Television-based bistatic radar

Griffiths, Hugh; Long, Ningbo

doi:10.1049/ip-f-1.1986.0104

Cited by 230 publications

(96 citation statements)

References 3 publications

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“…Passive radar encompasses a class of radar systems that detect and track objects by processing reflections from noncooperative illumination sources of opportunity in the environment, such as commercial broadcast and communications signals [1][2][3]. Due to the inherent narrow signal bandwidth and low carrier frequency properties of the transmitted signals, passive radar often suffers from low spatial resolution [4] a .…”

Section: Introductionmentioning

confidence: 99%

Low-complexity sparse reconstruction for high-resolution multi-static passive SAR imaging*

Mao

Zhang

Amin

2014

EURASIP J. Adv. Signal Process.

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Bi-static passive synthetic aperture radar (SAR) systems using ground broadcast and wireless network signals suffer from a low spatial resolution due to the narrow bandwidths and low carrier frequencies. By exploiting multiple distributed illuminators, multi-static passive radar has the possibility of producing high-resolution SAR images. In this paper, a two-stage image formation approach, which combines the Fourier transform and sparse reconstruction strategies, is proposed to process multi-static SAR data. This method exploits the group sparsity of the sparse scene, i.e., the observations associated with different bi-static pairs share the same support of the sparse scene but correspond to aspect-dependent scattering coefficients. Such observations are described as a number of generally disjoint sub-bands in the two-dimensional spatial frequency domain. In each sub-band, the sampling satisfies the Nyquist criterion, whereas different sub-bands are sparsely distributed. In the proposed approach, Fourier-based reconstruction is applied to the sub-band data to produce the coarse-resolution images, which are then combined to produce a high-resolution image through the exploitation of sparse reconstruction techniques. The proposed approach greatly improves the imaging quality as compared to Fourier-based reconstruction, whereas it exhibits significant reduction of the computational complexity when compared to direct application of sparse reconstruction techniques. The exploitation of block sparsity-based techniques also permits practical treatment of the angle-dependent target scattering characteristics in SAR image reconstruction. The advantages of the proposed approach are delineated using analysis and simulations.

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Section: Introductionmentioning

confidence: 99%

Low-complexity sparse reconstruction for high-resolution multi-static passive SAR imaging*

Mao

Zhang

Amin

2014

EURASIP J. Adv. Signal Process.

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“…With the rapid growth of broadcasting stations, mobile phone base stations, communication and navigation satellites, as well as relatively low cost and rapid deployment of receivers, passive radar imaging using transmitters of opportunity has emerged as an active area of research in recent years [1]- [7].…”

Section: Introductionmentioning

confidence: 99%

Passive radar imaging of moving targets with sparsely distributed receivers

Wang

Yaz

2010

2010 IEEE Sensor Array and Multichannel Signal Processing Workshop

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Abstract-We develop a novel passive image formation method for moving targets using measurements from a sparse array of receivers that rely on illumination sources of opportunity. We use a physics-based approach to model the wave propagation and develop a passive measurement model that expresses the measurement at each receiver in terms of the measurement at a different receiver. This model eliminates the need for knowledge about the transmitter locations and waveforms in the proposed image formation method. We formulate the image formation problem as a Generalized Likelihood Ratio Test (GLRT) for unknown target location and velocity using the proposed passive measurement model. We form the image in spatial and velocity space using the space-and velocity-resolved test-statistics.

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“…[1][2][3][4][5][6][7][8][9][10][11][12][13] Based on the fact that most of the transmitters of opportunity are single-frequency or ultra-narrowband sources, such as radio and TV stations, we consider passive airborne receivers that use backscattered signals from sources of opportunity transmitting fixed-frequency waveforms. These waveforms are also referred to as high-Doppler-resolution or continuous-wave (CW) waveforms.…”

Section: Introductionmentioning

confidence: 99%

Doppler Synthetic Aperture Hitchhiker imaging

Yarman¹,

Yazıcı

2008

2008 IEEE Radar Conference

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We consider passive airborne receivers that use backscattered signals from sources of opportunity transmitting fixed-frequency waveforms, which we refer to as Doppler Synthetic Aperture Hitchhiker (DSAH). We present a novel image formation method for DSAH. Our method first correlates the windowed signal obtained from one receiver with the windowed, filtered, scaled and translated version of the received signal from another receiver, and then uses the microlocal analysis to reconstruct the scene radiance by the weighted-backprojection of the correlated signal. This imaging algorithm can put the visible edges of the scene radiance at the correct location, and under appropriate conditions, with correct strength. We show that the resolution of the image is directly related to the length of the support of the windowing function and the frequency of the transmitted waveform. We present numerical experiments to demonstrate the performance of the proposed method.

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Television-based bistatic radar

Cited by 230 publications

References 3 publications

Low-complexity sparse reconstruction for high-resolution multi-static passive SAR imaging*

Low-complexity sparse reconstruction for high-resolution multi-static passive SAR imaging*

Passive radar imaging of moving targets with sparsely distributed receivers

Doppler Synthetic Aperture Hitchhiker imaging

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