MIMO-Based Forward-Looking SAR Imaging Algorithm and Simulation

Multiple-input multiple-output (MIMO) radar imaging can provide higher resolution and better sensitivity and thus can be applied to targets detection, recognition, and tracking. Missile-borne forward-looking SAR (MFL-SAR) is a new and special MIMO radar mode. It has advantage of two-dimensional (2D) imaging capability in forward direction over monostatic missile-borne SAR and airborne SAR. However, it is difficult to obtain accurate 2D frequency spectrum of the target echo signal due to the high velocity and descending height of this platform, which brings a lot of obstacles to imaging algorithm design. Therefore, a new imaging algorithm for MFL-SAR configuration based on the method of series reversion is proposed in this paper. This imaging method can implement range compression, secondary range compression (SRC), and range cell migration correction (RCMC) effectively. Finally, some simulations of point targets and comparison results confirm the efficiency of our proposed algorithm

Imaging Formation Algorithm of the Ground and Space-Borne Hybrid BiSAR Based on Parameters Estimation from Direct Signal

This paper proposes a novel image formation algorithm for the bistatic synthetic aperture radar (BiSAR) with the configuration of a noncooperative transmitter and a stationary receiver in which the traditional imaging algorithm failed because the necessary imaging parameters cannot be estimated from the limited information from the noncooperative data provider. In the new algorithm, the essential parameters for imaging, such as squint angle, Doppler centroid, and Doppler chirp-rate, will be estimated by full exploration of the recorded direct signal (direct signal is the echo from satellite to stationary receiver directly) from the transmitter. The Doppler chirp-rate is retrieved by modeling the peak phase of direct signal as a quadratic polynomial. The Doppler centroid frequency and the squint angle can be derived from the image contrast optimization. Then the range focusing, the range cell migration correction (RCMC), and the azimuth focusing are implemented by secondary range compression (SRC) and the range cell migration, respectively. At last, the proposed algorithm is validated by imaging of the BiSAR experiment configured with china YAOGAN 10 SAR as the transmitter and the receiver platform located on a building at a height of 109 m in Jiangsu province. The experiment image with geometric correction shows good accordance with local Google images

Validation of CReSIS Synthetic Aperture Radar Processor and Optimal Processing Parameters

Sounding the ice sheets of Greenland and Antarctica is a vital component in determining the effect of global warming on sea level rise. Of particular importance are measurements of the bedrock topography of the outlet glaciers that transport ice from the ice sheet's interior to the margin where it calves into icebergs, contributing to sea level rise. These outlet glaciers are difficult to sound due to crevassing caused by the relatively fast movement of the ice in the glacial channel and higher signal attenuation caused by warmer ice. The Center for Remote Sensing of Ice Sheets (CReSIS) uses multi-channel airborne radars which employ methods for achieving better resolution and signal-to-noise ratio (SNR) to better sound outlet glaciers. Synthetic aperture radar (SAR) techniques are used in the along-track dimension, pulse compression in the range dimension, and an antenna array in the cross-track dimension. CReSIS has developed the CReSIS SAR processor (CSARP) to effectively and efficiently process the data collected by these radars in each dimension. To validate the performance of this processor a SAR simulator was developed with the functionality to test the implementation of the processing algorithms in CSARP. In addition to the implementation of this simulator for validation of processing the data in the along-track, cross-track and range dimensions, there are a number of data-dependent processing steps that can affect the quality of the final data product. CSARP was tested with an ideal simulated point target in white Gaussian noise. The SNR change achieved by range compression, azimuth compression, array combination with and without matched filtering, and lever arm application were all within .2 dB of the theoretical expectation. Channel equalization, when paired with noise-based matched filtering, provided 1-2 dB of gain on average but significantly less than the expected gain. Extending the SAR aperture length to sound bedrock will improve the along-track resolution, but at the expense of SNR. Increasing the taper of a window in the fast-time and slow-time will slightly improve the SNR of the data. Changing the relative permittivity used to process the data improved the resulting SNR by no more than 0.025 dB for the test dataset

Bistatic SAR for Building Wall Material Characterisation

© Cranfield University 2020. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright ownerThis thesis addresses the problem of using radar to extract interpretable information concerning both the structure and electrical properties of a wall, and the environment behind it. This is broken down into two subproblems: how to determine the thickness and electromagnetic properties of the wall without being in direct contact with it, and how to obtain the most accurate images of what lies beyond the wall. Existing research in the area is evaluated and a theoretical study is presented on the use of monostatic, bistatic, and multistatic Synthetic Aperture Radar (SAR) in both one and two dimensional apertures. New methods of determining the wall properties are evaluated by both computer simulation and with laboratory radar measurements, where a wall of concrete blocks is constructed. The robustness of the asymmetric SAR geometry approach is evaluated with the addition of complex objects placed behind the wall. The uncertainty associated with estimating the wall properties is evaluated and consequential improvements to image quality are discussed. It was found that an asymmetric bistatic SAR geometry accurately extracts the refractive index and thickness of a wall. The method is applicable to both cluttered environments and non-parallel wall trajectories without loss of accuracy. Applying a compensation for refraction in the SAR imagery results in better positional accuracy but does not necessarily result in better image focusing. Volumetric multistatic image formation benefits from applied refraction compensation. SAR image formation, and in particular volumetric image formation, can be significantly accelerated via a spatially variant basebanding technique followed by zero padding. Spatially variant basebanding is sub optimal when applied to a Through-Wall radar scenario where there is a visible wall signature in the image. Keywords: Through-Wall radar, Multistatic radar, Multidimensional signal processing, Electromagnetic propagation, Radar imagi

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