An efficient imaging algorithm for GNSS-R bi-static SAR

Global Navigation Satellite System Reflectometry (GNSS-R) based Bi-static Synthetic Aperture Radar (BSAR) is becoming more and more important in remote sensing, given its low power, low mass, low cost, and real-time global coverage capability. Due to its complex configuration, the imaging for GNSS-R BSAR is usually based on the Back-Projection Algorithm (BPA), which is very time consuming. In this paper, an efficient and general imaging algorithm for GNSS-R BSAR is presented. A Two Step Range Cell Migration (TSRCM) correction is firstly applied. The first step roughly compensates the RCM and Doppler phase caused by the motion of the transmitter, which simplifies the SAR data into the quasi-mono-static case. The second step removes the residual RCM caused by the motion of the receiver using the modified frequency scaling algorithm. Then, a cubic phase perturbation operation is introduced to equalize the Doppler frequency modulation rate along the same range cell. Finally, azimuth phase compensation and geometric correction are completed to obtain the focused SAR image. A simulation and experiment are conducted to demonstrate the feasibility of the proposed algorithm, showing that the proposed algorithm is more efficient than the BPA, without causing significant degradation in imaging quality

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

Frequency-modulated continuous-wave synthetic-aperture radar: improvements in signal processing

With the advance of solid state devices, frequency-modulated continuous-wave (FMCW) designs have recently been used in synthetic-aperture radar (SAR) to decrease cost, size, weight and power consumption, making it deployable on smaller mobile plat-forms, including small (< 25 kg) unmanned aerial vehicle(s) (UAV). To foster its mobile uses, several SAR capabilities were studied: moving target indication (MTI) for increased situational awareness, bistatic operation, e.g. in UAV formation flights, for increased range, and signal processing algorithms for faster real-time performance. Most off-the-shelf SAR systems for small mobile platforms are commercial proprie-tary and/or military (ITAR, International Trades in Arms Regulations) restricted. As such, it necessitated the design and build of a prototype FMCW SAR system at the early stage to serve as a research tool. This enabled unrestricted hardware and software modifica-tions and experimentation. A model to analyze the triangularly modulated (TM) linear frequency modulated (LFM) waveform as one signal was established and used to develop a MTI algorithm which is effective for slow moving targets detection. Experimental field data collected by the prototyped FMCW SAR was then used to validate and demonstrate the effectiveness of the proposed MTI method. A bistatic FMCW SAR model was next introduced: Bistatic configuration is a poten-tial technique to overcome the power leakage problem in monostatic FMCW SAR. By mounting the transmitter and receiver on spatially separate mobile (UAV) platforms in formation deployment, the operation range of a bistatic FMCW SAR can be significantly improved. The proposed approximation algorithm established a signal model for bistatic FMCW SAR by using the Fresnel approximation. This model allows the existing signal processing algorithms to be used in bistatic FMCW SAR image generation without sig-nificant modification simplifying bistatic FMCW SAR signal processing. The proposed range migration algorithm is a versatile and efficient FMCW SAR sig-nal processing algorithm which requires less memory and computational load than the traditional RMA. This imaging algorithm can be employed for real-time image genera-tion by the FMCW SAR system on mobile platforms. Simulation results verified the pro-posed spectral model and experimental data demonstrated the effectiveness of the modi-fied RMA

Opportunistic radar imaging using a multichannel receiver

Bistatic Synthetic Aperture Radars have a physically separated transmitter and receiver where one or both are moving. Besides the advantages of reduced procurement and maintenance costs, the receiving system can sense passively while remaining covert which offers obvious tactical advantages. In this work, spaceborne monostatic SARs are used as emitters of opportunity with a stationary ground-based receiver. The imaging mode of SAR systems over land is usually a wide-swath mode such as ScanSAR or TOPSAR in which the antenna scans the area of interest in range to image a larger swath at the expense of degraded cross-range resolution compared to the conventional stripmap mode. In the bistatic geometry considered here, the signals from the sidelobes of the scanning beams illuminating the adjacent sub-swath are exploited to produce images with high cross-range resolution from data obtained from a SAR system operating in wide-swath mode. To achieve this, the SAR inverse problem is rigorously formulated and solved using a Maximum A Posteriori estimation method providing enhanced cross-range resolution compared to that obtained by classical burst-mode SAR processing. This dramatically increases the number of useful images that can be produced using emitters of opportunity. Signals from any radar satellite in the receiving band of the receiver can be used, thus further decreasing the revisit time of the area of interest. As a comparison, a compressive sensing-based method is critically analysed and proves more sensitive to off-grid targets and only suited to sparse scene. The novel SAR imaging method is demonstrated using simulated data and real measurements from C-band satellites such as RADARSAT-2 and ESA’s satellites ERS-2, ENVISAT and Sentinel-1A. In addition, this thesis analyses the main technological issues in bistatic SAR such as the azimuth-variant characteristic of bistatic data and the effect of imperfect synchronisation between the non-cooperative transmitter and the receiver