137 research outputs found

    Anti-jamming techniques for multichannel SAR imaging

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    © The Institution of Engineering and Technology 2006 IEE Proceedings online no. 20045090An airborne broadband jammer present in the mainbeam of a synthetic aperture radar (SAR) can potentially destroy a large region of the SAR image. In addition to this, multipath reflections from the ground, known as hot-clutter or terrain scattered interference will add a non-stationary interference component to the image. The goal of interference suppression for SAR is to successfully suppress these interferences while not significantly effecting the image quality by blurring, reducing the resolution or raising the sidelobe level. The paper provides an analysis of the degradation from hot-clutter, the limited restoration that multichannel imaging and slow-time space time adaptive processing (STAP) can provide and how fast-time STAP can improve the final image quality.L. Rosenberg and D. Gra

    Frequency Diversity for Improving Synthetic Aperture Radar Imaging

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    In this work, a novel theoretical framework is presented for using recent advances in frequency diversity arrays (FDAs). Unlike a conventional array, the FDA simultaneously transmits a unique frequency from each element in the array. As a result, special time and space properties of the radiation pattern are exploited to improve cross-range resolution. The idealized FDA radiation pattern is compared with and validated against a full-wave electromagnetic solver, and it is shown that the conventional array is a special case of the FDA. A new signal model, based on the FDA, is used to simulate SAR imagery of ideal point mass targets and the new model is used to derive the impulse response function of the SAR system, which is rarely achievable with other analytic methods. This work also presents an innovative solution for using the convolution back-projection algorithm, the gold standard in SAR image processing, and is a significant advantage of the proposed FDA model. The new FDA model and novel SAR system concept of operation are shown to reduce collection time by 33 percent while achieving a 4.5 dB improvement in cross-range resolution as compared to traditional imaging systems

    Adaptive Illumination Patterns for Radar Applications

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    The fundamental goal of Fully Adaptive Radar (FAR) involves full exploitation of the joint, synergistic adaptivity of the radar\u27s transmitter and receiver. Little work has been done to exploit the joint space time Degrees-of-Freedom (DOF) available via an Active Electronically Steered Array (AESA) during the radar\u27s transmit illumination cycle. This research introduces Adaptive Illumination Patterns (AIP) as a means for exploiting this previously untapped transmit DOF. This research investigates ways to mitigate clutter interference effects by adapting the illumination pattern on transmit. Two types of illumination pattern adaptivity were explored, termed Space Time Illumination Patterns (STIP) and Scene Adaptive Illumination Patterns (SAIP). Using clairvoyant knowledge, STIP demonstrates the ability to remove sidelobe clutter at user specified Doppler frequencies, resulting in optimum receiver performance using a non-adaptive receive processor. Using available database knowledge, SAIP demonstrated the ability to reduce training data heterogeneity in dense target environments, thereby greatly improving the minimum discernable velocity achieved through STAP processing

    The Bi-directional Spatial Spectrum for MIMO Radar and Its Applications

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    <p>Radar systems have long applied electronically-steered phased arrays to discriminate returns in azimuth angle and elevation angle. On receiver arrays, beamforming is performed after reception of the data, allowing for many adaptive array processing algorithms to be employed. However, on transmitter arrays, up until recently pre-determined phase shifts had to applied to each transmitter element before transmission, precluding adaptive transmit array processing schemes. Recent advances in multiple-input multiple-output radar techniques have allowed for transmitter channels to separated after data reception, allowing for virtual non-causal "after-the-fact" transmit beamforming. The ability to discriminate in both direction-of-arrival and direction-of-departure allows for the novel ability to discriminate line-of-sight returns from multipath returns. This works extends the concept of virtual non-causal transmit beamforming to the broader concept of a bi-directional spatial spectrum, and describes application of such a spectrum to applications such as spread-Doppler multipath clutter mitigation in ground-vehicle radar, and calibration of a receiver array of a MIMO system with ground clutter only. Additionally, for this work, a low-power MIMO radar testbed was developed for lab testing of MIMO radar concepts.</p>Dissertatio

    Radar Signal Processing for Interference Mitigation

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    It is necessary for radars to suppress interferences to near the noise level to achieve the best performance in target detection and measurements. In this dissertation work, innovative signal processing approaches are proposed to effectively mitigate two of the most common types of interferences: jammers and clutter. Two types of radar systems are considered for developing new signal processing algorithms: phased-array radar and multiple-input multiple-output (MIMO) radar. For phased-array radar, an innovative target-clutter feature-based recognition approach termed as Beam-Doppler Image Feature Recognition (BDIFR) is proposed to detect moving targets in inhomogeneous clutter. Moreover, a new ground moving target detection algorithm is proposed for airborne radar. The essence of this algorithm is to compensate for the ground clutter Doppler shift caused by the moving platform and then to cancel the Doppler-compensated clutter using MTI filters that are commonly used in ground-based radar systems. Without the need of clutter estimation, the new algorithms outperform the conventional Space-Time Adaptive Processing (STAP) algorithm in ground moving target detection in inhomogeneous clutter. For MIMO radar, a time-efficient reduced-dimensional clutter suppression algorithm termed as Reduced-dimension Space-time Adaptive Processing (RSTAP) is proposed to minimize the number of the training samples required for clutter estimation. To deal with highly heterogeneous clutter more effectively, we also proposed a robust deterministic STAP algorithm operating on snapshot-to-snapshot basis. For cancelling jammers in the radar mainlobe direction, an innovative jamming elimination approach is proposed based on coherent MIMO radar adaptive beamforming. When combined with mutual information (MI) based cognitive radar transmit waveform design, this new approach can be used to enable spectrum sharing effectively between radar and wireless communication systems. The proposed interference mitigation approaches are validated by carrying out simulations for typical radar operation scenarios. The advantages of the proposed interference mitigation methods over the existing signal processing techniques are demonstrated both analytically and empirically
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