction of the object shape and its electric properties. A general framework based on a UWB bifocusing operator (UWB-BF) with good tomographic imaging capabilities is presented. This general approach provides a comprehensive understanding of the basic tradeoffs with regard to sensing geometry and image quality parameters. Through numerical simulations and measurements applied to canonical as well as to complex objects, basic design criteria are assessed and the potential of UWB tomographic radar imaging is presented.