Antenna Array for Passive Radar: Configuration Design and Adaptive Approaches to Disturbance Cancellation

Villano, Michelangelo; Colone, Fabiola; Lombardo, P.

doi:10.1155/2013/920639

Cited by 13 publications

(17 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Eigen-subspace-based beamforming techniques for passive radar application is proposed in [4,5]. According to these works, the spatial correlation matrix can be decomposed to the Topics in Radar Signal Processingsignal subspace and the noise subspace.…”

Section: Subspace-based Techniquementioning

confidence: 99%

“…The adaptive optimum beamformer for passive radar application has been investigated in [2,3]. Methods which utilize the eigenstructure of the spatial correlation matrix have been proposed in [4,5]. Moscardini et al [6] have made efforts to identify the most suitable multi-channel processing architecture.…”

Section: Introductionmentioning

confidence: 99%

“…Their work focuses on the optimum beamformer for digital video broadcasting-terrestrial (DVB-T)-based systems. Villano et al examined the non-adaptive beam steering and null-steering methods as well as the adaptive correlation matrix inversion-based methods [5].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Clutter Cancellation Techniques for Passive Radars

Pető¹,

Seller²

2018

Topics in Radar Signal Processing

View full text Add to dashboard Cite

In radar systems, the ambiguity function of the applied illuminator signal essentially determines the detection capabilities. Zero Doppler interference (ZDI) or close targets returns can mask weak target reflections from higher distances. This is particularly the case for passive radars where the illuminator signal is not under the control of the radar designer. In recent times, great efforts have been carried out to research and develop efficiently working filter algorithms. These adaptive algorithms aim to cancel the undesired interference components in order to enhance the useful dynamic range. A number of different algorithms are operating in the space and also in the time domain. Spatial algorithms apply beamforming techniques, while temporal algorithms utilize the available reference signal to suppress the interferences. The main goal of this chapter is to present and compare the available spatial and temporal adaptive interference cancellation techniques in terms of filtering efficiency and computationcostonreal-lifedata.

show abstract

Section: Subspace-based Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Clutter Cancellation Techniques for Passive Radars

Pető¹,

Seller²

2018

Topics in Radar Signal Processing

View full text Add to dashboard Cite

show abstract

“…Note that the outputs of this particular CAF remain in the range-Doppler plane unlike other approaches (see e.g. [4], [5], [6], [7], [8]) using CAF built on a spatial model where the angular parameters increase the output dimension.…”

Section: A a "Blind" Cross-ambiguity Function (Caf)mentioning

confidence: 99%

“…For ground radars, this dominant interference is mostly caused by zero-Doppler contribution (ZDC). Note that space-time approaches based on cross-ambiguity function [4], [5], [6], [7], [8] also recommend a ZDC rejection. For airborne radars, rejection of the Doppler shifted strongest contributions is also required with the risk that some targets of interest (often in practice the slowest moving targets) fall in the rejection band of the filter [9].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Target Detection Techniques for OFDM-Based Passive Radar Exploiting Spatial Diversity

Chabriel

Barrère

2017

IEEE Trans. Signal Process.

View full text Add to dashboard Cite

Abstract-Recently, it has been studied the benefit of using a channel-based detector (CHAD) with a passive radar exploiting OFDM waveforms radiated e.g. by DVB-T transmitters of opportunity. When multiple antennas are available on receive, we state that CHAD can be seen as space-time array-processing performing on a particular coherent frequency datacube. Building on this new interpretation, we propose an improved version of CHAD in the form of a fully dimensional space-time adaptive processing. Optimization of the signal-to-interference-plus-noise ratio is obtained combining a linearly constrained minimum variance (LCMV) space-time adaptive beamforming and a least squares (LS) spatial adaptive filtering. Unlike classical STAP approaches, no training data are here used and only one space-time sample matrix inversion is required. The computational load is then highly reduced allowing a practical deployment. Moreover, since no beamscan in space is performed, the knowledge of array characteristics is not required and the performance shall not be impacted by any calibration errors. Finally, the full set of target signal returns being collected in a single range-Doppler surveillance map, the detection process is then simplified. Results on experimental data show the interests of this new surveillance scheme: no need for a prior rejection of the dominant interference, systematic reduction of secondary lobes, discrimination of slow moving targets.

show abstract