A NEW CONICAL-TRAJECTORY POLAR FORMAT ALGORITHM FOR SPOTLIGHT BISTATIC SAR

Abstract-The Polar Format Algorithm (PFA) is suitable for spotlight synthetic aperture radar (SAR) image focusing either in monostatic or bistatic cases. The classic linear-trajectory PFA complete data correction in wavenumber domain, converting data from the polar format to the rectangular format. However, the twodimension processing (either using interpolation or chirp-z transform) introduces heavy computational load, which limits its real-time applications. This study presents a conical-trajectory PFA for bistatic SAR, in which the transmitter and receiver are designed to fly on conical surfaces, to simplify image formation procedures via eliminating the necessity of range processing. Moreover, the conicaltrajectory PFA provides a space-invariant range resolution to simplify the SAR image comprehension. A spotlight forward-looking bistatic missile guidance application was simulated for the algorithm validation and performance analysis

Advances in Synthetic Aperture Radar from a Wavenumber Perspective

This dissertation examines the wavenumber domain of Synthetic Aperture Radar (SAR) images. This domain is the inverse Fourier transform domain of a SAR image. The dissertation begins with the radar receiver's signal model and develops equations describing the wavenumber domain of a SAR image produced by a generalized bistatic and monostatic SAR system. Then, closed form expressions for bistatic synthetic aperture radar spatial resolution of a generalized system from the wavenumber domain are developed. These spatial resolution equations have not previously appeared in the literature. From these equations, significant resolution is found in both range and cross-range forecasting a forward-scatter bistatic SAR image when the elevation angles of each bistatic platform are significantly different. Next, wavenumber and time domain image formation algorithms are discussed. Developed within this dissertation is a wavenumber preprocessing method that increases the speed of the Back Projection Algorithm (BPA). This preprocessing method takes advantage of deramped SAR radar returns and their polar wavenumber format. This new algorithm is called the Fast Decimated Wavenumber Back Projection Algorithm (FDWBPA). Matlab functions are included to implement this algorithm, simulate bistatic SAR images and process the data from anechoic chamber tests demonstrating forward scatter resolution

Signal processing for microwave imaging systems with very sparse array

This dissertation investigates image reconstruction algorithms for near-field, two dimensional (2D) synthetic aperture radar (SAR) using compressed sensing (CS) based methods. In conventional SAR imaging systems, acquiring higher-quality images requires longer measuring time and/or more elements in an antenna array. Millimeter wave imaging systems using evenly-spaced antenna arrays also have spatial resolution constraints due to the large size of the antennas. This dissertation applies the CS principle to a bistatic antenna array that consists of separate transmitter and receiver subarrays very sparsely and non-uniformly distributed on a 2D plane. One pair of transmitter and receiver elements is turned on at a time, and different pairs are turned on in series to achieve synthetic aperture and controlled random measurements. This dissertation contributes to CS-hardware co-design by proposing several signal-processing methods, including monostatic approximation, re-gridding, adaptive interpolation, CS-based reconstruction, and image denoising. The proposed algorithms enable the successful implementation of CS-SAR hardware cameras, improve the resolution and image quality, and reduce hardware cost and experiment time. This dissertation also describes and analyzes the results for each independent method. The algorithms proposed in this dissertation break the limitations of hardware configuration. By using 16 x 16 transmit and receive elements with an average space of 16 mm, the sparse-array camera achieves the image resolution of 2 mm. This is equivalent to six percent of the λ/4 evenly-spaced array. The reconstructed images achieve similar quality as the fully-sampled array with the structure similarity (SSIM) larger than 0.8 and peak signal-to-noise ratio (PSNR) greater than 25 --Abstract, page iv

Passive Synthetic Aperture Radar Imaging Using Commercial OFDM Communication Networks

Modern communication systems provide myriad opportunities for passive radar applications. OFDM is a popular waveform used widely in wireless communication networks today. Understanding the structure of these networks becomes critical in future passive radar systems design and concept development. This research develops collection and signal processing models to produce passive SAR ground images using OFDM communication networks. The OFDM-based WiMAX network is selected as a relevant example and is evaluated as a viable source for radar ground imaging. The monostatic and bistatic phase history models for OFDM are derived and validated with experimental single dimensional data. An airborne passive collection model is defined and signal processing approaches are proposed providing practical solutions to passive SAR imaging scenarios. Finally, experimental SAR images using general OFDM and WiMAX waveforms are shown to validate the overarching signal processing concept

Wide-Angle Multistatic Synthetic Aperture Radar: Focused Image Formation and Aliasing Artifact Mitigation

Traditional monostatic Synthetic Aperture Radar (SAR) platforms force the user to choose between two image types: larger, low resolution images or smaller, high resolution images. Switching to a Wide-Angle Multistatic Synthetic Aperture Radar (WAM-SAR) approach allows formation of large high-resolution images. Unfortunately, WAM-SAR suffers from two significant implementation problems. First, wavefront curvature effects, non-linear flight paths, and warped ground planes lead to image defocusing with traditional SAR processing methods. A new 3-D monostatic/bistatic image formation routine solves the defocusing problem, correcting for all relevant wide-angle effects. Inverse SAR (ISAR) imagery from a Radar Cross Section (RCS) chamber validates this approach. The second implementation problem stems from the large Doppler spread in the wide-angle scene, leading to severe aliasing problems. This research effort develops a new anti-aliasing technique using randomized Stepped-Frequency (SF) waveforms to form Doppler filter nulls coinciding with aliasing artifact locations. Both simulation and laboratory results demonstrate effective performance, eliminating more than 99% of the aliased energy