Radar signature characterization from wind turbine scattering

textThe growth in the number of wind farms has raised significant concerns in the radar community due to their potential interference on radar systems. The motion of the turbine blades creates unwanted Doppler clutter that can interfere in the tracking of moving targets. Large turbine structures can also produce electromagnetic shadows that may make observing objects behind a wind farm difficult. Detailed characterization of the clutter is the first step towards effective mitigation techniques. The goal of this dissertation research is to gain a better understanding of the dynamic radar signatures resulting from scattering by wind turbines. First, the scattering characteristics of turbines in the presence of ground surface are studied. Image theory in conjunction with a shooting-and-bouncing ray code, Ahilo, is used to carry out the dynamic signature simulation. The observed features in the simulation are corroborated with laboratory model measurements. Second, the effects of higher order motions of a turbine undergoing rotation on the radar signatures are investigated and characterized. Mathematical models for the motions are proposed and used to simulate the joint time-frequency and inverse synthetic aperture radar characteristics of the turbine undergoing these motions. The motions are studied for an isolated turbine as well as for a turbine rotating above a ground. Selected motions are corroborated by laboratory model measurements. Next, a method to remove the dynamic clutter produced by wind turbines is presented. A physics-based basis is constructed to model the radar backscattering from a wind turbine. This basis is used in conjunction with the matching pursuit algorithm to iteratively remove the Doppler clutter due to wind turbines. The algorithm is tested using radar return generated using Ahilo. Finally, radar features of wind turbines are simulated and studied in the HF (high frequency) band. The features are presented in the range-Doppler plane for single as well as arrays of turbines. Doppler aliasing due to the limited pulse repetition frequency of HF radars is examined. Shadowing characteristics of arrays of turbines are simulated and analyzed. Electromagnetic modeling details including effects of thin-wire modeling, non-conducting turbine components, and the presence of a conducting ground surface are discussed.Electrical and Computer Engineerin

Decentralized Subspace Pursuit for Joint Sparsity Pattern Recovery

To solve the problem of joint sparsity pattern recovery in a decen-tralized network, we propose an algorithm named decentralized and collaborative subspace pursuit (DCSP). The basic idea of DCSP is to embed collaboration among nodes and fusion strategy into each iteration of the standard subspace pursuit (SP) algorithm. In DCSP, each node collaborates with several of its neighbors by sharing high-dimensional coefficient estimates and communicates with other remote nodes by exchanging low-dimensional support set estimates. Experimental evaluations show that, compared with several existing algorithms for sparsity pattern recovery, DCSP produces satisfactory results in terms of accuracy of sparsity pattern recovery with much less communication cost.Comment: 5 pages, 3 figures, accepted by ICASSP 201

Multiple input multiple output radar three dimensional imaging technique

Ph.DDOCTOR OF PHILOSOPH

高精度3次元近距離レーダに関する研究

Tohoku University佐藤源之課

ON SOME COMMON COMPRESSIVE SENSING RECOVERY ALGORITHMS AND APPLICATIONS

Compressive Sensing, as an emerging technique in signal processing is reviewed in this paper together with its’ common applications. As an alternative to the traditional signal sampling, Compressive Sensing allows a new acquisition strategy with significantly reduced number of samples needed for accurate signal reconstruction. The basic ideas and motivation behind this approach are provided in the theoretical part of the paper. The commonly used algorithms for missing data reconstruction are presented. The Compressive Sensing applications have gained significant attention leading to an intensive growth of signal processing possibilities. Hence, some of the existing practical applications assuming different types of signals in real-world scenarios are described and analyzed as well

コンプレッシブ・センシングによる合成開口レーダの高分解能化

Tohoku University佐藤源之課

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