Phased array imaging of moving targets with randomized beamsteering and area spotlighting

This paper presents a system model and inversion for imaging moving targets using phased arrays. The system model provides a mathematical framework to represent the motion of a moving target in the beam-steering domain which is identified as the slow-time domain. The inversion provides a reconstruction of the moving targets in the spatial and velocity domains. It is shown that a randomized beam steering strategy in the slow-time domain can improve the resolution in the velocity domain. The imaging problem is also formulated for a phased array system that spotlights a target area with its transmitted beam to improve the target to clutter power ratio, and obtains beam-steered data in the receive mode for high-resolution imaging. We cite a diagnostic medical ultrasound problem due to the practical difficulties and challenges that are associated with it.     

Multiresolution dynamic image representation with uniform andfoveal spiral scan data

This work addresses the problem of representing a dynamic image via its temporal spiral scan data. Two types of spiral scan data are considered: uniform density and foveal. Spatial sampling strategies for these two spiral scans are examined. A signal model is developed to interpret the temporal readouts of repeated spiral scans via two separate time variables, the slow time and fast time. This mathematical model is used to construct a method for forming the time progression of the target image. A method for increasing the repetition rate of the spiral data collection via utilizing both forward and backward spiral scans is presented. Results are provided.     

Signal subspace fusion of uncalibrated sensors with application inSAR and diagnostic medicine

Addresses the problem of fusing the information content of two uncalibrated sensors. This problem arises in registering images of a scene when it is viewed via two different sensory systems, or detecting change in a scene when it is viewed at two different time points by a sensory system, or via two different sensory systems or observation channels. We are concerned with sensory systems which have not only a relative shift, scaling and rotational calibration error, but also an unknown point spread function (that is time varying for a single sensor, or different for two sensors). By modeling one image in terms of an unknown linear combination of the other image, its powers and their spatially transformed (shift, rotation and scaling) versions, a signal subspace processing is developed for fusing uncalibrated sensors. The proposed method is shown to be applicable in moving target detection (MTD) using monopulse synthetic aperture radar (SAR) with uncalibrated radars. Results are shown for video, magnetic resonance images of a human brain, moving target detector monopulse SAR, and registration of SAR images of a target obtained via two different radars or at different coordinates by the same radar for automatic target recognition (ATR).     

Phase and amplitude phase restoration in synthetic aperture radarimaging

Methods for addressing two types of multiplicative noise in synthetic aperture radar (SAR) imaging are presented. The authors consider a multiplicative noise with a real phase (i.e. the SAR signal's phase is contaminated but its amplitude is uncorrupted) that possesses unknown functional characteristics with respect to the radar signal's temporal frequencies. A perturbation solution for phase reconstruction from amplitude is developed from a wave equation governing the SAR signal and a Riccati equation that relates the amplitude and phase functions of the SAR signal. This solution is converted into a noniterative analytical solution in terms of the moments and powers of the log amplitude function. Next, the authors consider a multiplicative noise with a complex phase (i.e. both the amplitude and phase of the SAR signal are contaminated) that varies linearly with respect to the radar signal's temporal frequencies. The two wave equations governing the SAR signal at two temporal frequencies of the radar signal are combined to derive a method to reconstruct the complex phase error function.     

Array imaging with beam-steered data

The author presents a system model and inversion for the beam-steered data obtained by linearly varying the relative phase among the elements of an array, also known as phased array scan data. The system model and inversion incorporate the radiation pattern of the array's elements. The inversion method utilizes the time samples of the echoed signals for each scan angle instead of range focusing. It is shown that the temporal Fourier transform of the phased array scan data provides the distribution of the spatial Fourier transform of the reflectivity function for the medium to be imaged. The extent of this coverage is related to the array's length and the temporal frequency bandwidth of the transmitted pulsed signal. Sampling constraints and reconstruction procedure for the imaging system are discussed. It is shown that the imaging information obtained by the inversion of phased array scan data is equivalent to the image reconstructed from its synthesized array counterpart.     

Signal subspace change detection in averaged multilook SAR imagery

This paper addresses change detection in averaged multilook synthetic aperture radar (SAR) imagery. Averaged multilook SAR images are preferable to full-aperture SAR reconstructions when the imaging algorithm is approximation-based (e.g., polar format processing) or when motion data are not accurate over a long full aperture. We examine the application of a SAR change-detection method, known as signal subspace processing, which is based on the principles of two-dimensional adaptive filtering, and we use it to recognize the addition of surface landmines to a particular area under surveillance. We describe the change-detection problem as a trinary hypothesis testing problem, and define a change signal and its normalized version to determine whether: 1) there is no change in the imaged scene; 2) a target has entered the imaged scene; or 3) a target has exited the imaged scene. A statistical analysis of the error signal is provided to show its properties and merits. Results are presented for averaged noncoherent multilook and coherent single-look X-band SAR imagery.     

Reconnaissance with slant plane circular SAR imaging

This paper presents a method for imaging from the slant plane data collected by a synthetic aperture radar (SAR) over the full rotation or a partial segment of a circular flight path. A Fourier analysis for the Green's function of the imaging system is provided. This analysis is the basis of an inversion for slant plane circular SAR data. The reconstruction algorithm and resolution for this SAR system are outlined. It is shown that the slant plane circular SAR, unlike the slant plane linear SAR, has the capability to extract three-dimensional imaging information of a target scene. The merits of the algorithm are demonstrated via a simulated target whose ultra wideband foliage penetrating (FOPEN) or ground penetrating (GPEN) ultrahigh frequency (UHF) radar signature varies with the radar's aspect angle.     

Blind-velocity SAR/ISAR imaging of a moving target in a stationarybackground

A synthetic aperture radio/inverse synthetic aperture radar (SAR/ISAR) coherent system model and inversion to image a target moving with an unknown constant velocity in a stationary background are presented. The approach is based on a recently developed system modelling and inversion principle for SAR/ISAR imaging that utilizes the spatial Fourier decomposition of SAR data in the synthetic aperture domain to convert the SAR system model's nonlinear phase functions into linear phase functions suitable for a computationally manageable inversion. It is shown that SAR/ISAR imaging of a moving target can be converted into imaging the target in a stationary squint-mode SAR problem where the parameters of the squint-mode geometry depend on the target's velocity. A method for estimating the moving target's velocity that utilizes a spatial Doppler analysis of the SAR data within overlapping subapertures is presented. The spatial Doppler technique does not require the radar signal to be narrowband, so the reconstructed image's resolution is not sacrificed to improve the target's velocity estimator.